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Power transmission and control include the conversion, transmission, and distribution of power, and the actuating of control in the end implement block; it plays an important part in the power and the vehicle of machines [...]

Abstract Magnetically coupled rodless cylinders are widely used in the coordinate positioning of mechanical arms, electrostatic paintings, and other industrial applications. However, they exhibit strong nonlinear characteristics, which lead to low servo control accuracy. In this study, a mass-flow equation through the valve port was derived to improve the control performance, considering the characteristics of the dynamics and throttle-hole flow. Subsequently, a friction model combining static, viscous, and Coulomb friction with a zero-velocity interval was proposed. In addition, energy and dynamic models were set for the experimental investigation of the magnetically coupled rodless cylinder. A nonlinear mathematical model for the position of the magnetically coupled rodless cylinder was proposed. An incremental PID controller was designed for the magnetically coupled rodless cylinder to control this system, and the PID parameters were adjusted online using RBF neural network. The response results of the PID parameters based on the RBF neural network were compared with those of the traditional incremental PID control, which proved the superiority of the optimization control algorithm of the incremental PID parameters based on the RBF neural network servo control system. The experimental results of this model were compared with the simulation results. The average error between the established model and the actual system was 0.005175054 (m), which was approximately 2.588% of the total travel length, demonstrating the accuracy of the theoretical model.

Most traditional rigid grippers can cause damage to the surface of objects in actual production processes and are susceptible to factors such as different shapes, sizes, materials, and positions of the product. This article studies a flexible finger for flexible grippers, more commonly described as PneuNet, designs the structure of the finger, discusses the processing and manufacturing methods of the flexible finger, and prepares a physical model. The influence of structural parameters such as the thickness of the flexible finger and the angle of the air chamber on the bending performance of the finger was analyzed using the Abaqus simulation tool. An RBF-PID control algorithm was used to stabilize the internal air pressure of the flexible fingers. A flexible finger stabilization experimental platform was built to test the ultimate pressure, ultimate bending angle, and end contact force of the fingers, and the simulation results were experimentally verified. The results show that when the thickness of the flexible finger is 2 mm and the air chamber angle is 0 deg, the maximum bending angle of the flexible finger can reach about 136.3°. Under the same air pressure, the bending angle is inversely correlated with the air chamber angle and finger thickness. The experimental error of the bending angle does not exceed 3%, which is consistent with the simulation results as a whole. When the thickness is 2 mm, the maximum end contact force can reach about 1.32 N, and the end contact force decreases with the increase in the air chamber angle. The RBF-PID control algorithm used has improved response speed and a better control effect compared to traditional PID control algorithms. This article provides a clear reference for the application of flexible fingers and flexible grippers, and this research method can be applied to the analysis and design optimization of other soft brakes.

Abstract The transportation of hydrogen is a weak link in the large‐scale development of the hydrogen energy industry. Injecting hydrogen into the natural gas pipeline network for transportation is an efficient way to achieve the large‐scale, long‐distance, and low‐cost transportation of hydrogen. Hydrogen can lead to hydrogen embrittlement in natural gas pipelines and cause safety incidents if hydrogen and natural gas are not mixed uniformly. Therefore, it is necessary to study the blending process and blending uniformity of hydrogen and natural gas. In this study, a three‐dimensional model of the hydrogen‐injected natural gas pipeline was constructed. The effects of hydrogen injection inlet and turbulator configuration on the mixing process of hydrogen and natural gas were investigated using a computational fluid dynamics approach. The results show that increasing the number of hydrogen injection inlets shortens the distance L98% of uniform mixing of hydrogen and natural gas. Increasing the radial distance r from the initial hydrogen mixing positions to the center of the pipeline will shorten the distance for uniform gas mixing in the pipeline. The addition of turbulator configurations in the pipeline significantly reduces the distance to uniform gas mixing. Changing the distance Lturb from the turbulator to the initial mixing position further shortens the distance between hydrogen and natural gas mixing uniformly. The results of this study provide a reference for the structural design of the hydrogen–natural gas mixing pipeline and the gas distribution state during the mixing process.

Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. However, during the transportation process, a non-uniform distribution of hydrogen concentration occurs in the pipeline due to gravity. Therefore, it is necessary to study the hydrogen concentration distribution law of hydrogen-blended natural gas in pipelines. The undulation and ball valve pipelines, which are common in transport pipelines, were constructed in this study. The effects of the undulation angle, height, pipeline diameter, ball valve opening, and temperature on the distribution of the hydrogen concentration were investigated using computational fluid dynamic (CFD) methods. The results indicated that the hydrogen concentration gradient changed gently with the larger diameter of the undulating pipeline, minimizing hydrogen accumulation. Higher undulation angle and smaller height differences reduces the hydrogen accumulation risk. Increasing vertical height difference of the pipeline from 5 m to 15 m increased the hydrogen volume fraction gradient by1.3 times. In the ball valve pipeline, the velocity fluctuation decreased as the ball valve opening increased. However, the hydrogen accumulation phenomenon was obvious. The opening increased from 25% to 100% and the hydrogen volume fraction gradient increased more than two times. Selecting delivery conditions with low hydrogen blending ratios, high temperatures, low pressures, and high flow rates reduces the occurrence of hydrogen buildup in the pipeline.

Coal dust is one of the seven disasters in coal mine. It affects the health of workers and causes coal dust explosion. The wetting effect of coal has a great influence on dust removal. Studies have shown that the wetting effect of coal is related to the wettability, surface roughness and surfactants of coal. In order to effectively solve the problem of coal dust under the mines, which selects hydrophilic Hami lignite, hydrophobic Anyang coking coal and weakly hydrophilic anthracite of Zhaogu No.2 mine as the research objects. The mean square roughness of the three coal samples were measured by the optical contact angle morphology combined instrument, the intrinsic contact angles of the three coal samples were measured, the two-dimensional physical model was constructed by COMSOL numerical software, the simulation conditions were set, the simulation parameters were adjusted, the experimental and simulation values were analyzed and compared, the feasibility of COMSOL numerical simulation was verified, and the influence of coal surface roughness on coal surface contact angle was studied. The results show that the droplet spreading process, the droplet spreading velocity and the droplet spreading shape of numerical simulation are similar to those of experiment, but the simulated contact angle is larger than that of experiment. With the increase of coal surface roughness, the contact angle of lignite decreases from 60.7° to 50.9°, the variation range is about 10°, the contact angle of coking coal increases from 96.5° to 112.7°, the variation range is about 16°, and the contact angle of anthracite decreases from 89.7° to 78.3°, and the variation range is about 11°. The simulated and experimental values of contact angle of three kinds of coal samples with the same surfactant have the same change trend, but the simulated value is larger than the experimental value. It is feasible to study the influence of coal surface roughness on coal surface contact angle by numerical simulation. The wetting of coal surface affected by roughness conforms to Wenzel model. The existence of surfactant does not change the variation of contact angle with surface roughness of three coal samples.

Surface defect detection of strip steel is an important guarantee for improving the production quality of strip steel. However, due to the diverse types, scales, and texture structures of surface defects on strip steel, as well as the irregular distribution of defects, it is difficult to achieve rapid and accurate detection of strip steel surface defects with existing methods. This article proposes a real-time and high-precision surface defect detection algorithm for strip steel based on YOLOv7. Firstly, Partial Conv is used to replace the conventional convolution blocks of the backbone network to reduce the size of the network model and improve the speed of detection; Secondly, The CA attention mechanism module is added to the ELAN module to enhance the ability of the network to extract detect features and improve the effectiveness of detect detection in complex environments; Finally, The SPD convolution module is introduced at the output end to improve the detection performance of small targets with surface defects on steel. The experimental results on the NEU-DET dataset indicate that the mean average accuracy (mAP@IoU = 0.5) is 80.4%, which is 4.0% higher than the baseline network. The number of parameters is reduced by 8.9%, and the computational load is reduced by 21.9% (GFLOPs). The detection speed reaches 90.9 FPS, which can well meet the requirements of real-time detection.

Hydrogen mixing in existing natural gas pipelines efficiently achieves large-scale, long-distance, and low-cost hydrogen delivery. The physical properties of hydrogen and natural gas differ significantly. Hydrogen-mixed natural gas modifies the flow state and thermodynamic properties of the original natural gas in the pipeline. Hydrogen-mixed natural gas can lead to increased errors in ultrasonic flow metering because of the high sound speed and low density of hydrogen. Ultrasonic flowmeter installation distances need to be re-determined. In this study, a Lamb wave non-contact ultrasonic gas flow meter is used to measure the flow of hydrogen-mixed natural gas in a T-type pipeline. The greater the hydrogen mixing ratio, the higher the flow rate of the branch pipeline, and the shorter the installation distance of the ultrasonic flow meter, for example, 10% at 150D, 20% at 110D, and 30% at 20D. The time-difference method with high accuracy and broad applicability is used to calculate the flow rates of COMSOL simulated values. The errors between COMSOL simulation and theoretical flow rates at the shortest installation distance downstream do not exceed 3%. The errors at the position where the mixing uniformity is 80% are significantly higher than those at the shortest installation distance, and the maximum error is about 7.7%. The COMSOL simulation results show the feasibility and accuracy of ultrasonic gas flow metering of hydrogen-mixed natural gas.

Hydrogen-blended natural gas transportation can effectively solve the problem of wind and photovoltaic energy curtailment and reduction of greenhouse gas emission, and realize the low-cost transportation of hydrogen in large scale, so it becomes an important way to achieve the "double carbon" goal. However, the risk of hydrogen embrittlement will be brought by blending hydrogen to the existing natural gas pipeline system and relevant transportation facilities. Therefore, the mechanism of hydrogen embrittlement was analyzed based on the structural composition of hydrogen-blended natural gas transportation system. Meanwhile, investigation was performed for the hydrogen embrittlement of the pipelines, welds, valves, compression devices, storage units and terminals of the hydrogen-blended natural gas transportation system. On this basis, countermeasures for prevention of hydrogen embrittlement were put forward. Then, the prospect and development of hydrogen-blended natural gas transportation system were forecast. Generally, the research results could provide reference for the large-scale and market-oriented development of hydrogen-blended natural gas transportation in China, and the improvement of research and development of pipeline hydrogen transportation technology and equipment, further accelerating the safe development of hydrogen economy.

The research on biomimetic robots, especially soft robots with flexible materials as the main structure, is constantly being explored. It integrates multi-disciplinary content, such as bionics, material science, mechatronics engineering, and control theory, and belongs to the cross-disciplinary field related to mechanical bionics and biological manufacturing. With the continuous development of various related disciplines, this area has become a hot research field. Particularly with the development of practical technologies such as 3D printing technology, shape memory alloy, piezoelectric materials, and hydrogels at the present stage, the functions and forms of soft robots are constantly being further developed, and a variety of new soft robots keep emerging. Soft robots, combined with their own materials or structural characteristics of large deformation, have almost unlimited degrees of freedom (DoF) compared with rigid robots, which also provide a more reliable structural basis for soft robots to adapt to the natural environment. Therefore, soft robots will have extremely strong adaptability in some special conditions. As a type of robot made of flexible materials, the changeable pose structure of soft robots is especially suitable for the large application environment of the ocean. Soft robots working underwater can better mimic the movement characteristics of marine life in the hope of achieving more complex underwater tasks. The main focus of this paper is to classify different types of underwater organisms according to their common motion modes, focusing on the achievements of some bionic mechanisms in different functional fields that have imitated various motion modes underwater in recent years (e.g., the underwater sucking glove, the underwater Gripper, and the self-powered soft robot). The development of various task types (e.g., grasping, adhesive, driving or swimming, and sensing functions) and mechanism realization forms of the underwater soft robot are described based on this article.

In clinic, the acquisition of airflow with nasal prongs, masks, thermistor to monitor respiratory function is more uncomfortable and inconvenience than surface diaphragm electromyography (EMGdi) using electrode pads. The EMGdi with strong electrocardiograph (ECG) interference affect the extraction of its characteristic information. In this work, surface EMGdi and airflow signals of 20 subjects were collected under 5 incremental inspiratory threshold loading protocols from quiet breathing to maximum forced breathing. First, we filtered out the ECG interference in EMGdi based on the combination of stationary wavelet transform and the positioning of ECG to obtain pure EMGdi (EMGdip). Second, the Spearman’s rank correlation coefficients between EMGdi and EMGdip quantified by time series fixed sample entropy (fSampEn), root mean square (RMS), and envelope were compared to verify the robustness of the fSampEn to ECG. A comparative analysis of correlation between fSampEn of EMGdi and inspiratory airflow and the correlation between envelope of EMGdip (EMGdie) and inspiratory airflow found that there was no significant difference between the two, indicating the feasibility of using fSampEn to predict airflow. Moreover, fSampEn of EMGdi was used as characteristic parameter to build a quantitative relationship with the airflow by polynomial regression analysis. Mean coefficient of determination of all subjects in any breathing state is greater than 0.88. Finally, nonlinear programming method was used to solve a universal fitting coefficient between fSampEn of EMGdi and airflow for each subject to further evaluate the possibility of using surface EMGdi to monitor and control respiratory activity.

Objective: Diaphragm pacing (DP) is a long-term and effective respiratory assist therapy for patients with central alveolar hypoventilation and high cervical spinal cord injury. The existing DP system has some limitations, especially high price, inconvenience preoperative evaluation methods and diaphragm fatigue easily. Our objective was to develop a DP system and evaluated reliability through hardware testing and animal experiments.Methods: A DP system with bidirectional constant current was designed, manufactured and tested. Effects of a wide range of stimulus amplitudes (range: .5–2.5 mA) and frequencies (range: 10–250 Hz) on airflow and corresponding inspired volume were investigated during DP. Differences in airflow characteristics under various stimulation parameters were evaluated using power function. ECG interference in diaphragm electromyography (EMGdi) was filtered out using stationary wavelet transform to obtain pure EMGdi (EMGdip). 80-min period with a tendency for diaphragm fatigue by root mean square (RMS) and centroid frequency (fc) of EMGdip was studied.Results: The increase of stimulus frequency and amplitude in animals resulted in different degrees of increase in envoked volume. Significant difference in Airflow Index (b) between anesthesia and DP provided a simple, non-invasive and feasible solution for phrenic nerve conduction function test. Increased stimulation duration with the developed DP system caused less diaphragm fatigue.Conclusion: A modular, inexpensive and reliable DP was successfully developed. Its effectiveness was confirmed in animal experiments.Significance: This study is useful for design of future implantable diaphragmatic pacemakers for improving diaphragm fatigue and convenient assessment of respiratory activity in experiments.

Surface roughness has an important effect on the wettability and surface energy of coal. Although the predecessors had studied the effect of surface roughness on the wettability of coal, there were few researches on the effect of surface energy of coal, and the relationship between wettability and surface energy had not been thoroughly studied. This paper aimed to study the effect of surface roughness on the wettability and surface energy of coal, and revealed the relationship between the wettability and surface energy of coal. Based on the surface roughness of coal, this paper selected Hami lignite, Anyang coking coal and Zhaogu anthracite as the research objects, used the experimental methods to measure the surface roughness and experimental contact angle of coal under different conditions to study the effect of surface roughness on the wettability, and then applied the OWRK method to calculate the surface energy of coal to study the effect of surface roughness on the surface energy. The experimental results showed that the wettability of hydrophilic coal became better and the surface energy increased with the increase of surface roughness, while the results of hydrophobic coal were opposite. There was a positive correlation between the wettability and surface energy of coal, and the wettability of coal could be analyzed from the perspective of surface energy. Surfactant could change the wettability of coal, but unchanged the law of wettability with surface roughness.

Abstract Vapor‐compression refrigeration systems are widely used in refrigeration equipment. Theoretically, the process is typically divided into two isobaric processes: an adiabatic isentropic compression process and adiabatic isentropic throttling process. The refrigeration compressor is the main energy‐consuming component in vapor‐compression refrigeration systems. However, this device has a large energy loss and low overall efficiency in the adiabatic isentropic compression process. In this study, a modified vapor‐compression refrigeration cycle with an isothermal piston is proposed to realize near‐isothermal compression of a refrigerator to significantly reduce the energy loss in the compression process and improve the system performance. A real‐gas compression process model is established, and the heat transfer index Hex is set. By changing the heat transfer index Hex, the performances of the vapor‐compression refrigeration system under ideal and real compression conditions are compared and analyzed. Compared with a traditional vapor‐compression refrigeration system, the coefficient of performance of the compressor with an isothermal compression process is increased by approximately 17%. The results also demonstrate that the lower the evaporation temperature Te and higher the condensation temperature Tc, the greater the optimization effect of the isothermal compression.

A novel sputum deposition classification method for mechanically ventilated patients based on the long-short-term memory network (LSTM) method was proposed in this study. A wireless ventilation airflow signals collection system was designed and used in this study. The ventilation airflow signals were collected wirelessly and used for sputum deposition classification. Two hundred sixty data groups from 15 patients in the intensive care unit were compiled and analyzed. A two-layer LSTM framework and 11 features extracted from the airflow signals were used for the model training. The cross-validations were adopted to test the classification performance. The sensitivity, specificity, precision, accuracy, F1 score, and G score were calculated. The proposed method has an accuracy of 84.7 ± 4.1% for sputum and non-sputum deposition classification. Moreover, compared with other classifiers (logistic regression, random forest, naive Bayes, support vector machine, and K-nearest neighbor), the proposed LSTM method is superior. In addition, the other advantages of using ventilation airflow signals for classification are its convenience and low complexity. Intelligent devices such as phones, laptops, or ventilators can be used for data processing and reminding medical staff to perform sputum suction. The proposed method could significantly reduce the workload of medical staff and increase the automation and efficiency of medical care, especially during the COVID-19 pandemic.

Abstract Nowadays, mild hypothermia is widely used in the fields of post-cardiac arrest resuscitation, stroke, cerebral hemorrhage, large-scale cerebral infarction, and craniocerebral injury. In this paper, a locally mixed sub-low temperature device is designed, and the cold and hot water mixing experiment is used to simulate the human blood transfer process. To set a foundation for the optimization of the heat transfer system, the static characteristics are analyzed by building the mathematic model and setting up the experimental station. In addition, the affection of several key structure parameters is researched. Through experimental and simulation studies, it can be concluded that, firstly, the mathematical model proved to be effective. Secondly, the results of simulation experiments show that 14.52 °C refrigeration can reduce the original temperature of 33.42 °C to 32.02 °C, and the temperature of refrigerated blood rises to 18.64 °C, and the average error is about 0.3 °C. Thirdly, as the thermal conductivity of the vascular sheath increases, the efficiency of the heat exchange system also increases significantly. Finally, as the input cold blood flow rate increases, the mass increases and the temperature of the mixed blood temperature decreases. It provides a research basis for subsequent research on local fixed-point sub-low temperature control technology.

Abstract When saving energy in a pneumatic system, the problem of energy losses is usually solved by reducing the air supply pressure. The power-matching method is applied to optimize the air-supply pressure of the pneumatic system, and the energy-saving effect is verified by experiments. First, the experimental platform of a pneumatic rotary actuator servo-control system is built, and the mechanism of the valve-controlled cylinder system is analyzed. Then, the output power characteristics and load characteristics of the system are derived, and their characteristic curves are drawn. The employed air compressor is considered as a constant-pressure source of a quantitative pump, and the power characteristic of the system is matched. The power source characteristic curve should envelope the output characteristic curve and load characteristic curve. The minimum gas supply pressure obtained by power matching represents the optimal gas supply pressure. The comparative experiments under two different gas supply pressure conditions show that the system under the optimal gas supply pressure can greatly reduce energy losses.

Respiratory sounds reveal important information of the lungs of patients. However, the analysis of lung sounds depends significantly on the medical skills and diagnostic experience of the physicians and is a time-consuming process. The development of an automatic respiratory sound classification system based on machine learning would, therefore, be beneficial. In this study, 705 respiratory sound signals (240 crackles, 260 rhonchi, and 205 normal respiratory sounds) were acquired from 130 patients. We found that similarities between the original and wavelet decomposed signals reflected the frequency of the signals. The Gaussian kernel function was used to evaluate the wavelet signal similarity. We combined the wavelet signal similarity with the relative wavelet energy and wavelet entropy as the feature vector. A 5-fold cross-validation was applied to assess the performance of the system. The artificial neural network model, which was applied, achieved the classification accuracy and classified the respiratory sound signals with an accuracy of 85.43%.

In recent years, precise high flow oxygen therapy as a new type of oxygen therapy machine has gradually attracted people’s attention and has been widely used in hospital emergency and clinical treatment of respiratory diseases; especially in recent years, severe coronavirus disease (COVID-19) has played an important role in the treatment of patients. This paper presents a new type of precise high flow oxygen therapy machine with electromagnetic pneumatic flow valve as the core control element. A sliding mode control strategy based on the system is proposed to realize the accurate control of oxygen concentration and output flow of oxygen therapy mixture. The physical equipment of the precision high flow system is established, and its working performance is verified through the test platform. The optimization design goal of the precision high flow equipment is achieved.

Abstract Pneumatic system has been widely used throughout industry, and it consumes more than billions kW h of electricity one year all over the world. So as to improve the efficiency of pneumatic system, its power evaluation as well as measurement methods should be proposed, and their applicability should be validated. In this paper, firstly, power evaluation and measurement methods of pneumatic system were introduced for the first time. Secondly, based on the proposed methods, power distributions in pneumatic system was analyzed. Thirdly, through the analysis on pneumatic efficiencies of typical compressors and pneumatic components, the applicability of the proposed methods were validated. It can be concluded that, first of all, the proposed methods to evaluation and measurement the power of pneumatic system were efficient. Furthermore, the pneumatic power efficiencies of pneumatic system in the air production and cleaning procedure are respectively about 35%–75% and 85%–90%. Moreover, the pneumatic power efficiencies of pneumatic system in the transmission and consumption procedures are about 70%–85% and 10%–35%. And the total pneumatic power efficiency of pneumatic system is about 2%–20%, which varies largely with the system configuration. This paper provides a method to analyze and measure the power of pneumatic system, lay a foundation for the optimization and energy-saving design of pneumatic system.

Recently, the cruising duration is a vital parameter of fuel-powered unmanned aerial vehicles (UAVs), and it is directly determined by the power characteristics of the aircraft engine in the UAV. In this study, to prolong the flight duration and enhance the power and efficiency of a UAV, an aircraft engine is analyzed based on the fuel injection control system and output power characteristics. First, the mathematical model of a fuel-controlled engine is constructed. In addition, the experimental stations of the aircraft engine are set up to verify the mathematical model. Furthermore, the effects of key parameters on the engine power characteristics are examined. By the experimental and simulation studies validity of the mathematical model is effectively verified which indicates that the increased rotating speed decreases the power efficiency of the aircraft engine, and reducing the fuel injection pulse width from 5 ms to 3.5 ms increases the power efficiency by 10%. Moreover, increasing the advance angle of ignition from 10° to 40° improves the power efficiency by 5%. In addition, when the fuel injection delay width increases from 0.5 mm to 1.5 mm at an engine speed between 3500 rpm and 4000 rpm, the power efficiency is improved by 6%. Finally, when the engine speed is higher than 4000 rpm, increasing the propeller rotor diameter from 650 mm to 800 mm enhances the power efficiency of the aircraft engine by approximately 5%. This research can be considered as the fuel injection system optimization and cruising duration improvement of a fuel-powered UAV.

Mechanical ventilation is an important and effective method for the treatment of pulmonary diseases patients with spontaneous breathing. Spontaneous breathing refers to the physiological breathing activity caused by the respiratory muscle. These patients retain some ability to breathe spontaneously, but do not reach the level of normal breathing. Mathematical simulation and modeling of the mechanical ventilation system are crucial for research on mechanical ventilation. In this paper, a novel pneumatic model of a mechanical ventilation system considering patients’ spontaneous breathing is presented. Mathematical equations are accurately derived to explain the principles of the respiratory system and mechanical ventilation system. An experimental prototype is designed to confirm the correctness and validity of the pneumatic model. The goodness of fit shows that the mathematical simulation curve fits well with the experimental curve, thus confirming the accuracy of the pneumatic model. For patients with a certain degree of spontaneous breathing, the mechanical ventilation mode is set to the pressure support ventilation (PSV) mode, and variations in the flow, pressure and tidal volume curves are observed by changing specific respiratory mechanics parameters such as the compliance ( $C$ ), the effective area of the throttle in the pneumatic model ( $A$ ), and the muscle pressure difference ( $\Delta P_{\mathrm {mus}}$ ). From the results, it can be concluded that the resistance of the mechanical ventilation system can be equivalent to $A$ . The dynamic characteristics (mainly flow characteristics, tidal volume characteristics and pressure characteristics) of the mechanical ventilation system are directly influenced by variations in $C$ , $A $ and $\Delta P_{\mathrm {mus}}$ . This study is an important reference for setting ventilation levels and ventilator control parameters. The results of this research are valuable for the diagnosis and treatment of respiratory diseases.

Energy saving is one of the main technique routes for net zero carbon emissions. Air compressor systems take up a large part of energy consumption in the industrial field. A pre-cooling air compressor system was proposed for energy saving by cooling the air before it flows in a compressor. The energy efficiency of the proposed system was analyzed. As additional energy consumption is required for air cooling, the feasibility of the pre-cooling method for energy saving was analyzed. As the efficiency of the pre-cooling air compressor system is mainly influenced by the environment temperature and humidity, applicability of the system in different regions and at different seasons was discussed. A pilot project was performed to verify the technical feasibility and economics of the proposed system. When the precooling temperature of the pilot system was set to 2 °C, the annual pneumatic-electrical ratio of the system can be increased by approximately 2% in several regions of China. This paper shows the pre-cooling air compressor system is feasible for energy saving.

Spinal cord injury (SCI) is an existing incurable disease that brings great pain and life obstacles to patients. Spinal cord electrical stimulation is an effective means to alleviate spinal cord injury. However, its complicated mechanism of action is still unclear. This article aims to summarize several different spinal cord electrical stimulation methods, analyze the stimulation effect, and briefly describe the current understanding of its origin and mechanism of action. In recent years, several application cases of the electrical stimulation system of stimulation methods have confirmed its positive effects in spinal cord injury diseases and provided new perspectives for the improvement of spinal cord injury. Finally, the possible development direction and corresponding challenges of spinal cord electrical stimulation in the future are proposed.

With the significant increase in demand for artificial intelligence, environmental map reconstruction has become a research hotspot for obstacle avoidance navigation, unmanned operations, and virtual reality. The quality of the map plays a vital role in positioning, path planning, and obstacle avoidance. This review starts with the development of SLAM (Simultaneous Localization and Mapping) and proceeds to a review of V-SLAM (Visual-SLAM) from its proposal to the present, with a summary of its historical milestones. In this context, the five parts of the classic V-SLAM framework—visual sensor, visual odometer, backend optimization, loop detection, and mapping—are explained separately. Meanwhile, the details of the latest methods are shown; VI-SLAM (Visual inertial SLAM) is reviewed and extended. The four critical techniques of V-SLAM and its technical difficulties are summarized as feature detection and matching, selection of keyframes, uncertainty technology, and expression of maps. Finally, the development direction and needs of the V-SLAM field are proposed.

The demand for mass custom parts is increasing, estimating the cost of parts to a high degree of efficiency is a matter of great concern to most manufacturing companies. Under the premise of machining operations, cost estimation based on features and processes yields high estimation accuracy, but it necessitates accurately identifying a part’s machining features and establishing the relationship between the feature and the cost. Accordingly, a feature recognition method based on syntactic pattern recognition is proposed herein. The proposed method provides a more precise feature definition and easily describes complex features using constraints. To establish the relationships between geometric features, processing modes, and cost, this study proposes a method of describing the features and the processing mode using feature quantities and adopts deep learning technology to establish the relationship between feature quantities and cost. By comparing a back propagation (BP) network and a convolutional neural network (CNN) it can be concluded that a CNN using the “RMSProp” optimizer exhibits higher accuracy.

Cough is a respiratory protective behavior for clearing the secretion. The cough process can be characterized by three features which are cough peak flow rate, peak velocity time, and cough expired volume. The cough expired volume (CEV) and the cough peak flow rate (CPFR) are important for medical diagnosis and cough effectiveness assessment. In this study, the CEV and CPFR values of 700 healthy participants were measured and collected by using a portable pulmonary function device. The gender, age, height, weight, and smoking status information of the 700 participants were also collected. Meanwhile, the integration of backpropagation neural network and genetic algorithm (GA-BP) method was developed to estimate CEV and CPFR values. The results showed that the estimation accuracy of GA-BP method exceeds 90%, which indicates that the GA-BP method could be effectively used for CEV and CPFR value estimation. Furthermore, the method proposed in this paper could be useful for medical diagnosis and medical device development.

Power efficiency of two-stroke spark-ignition engine is generally low because improper amount of fuel injection leads to a lot of unburned fuel loss during the engine working process. However, parameters of the fuel injection system are hard to confirm by aviation experiments due to expensive test costs. This paper proposes a method of calibrating injection parameters of two-stroke spark-ignition engine based on thermodynamic simulation and parameter optimum algorithm. Firstly, the one-dimensional thermodynamic model is built according to the internal structure and thermodynamic process of the engine; then, the model parameters are corrected according to the operating principle of the injector; after experimental verification of the model, considering both the engine power sufficiency and fuel economy, Analytic Hierarchy Process method is applied to look for the optimal injection amount and fuel injection advance angle at different engine working speeds; finally, an aeroengine experiment station with an electronic fuel injector system is built. Through simulation and experiment studies, it can be seen that when the engine speed changes from 3000 to 3500 RPM, the oil consumption rate of the optimal results is higher than that of the previous ones; when the aeroengine speed is higher than 4000 RPM, the oil consumption rate results of the optimal method are 10% to 27% higher than the original results. This paper can be a reference in the optimization of UAV aircraft engine.

The synchrony of patient-ventilator interaction affects the process of mechanical ventilation which is clinically applied for respiratory support. The occurrence of patient-ventilator asynchrony (PVA) not only increases the risk of ventilator complications but also affects the comfort of patients. To solve the problem of uncertain patient-ventilator interaction in the mechanical ventilation system, a novel method to evaluate patient-ventilator synchrony is proposed in this article. Firstly, a pneumatic model is established to simulate the mechanical ventilation system, which is verified to be accurate by the experiments. Then, the PVA phenomena are classified and detected based on the analysis of the ventilator waveforms. On this basis, a novel synchrony index SIhao is established to evaluate the patient-ventilator synchrony. It not only solves the defects of previous evaluation indexes but also can be used as the response parameter in the future research of ventilator control algorithms. The accurate evaluation of patient-ventilator synchrony can be applied to the adjustment of clinical strategies and the pathological analyses of patients. This research can also reduce the burden on clinicians and help to realize the adaptive control of the mechanical ventilation and weaning process in the future.

The nonlinear characteristics of the pneumatic servo system are the main factors limiting its control accuracy. A new mathematical model of the nonlinear system of the valve control cylinder is proposed in order to improve the control accuracy of the pneumatic servo system. Firstly, the mass flow equation of the gas flowing through each port is established by analyzing the physical structure of the proportional directional control valve. Then, the dynamic equation of the system is set up by applying the Stribeck friction model for the friction model of the valve control cylinder and building a pneumatic circuit experiment to identify the friction model parameters. Finally, the correctness of the mathematical model is verified by the inflation and deflation experiment of the fixed capacitive chamber and the servo controls experiment based on PID position. The Simulink simulation of the mathematical model better reflects the characteristics of the pneumatic position servo system.

Water-spray-cooled quasi-isothermal compressed air energy storage aims to avoid heat energy losses from advanced adiabatic compressed-air energy storage (AA-CAES). The compression efficiency increases with injection water spray. However, the energy-generated water spray cannot be ignored. As the air pressure increases, the work done by the piston and the work converted into heat rise gradually in the compression process. Accordingly, the flow rate of the water needed for heat transfer is not a constant with respect to time. To match the rising compression heat, a time sequence of water-spray flow rate is constructed, and the algorithm is designed. Real-time water-spray flow rate is calculated according to the difference between the compression power and heat-transfer power. Compared with the uniform flow rate of water spray, energy consumption from the improved flow rate is reduced.

Reducing carbon emissions is an urgent problem around the world while facing the energy and environmental crises. Whatever progress has been made in renewable energy research, efforts made to energy-saving technology is always necessary. The energy consumption from fluid power systems of industrial processes is considerable, especially for pneumatic systems. A novel isothermal compression method was proposed to lower the energy consumption of compressors. A porous medium was introduced to compose an isothermal piston. The porous medium was located beneath a conventional piston, and gradually immerged into the liquid during compression. The compression heat was absorbed by the porous medium, and finally conducted with the liquid at the chamber bottom. The heat transfer can be significantly enhanced due to the large surface area of the porous medium. As the liquid has a large heat capacity, the liquid temperature can maintain constant through circulation outside. This create near-isothermal compression, which minimizes energy loss in the form of heat, which cannot be recovered. There will be mass loss of the air due to dissolution and leakage. Therefore, the dissolution and leakage amount of gas are compensated for in this method. Gas is dissolved into liquid with the pressure increasing, which leads to mass loss of the gas. With a pressure ratio of 4:1 and a rotational speed of 100 rpm, the isothermal piston decreased the energy consumption by 45% over the conventional reciprocation piston. This gain was accomplished by increasing the heat transfer during the gas compression by increasing the surface area to volume ratio in the compression chamber. Frictional forces between the porous medium and liquid was presented. Work to overcome the frictional forces is negligible (0.21% of the total compression work) under the current operating condition.

Magnetic flux leakage (MFL) detection is one of the most popular methods of pipeline inspection. It is a nondestructive testing technique which uses magnetic sensitive sensors to detect the magnetic leakage field of defects on both the internal and external surfaces of pipelines. This paper introduces the main principles, measurement and processing of MFL data. As the key point of a quantitative analysis of MFL detection, the identification of the leakage magnetic signal is also discussed. In addition, the advantages and disadvantages of different identification methods are analyzed. Then the paper briefly introduces the expert systems used. At the end of this paper, future developments in pipeline MFL detection are predicted.

Air is usually compressed adiabatically in the compressor. As the operating speed of compressors can be several thousand rpm, heat generated during compression cannot be sufficiently transmitted to the environment in such a short time. It is for this reason that compressor efficiency is limited. Isothermal compression could be an alternative choice applied on industrial compressor and compressed air energy storage (CAES). This paper proposed a new kind of piston to perform isothermal compression. Surface area of such isothermal piston structure is larger. A certain amount of fluid at the chamber bottom absorbs the heat from the isothermal piston. Heat transfer between piston and fluid during compression is investigated. Air pressure is measured to validate the effectiveness of this proposed piston structure in heat transfer. Compression work of the proposed isothermal piston and conventional one is compared. One issue of this comparison is that air-liquid dissolution can affect the pressure and compression work. The influence of dissolution is quantified with Henry’s Law. Quantitative analysis is performed to determine that heat transfer is the dominant factor affecting the pressure and compression work. Some simple experiments are described in this paper, which shed light on that heat transfer could be significantly improved adopting this proposed isothermal piston.

In order to accurately reflect the characteristics and motion states of a pneumatic rotary actuator position servo system, an accurate non-linear model of the valve-controlled actuator system is proposed, and its parameter identification and experimental verification are carried out. Firstly, in the modeling of this system, the mass flow rate of the gas flowing through each port of the proportional directional control valve is derived by taking into account the clearance between the valve spool and the sleeve, the heat transfer formula is used to the derivation of the energy equation, and the Stribeck model is applied to the friction model of the pneumatic rotary actuator. Then, the flow coefficient, the heat transfer coefficient and the friction parameters are identified by the model and pneumatic test circuits. After the verification experiment of the mass flow rate equations, the charging and discharging experiment reveals that the model can clearly show the effect of clearances on gas pressure changes and describe the effect of heat transfer on gas temperature changes. Finally, the results of model verification indicate that the simulation curves of rotation angle and two-chamber pressures are consistent with their experimental values, and the non-linear model shows high accuracy.

Air-liquid pressurization convertor has been applied in energy boosting which is widely used in sustainable energy automobile. In this article, output dynamic control method is analyzed by model simulation and experimental validation to set foundation for optimization, in which the pneumatic and hydraulic nonlinear combination equations, total nonlinear frictions on pistons, and load nonlinear equilibrium equation are considered. Moreover, influences on output dynamic control characteristics of the late automobile model with nonlinearity are studied. The conclusion can be made as follows: first, the built model is effectively verified by comparison of experimental and simulation results. Second, as one of the key power system parameters, longer piston stroke will lead to better output dynamic property within a certain limit. Third, area ratio is considered to be approximately 8, which can avoid the unsteadiness of the output dynamic characteristics. Furthermore, suitably bigger orifice will greatly promote the characteristic property of the air-liquid pressurization convertor. Finally, under the condition of this article, input pressure can be set to 0.65 MPa to obtain a better power system combination property. This study can provide reference for the optimization of dynamic characteristics of the sustainable energy automobile.

To improve the condition of air and eliminate exhaust gas pollution, this article proposes a compressed air power system. Instead of an internal combustion engine, the automobile is equipped with a compressed air engine, which transforms the energy of compressed air into mechanical motion energy. A prototype was built, and the compressed air engine was tested on an experimental platform. The output torque and energy efficiency were obtained from experimental results. When the supply pressure was set at 2 MPa and the speed was 420 r min −1 , the output torque, the output power, and the energy efficiency were 56 N m, 1.93 kW, and 25%, respectively. To improve the efficiency of the system, a fuzzy logic speed control strategy is proposed and simulated. The experimental study verified that the theoretical evaluation of the system was reasonable, and this research can be referred to as the design and control of air-powered vehicles.

Because of its cleanness, safety, explosion proof, and other characteristics, pneumatic technologies have been applied in numerous industrial automation fields. As a key controlling element of a pneumatic system, electric-pneumatic pressure proportional valves have attracted the attention of many scholars in recent years. In this paper, in order to illustrate the research status and the development trend of electric-pneumatic pressure proportional valves, firstly, several related technologies will be introduced, for example, simulation methods and experimental modes. In addition, controlling methods, structural styles, and feedback forms are also compared in several types of pressure proportional valves. Moreover, the controlling strategy, as a significant relevant factor affecting the efficiency of valves, will be discussed in this paper. At the end, the conclusion and worksof electric-pneumatic pressure proportional valves in the future will bediscussed to achieve the electrical integration.

A new camless compressed air engine is proposed, which can make the compressed air energy reasonably distributed. Through analysis of the camless compressed air engine, a mathematical model of the working processes was set up. Using the software MATLAB/Simulink for simulation, the pressure, temperature, and air mass of the cylinder were obtained. In order to verify the accuracy of the mathematical model, the experiments were conducted. Moreover, performance analysis was introduced to design compressed air engine. Results show that, firstly, the simulation results have good consistency with the experimental results. Secondly, under different intake pressures, the highest output power is obtained when the crank speed reaches 500 rpm, which also provides the maximum output torque. Finally, higher energy utilization efficiency can be obtained at the lower speed, intake pressure, and valve duration angle. This research can refer to the design of the camless valve of compressed air engine.