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There are several imaging modes in AFM, and the tapping mode is the most commonly used scanning mode. Tapping mode can acquire the height information and phase information of the sample surface, among which the phase information has more value, which can reflect the physical properties of the sample surface. In order to understand the phase imaging mechanism of AFM, this paper uses the vibration theory to derive the theoretical expression of phase, and finds that the excitation frequency will directly affect the phase contrast. Based on this, this paper finds, through theoretical and experimental analysis, that there exists an optimal excitation frequency that maximizes the phase contrast during the scanning process. These results are important for interpreting the phase image of AFM and thus optimizing the phase imaging in experiments.

Bearings play a crucial role in the functionality of rotating machinery, and any defects in these components can result in machine failure. Detecting, diagnosing, and prognosing bearing faults are crucial steps in machine failure diagnostics to prevent malfunctions and breakdowns. While various methods exist for fault detection, including acoustic emission analysis, visual inspection, thermography, ultrasonic, motor current analysis, wear-debris analysis, oil analysis, and vibration analysis, the latter stands out as a popular non-destructive method. This paper focuses on time and frequency domain vibration analysis techniques for detecting faults in floating bush bearings. Particularly beneficial for online monitoring, remote and non-human intervention areas, and hazardous locations, the time-frequency domain approach enhances diagnostic capabilities. The vibration data collected during these experiments has been rigorously analyzed using data acquisition system and applied a comprehensive approach that includes evaluating the data in both the time and frequency domains, as well as utilizing advanced signal processing techniques, notably the high-frequency resonance technique. Test results underscore the effectiveness of specific parameters in identifying defects: waveform, form factor, parameter K, and cepstrum excel in pinpointing external defects, while kurtosis, crest factor, and skewness prove adept at identifying internal faults. In the frequency domain, the enveloped spectrum emerges as a robust method for comprehensive defect detection. The vibration data presented in this paper will prove to be an invaluable resource for professionals engaged in the field of vibration measurement and analysis.

In the paper, a feedback hybrid control including a force feedback control and a position control is proposed to control a four degree of freedom (4-dof) upper limb exoskeleton for supporting human movement at the shoulder, elbow and wrist joints. The novelty of the paper is that it has been able to control all the interaction forces at all links in the exoskeleton robot by using the proposed control. The desired interaction forces at the links and desired position are compared with the measured interaction forces and position, respectively. Then the torque at the shoulder, the torque elbow and the torque wrist joints are controlled to compensate the force error and the position error. The gains of the proposed controller are optimized by using the Balancing Composite Motion Optimization (BCMO). The simulation and control of the 4-dof upper limb exoskeleton using the proposed control is carried out in the paper to show that the interaction forces and the position of the exoskeleton track their desired values.

Explosion shock wave pressure is one of the main damage parameters produced in the process of ammunition explosion, and it is also an important technical index to evaluate the damage power of ammunition. However, in the actual testing process, only a limited amount of shockwave pressure data at specific measuring points can be obtained, which cannot accurately reflect the distribution laws of the shockwave pressure propagation after the ammunition explosion. Therefore, it is particularly important to conduct reconstruction of the shockwave pressure field distribution laws based on limited measuring point data. This paper reviews the research work and related achievements obtained by researchers at home and abroad on the reconstruction of shockwave pressure distribution laws in explosion fields. The paper also elucidates the relevant application of computer tomography imaging techniques, shockwave propagation attenuation model reconstruction, and various interpolation algorithms in the reconstruction process of the shockwave pressure field. Given the current research situation both domestically and internationally, we have pinpointed the major issues that still exist in the current stage of research and proposed the key areas of focus that need attention in future research.

In view of the problem that the electro-erosion fault signal is rare and weak during motor operation, and the database is seriously imbalanced, this paper proposes an ASMOTE-CFR training model based on adaptive minority oversampling technology. Four bearing vibration acceleration signals in different states were collected through experiments, and each signal obtained 32 sets of energy features using wavelet packet decomposition. Then ASMOTE technology is used to balance the energy features of electro-erosion fault signal. And construct a vector matrix combined by energy features and bearing fault state features. Finally, the collaborative filter model of matrix decomposition is used to train and identify. The results show that the recognition rate of the ASMOTE-CFR model proposed in this paper is 98.46 %, which improves by 7 % compared with the traditional CFR, which verifies the effectiveness of this method.

The dual-rotor system is the core component of advanced aero-engine. Establishing a reasonable, accurate, and efficient dynamics model is the key to studying the dynamics and vibration of the rotor system for aero-engine. This manuscript takes a representative aircraft engine dual-rotor system as a prototype, considers the rig-id-flexible coupling characteristics of different stiffness elastic supports and rotor structures, and establishes an analytical dynamic model of the dual-rotor system. Based on the established dynamic model, the natural char-acteristics of the dual-rotor system are analyzed. The model was validated using two different research methods: the rigid-flexible coupling multi-body system dynamics simulation platform ADAMS, and finite element analy-sis. The dynamic model of the dual-rotor system established in this paper can meet the requirements of hierar-chical rigid-flexible coupling of system and structure, overall mass distribution, and stiffness distribution. In particular, it can also effectively realize the simulation of multi-facet and multi-phase unbalanced vibration of the rotor system. The research methods of this paper can further enrich the basic theory of dynamics and vibration of the aero-engine rotor system.

Aiming at the problems of low detection accuracy and the large size of the pedestrian detection algorithm, to improve the edge intelligent recognition capability of the terminal, this paper proposes a lightweight pedestrian detection scheme based on the improved YOLOv5. In this paper, the algorithm first takes the original YOLOv5 as the basic framework and uses the Ghost Bottleneck module to replace the C3 module in the original YOLOv5 network to reduce the number of parameters, eliminate redundant features, and obtain a more lightweight model. Then the attention mechanism CBAM module is added to improve the feature extraction capability and detection accuracy of the algorithm. After experimental verification, the improved lightweight YOLOv5 algorithm significantly reduces the model size and computational cost while guaranteeing accuracy, which is suitable for deployment in edge devices.

In recent years, methods of road damage detection, recognition and classification have achieved remarkable results, but there are still problems of efficient and accurate damage detection, recognition and classification. In order to solve this problem, this paper proposes a road damage VGG-19 model construction method that can be used for road damage detection. The road damage image is processed by digital image processing technology (DIP), and then combined with the improved VGG-19 network model to study the method of improving the recognition speed and accuracy of VGG-19 road damage model. Based on the performance evaluation index of neural network model, the feasibility of the improved VGG-19 method is verified. The results show that compared with the traditional VGG-19 model, the road damage VGG-19 road damage recognition model proposed in this paper shortens the training time by 79 % and the average test time by 68 %. In the performance evaluation of the neural network model, the comprehensive performance index is improved by 2.4 % compared with the traditional VGG-19 network model. The research is helpful to improve the model performance of VGG-19 road damage identification network model and its fit to road damages.

In order to improve the communication performance between different equipment in the seismic detection system, a wireless network system with MIMO (Multiple Input and Multiple Output) characteristics was designed and applied in the paper. On the basis of 5G communication, a new data conversion and transmission model was built, which can improve the rate of signal transmission and reduce the bit error rate and power consumption. For the purpose of power optimization, the overall framework of the network system was improved, of which power characteristics and performance were verified. The conjugate beam was normalized, and the cumulative distribution function under different downlink rates was obtained based on the maximum minimum power control scheme. In order to verify the energy-saving effect of the design, the ADC (Analog-to-Digital Conversion) power model is introduced. Through simulation analysis, the change rules of spectrum efficiency and energy efficiency under different network nodes were obtained. The results show that the normalized conjugate beam can be less affected by the transmission nodes, and the power control is more reliable under the same conditions. The research and application of this subject can significantly improve the wireless communication performance of the seismic monitoring system, reduce the power consumption of network equipment, improve the data transmission efficiency, and provide strong technical support for seismic prediction and data analysis. Through the test of artificial earthquake, it is verified that the communication scheme designed in this paper has higher transmission efficiency and lower bit error rate, and is very suitable for the long-distance transmission of seismic signals.

In view of the fact that the traditional study of the chain breaking condition of the scraper conveyor only considers the case of two-way simultaneous chain breaking, this paper mainly studies the single-side chain breaking condition and its influence on the longitudinal vibration and swing vibration characteristics of the scraper chain system. Using the tension calculation principle of the point-by-point tension method, each section of the scraper in the study area is taken as a unit. A coupled dynamic model of longitudinal and oscillating vibration of scrapers is established and connected with Voigt model. The dynamic response laws of the longitudinal and oscillating vibration of the scraper before and after the chain fracture under different transportation conditions are numerically simulated. The calculation results show that when there is material behind the broken chain, the longitudinal tension of the chain and the oscillating vibration of the scraper reach the maximum value, and the chain speed fluctuation reaches 543.1 % compared with the normal operating conditions. Only when there is material in front of the broken chain, the longitudinal tension mutation of the chain and the oscillating vibration value of the scraper are weaker than those of the previous working conditions. When there are materials at the front and back of the broken chain, the sudden change of the longitudinal tension of the chain and the oscillating vibration value of the scraper are the minimum, but they also reach twice the normal working condition, and the chain speed fluctuation reached 194.4 %. The research results of this paper provide a theoretical basis for grasping the operation status of the scraper conveyor in the coal mine and predicting the life of the scraper conveyor.

Graphene possesses not only excellent optical, electrical and thermal properties but also outstanding thermoelectric and photothermal conversion capabilities. The application of graphene with functional responses plays a vital role in the development of intelligent materials intended for flexible actuators and intelligent robots. Cellulose paper is foldable and is a hydrophilic network comprised of porous cellulose fibres. In this paper, graphene composites as well as cellulose paper were taken as basic materials, which were further combined with other polymer materials (biaxially oriented polypropylene film (BOPP) and poly (3, 4-ethylenedioxythiophene/polystyrene sulfonate) (PEDOT: PSS). PEDOT: PSS solution can penetrate into the porous network of the paper to form a high-strength nanocomposite structure. A flexible thin film driver capable of multiple stimuli under light, heat and humidity was produced. Through characterization, it was found that the bending ability of the composite film was significantly improved in response to stimulation.

Probabilistic seismic hazard analysis is an important scientific basis for building seismic fortification. Unlike most seismic hazard analyses starting from the perspective of magnitude, this paper presents a seismic hazard analysis method based on the monthly maximum peak ground acceleration (PGA) distribution. In this paper, cities of Chongqing, Chengdu, and Kunming in southwest China are taken as examples where historical earthquake events from 1920 to 2020 with surface wave magnitude (Ms) greater than or equal to 3 and epicentral distances within 400 km are selected for analysis. PGA data are back-calculated from Ms data recorded in the earthquake catalog using the attenuation relation of seismic parameters. By considering the monthly maximum PGA values of the three cities as statistical samples, regression analysis is performed to obtain the monthly maximum PGA distribution and the frequency-PGA relation respectively. Based on the Poisson model and the parameters obtained from the regression analysis, then seismic hazard analysis is conducted to derive year exceedance probability vs. PGA curves and recurrence interval vs. PGA curves. Finally, earthquake events with the epicentral distance within 200 km, 300 km, and 400 km are respectively analyzed to discuss the influence of the epicentral distance on results of seismic hazard analysis.

Considering that the scraper will produce longitudinal and torsional pendulum vibration when passing through the bending section, and have a great influence on the motion characteristics of the scraper conveyor, this paper studies the longitudinal and torsional pendulum coupling vibration characteristics of the scraper conveyor under the working condition of over-bending section for the first time. Firstly, the simplified model of torsional pendulum vibration of scraper chain system is established based on Voigt model and point-by-point tension method. Then, the change law of scraper group vibration and chain tension under the condition of scraper bending is studied. Thirdly, through the influence area and attenuation characteristics of torsional pendulum vibration, the thumbnail model of torsional pendulum vibration is constructed. Finally, the longitudinal and torsional pendulum coupling vibration dynamic model of the scraper chain system is constructed based on the torsional pendulum vibration abbreviation model, and the overall longitudinal and torsional pendulum vibration characteristics of the scraper conveyor are studied when the scraper is over the bending section. The conclusion of this paper provides a theoretical basis for better understanding the operation characteristics of scraper conveyor in coal mine.

Transport noise and vibration have a negative influence on the environment, human health, and quality of life. The measurement and analysis of transport noise and vibration are required by the regulations and guidelines that various countries have set in order to manage and mitigate these effects. This review paper provides an overview of the requirements for the measurement and analysis of vibration and noise in transportation in different countries. The paper examines the measurement and analysis parameters, methods, and standards used in the United States, Europe, Australia and Japan. The review finds that although the requirements for measurement and analysis vary between countries, there are common parameters and methods used worldwide, such as sound pressure level and frequency spectrum measurements, noise and vibration impact assessment, prediction, and control measures. A comprehensive understanding of the measurement and analysis requirements for transport noise and vibration in different countries is essential for ensuring compliance with regulations, mitigating adverse impacts, and promoting sustainable transport development.

Vibration-driven locomotion systems are widely used in various industries, particularly, in the form of capsule-type robots, wheeled platforms, worm-like units, etc. Because of the changeable operating conditions, such systems require continuous control of their kinematic and dynamic characteristics. The main purpose of the present paper is to define the optimal excitation conditions (forced frequencies and phase shifts) of a wheeled two-module vibration-driven robot equipped with two unbalanced rotors. The research methodology contains four stages: developing the robot’s dynamic diagram and mathematical model describing its motion; designing the robot’s simulation model in the MapleSim software; numerical modeling of the system locomotion conditions in the Mathematica software; simulating the system dynamic behavior in the MapleSim software. The obtained results show the time dependencies of the system’s kinematic characteristics at different phase shift angles of the unbalanced rotors. The major scientific novelty of this paper consists in substantiating the possibilities of adjusting the system’s operational parameters in accordance with the changeable technological requirements by means of changing the phase shift angles of the unbalanced rotors. The proposed ideas and obtained results can be used while developing new designs of robots based on the two-module vibration-driven systems and while improving the control systems for adjusting their performance in accordance with the changeable operational conditions.

Collaborative robots are machines that work hand in hand with humans; or as the name suggests, collaborate with them in a specific workspace. These robots are not enclosed in confined safety zones like traditional robots, as they interact very closely with humans. Though this is the case, appropriate measures are captivated while designing these robots considering human safety. These robots are well-versed in adapting to changes and frequent upgrades. They are flexible enough to carry out complex tasks. Due to these abilities, they become a significant asset in the manufacturing field. It’s been many years now since cobots are introduced in the industry sector. So, this is the right time to review various applications of cobots in manufacturing. First, the paper starts with a brief introduction followed by an extensive literature review which was structured after reviewing 76 research papers and articles. It ends with some essential conclusions. This paper discusses the diverse applications of cobots used in the manufacturing sector and their advantages. Further, it highlights the future of cobots and how they will be a boon for a technology-driven world.

During hard rock excavation in the process of tunnel construction, the hard rock excavator wears seriously and quickly and reduces its excavation efficiency. Aiming at this problem, this paper proposes a composite rock breaking method by impact rolling and cutting as a solution. In this paper, the composite rock breaking characteristics of impact hob are studied. The impact cutting load of the hob was analyzed, and the hobbing force equation and the rock crushing volume equation were established. The effects of different impact frequencies and impact loads on the cutting force and rock crushing characteristics of the hob were analyzed by experiments. The results show that under a certain thrust and hob spacing, with the increase of the impact frequency, the rock ridge between the two hobs gradually decreases, while the crushed volume of the rock increases gradually. Under the same axial load and cutter spacing conditions, with the increase of the impact frequency, the hob shear force decreases significantly. Under a certain axial load and impact frequency, with the increase of impact load, the crushing volume of rock and the hob shear force decrease significantly. These test results are of great significance for guiding the efficient excavation of hard rock tunnels.

An Industrial Robot is used in industries for transporting, assembly, manufacturing and many more applications. Industrial robots include manufacturing robots, material handling robots, robotic arm and manipulator, mobile robots, assembly robots, etc. In this paper, Mobile Robots are further being discussed. One of the tools that a Mobile Robot uses to function is all with the help of Artificial Intelligence (AI) for performing several tasks autonomously. AI works as the intelligence of the human body for robots. AI is the technology that made it possible for robots to be capable of being totally autonomous. AI marks its presence in the Manufacturing Industry with the 4th Industrial Revolution. AI has several algorithms that help in collecting and analyzing data in order to help robots to function in specific ways. These techniques include Fuzzy Logic, Genetic Algorithm, Neural Network, etc. In this paper, the role of these algorithms in Mobile Robots is discussed. Based on the review of 74 papers and articles, it is observed that there are no review papers discussing the role of nature-based and conventional algorithms used for navigation in Mobile Robots. The use of different AI techniques for specific applications has been discussed in tabular form in this paper.

Investigate whether different results about the physical properties of the same biomaterial frequently found in the literature are due to chewing simulator deficiency. A literature review was performed by searching for data on indicators of test accuracy, reproducibility, maintenance of test parameters during all experiments, and standards in the articles or in the sites of manufacturers. The database searched was CAPES PORTAL, and the keywords used were “bite force” AND “simulator”, “chewing simulator” and “mastication simulator”. Including criteria for the papers are publication filter date of “January 1, 2016”, articles in English, Spanish and Portuguese language were accepted. The first 100 papers that seemed suitable when considering the title and abstract were recovered. Only one simulator used for food property studies had the parameters searched. In the customized simulators for biomaterial properties, only one showed standards, and 8 showed all other parameters searched. All manufactured simulators showed all parameters searched, and only two manufactures did not show standards. Based on the data obtained, the disparate results of experiments with dental materials appeared to be more related to the test conditions than to the testing machines. Knowledge Transfer Statement The findings of the current review suggest that the chewing simulators used in preclinical research are reliable, bringing safety to restorative processes regarding the material. Any difference in preclinical investigations about dental material physical properties is due to test conditions other than chewing simulators.

The performance analysis of wind turbine systems should be considered when calculating the wind speed relative to the wind turbine structure, and is essential for wind turbine design. Since the conditions are precarious in transient state and the operating environments are challenging, the wind turbine is a complex, multivariate, nonlinear system. This paper presents a novel dynamic response test method for wind turbines based on three-dimensional digital speckle measurement. This method use a real-time speckle image collection of objects in various stages using binocular stereo vision to perform stereo matching of deformation points on object surface. A digital image correlation algorithm is used to rebuild three-dimensional space coordinates of matching points so as to achieve wind turbine dynamic response. A laboratory-scale experimental platform is constructed to test the dynamic response of the wind turbine system. In order to verify the accuracy of the proposed method, a three-dimensional model of a wind turbine is built. With dynamic structure response process adopted to carry out dynamic analysis and compare theoretical results with test results, the results vary by less than 10 %, indicating that the test method presented in the paper is feasible and effective.

In this paper, the fuel pump impeller was selected as a typical airborne equipment for the investigation of random vibration fatigue. First, based on the platform of ANSYS WORKBENCH, the reasonable calculation of FSI for the impeller was carried out. Then, the stress was transferred to modal analysis, and the prestress-structure modal was extracted. Through random vibration response analysis, the stress of the impeller was obtained. The Palmgren and Miner rule and Dirlik fatigue calculation method was used to calculate fatigue life, and the result was consistent with practice. The work in this paper provided a method about how to obtain random vibration fatigue life with prestress-structure, which was critical references for aviation technologists.

Oil tank level is an important control parameter in oil depot management. According to the principle that the liquid in the oil tank can absorb the guided wave propagation energy in the tank wall, this paper studied a non-reference detection method of external ultrasonic liquid level switch based on the signal energy change value between the current and the previously liquid level detection signal. The experimental results show that the ultrasonic guided wave with the center frequency of 30 kHz is sensitive and low misjudgment to liquid level detection. According to the experimental setup, the liquid level judgment threshold is set to 0.9890. The influence of the liquid on the guided wave propagation in the tank wall decreases with the frequency of the guided wave increase. Finally, the effectiveness of the proposed method is verified on a diesel oil tank. The research of this paper provides a method for the research of oil tank external liquid level switch technology, and provides an idea for the research of oil tank liquid level measurement based on ultrasonic guided wave.

In this paper, the 14-equations of pipeline system were written as matrix forms in frequency domain with Laplace transformation and further solved by transfer matrix method (TMM). Moreover, the added mass and added damping models were established and combined with the TMM for decoupling investigated the Turbulence-Induced Vibration (TIV) of clamped-clamped pipe system. Firstly, the feasibility of the TMM for analyzing the frequency responses of water-filled pipelines with free support boundary conditions and the added mass, added damping for decoupling investigation of TIV were finished verify. Then the frequency responses for Fluid-Structure Interaction (FSI) problems of pipeline with different flow velocities were acquired. The results indicate that the calculated frequencies agree well with corresponding data yield from Galerkin method. And the increasing flow velocity results in a decreased amplitudes of the frequency responses due to the effect of fluid added damping. Those results of the research in this paper implied that the decoupling method composed of the TMM that considered the added mass and added damping is validity and accuracy for frequency response analysis of the pipeline.

Fuel cell air filter can absorb harmful impurities and gases to fuel cell and is an important component to ensure the service life of fuel cell. The previous researches mainly focus on the activated carbon and filter paper materials in the laboratory. The object of this paper is the fuel cell air filter product assembly being used by the main engine plant. According to the tests of air filters with different carbon contents, it was found that the adsorption efficiency of current products for NO2 was better than that of C7H8, SO2 and C4H10. Based on the adsorption mechanism of activated carbon for different gases, the adsorption difference was explained. The testes also found that there was no direct relationship between the change of carbon content of products containing activated carbon and the fractional filtration efficiency. The main reason is that the gap between the activated carbon particles is large, which cannot effectively intercept dust particles. The filtering of small size particles still depends on the melt-blown layer material in the air filter element and its electrostatic electret process. It was also found that there was a positive correlation between inlet air resistance and carbon content, and a negative correlation between dust holding capacity and carbon content. This test results can help the main engine factory understand the performance and improvement direction of products.

The analysis of rail/wheel sliding friction heat is a very important research field. The numerical simulation is often adopted to calculate the friction heat, and experimental method is relatively few. In this paper, an experimental machine is designed to simulate the rail/wheel sliding contact. At the same time, a rail/wheel contact wear model and a friction heat transfer model are established. The characteristics of temperature on rail/wheel sliding contact are analyzed by experimental test and numerical calculation. The research results show that the temperature rise of wheel and rail is quick in the initial sliding contact stage, then gradually slows down. The temperature of wheel is higher than that of rail at the same depth from the contact surface. In the initial sliding stage, the wheel temperature rises faster than the rail temperature, which is related to the size of contact surface and the concentration degree of friction heat. Moreover, the results of this paper show that the temperature values of the rail/wheel obtained through experimental test and numerical calculation are in good agreement. The experimental and numerical calculation methods used in this article can be adopted to analyze the contact problems of other sliding friction pairs.

Target detection is an important problem in computer vision and has important research value in the fields of pedestrian tracking, license plate recognition, and unmanned vehicles [1].The Viola-Jones algorithm is used to detect frontal face images, which improves the speed of face detection by tens or hundreds of times while obtaining the same or even better accuracy, but for special and HOG captures local shape information better and has good invariance to both geometric and optical changes, SVM solves machine learning in small sample cases, but its feature descriptor acquisition process is complex and has high dimensionality, leading to poor real-time performance, and the support vector machine algorithm is difficult to implement for large-scale training samples, while the deep learning-based YOLOv5 target detection algorithm combines the advantages of Viola-Jones algorithm and HOG+SVM algorithm to make up for the shortcomings of the above two algorithms, which is not only very stable for occlusion and complex case processing, but also can be implemented for large regular training samples, but the accuracy of YOLOv5 for target detection is not ideal, and this paper adds SENet mechanism in YOLOv5, which can make the network better to learn the locations in the images that need attention. Therefore, this paper first introduces the traditional target detection algorithm, then introduces and analyzes the Yolov5 algorithm, and improves and optimizes it, and compares it with the traditional target detection algorithm, and the results show that the improved Yolov5 algorithm has better results for target detection.