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Dust accumulation is severe during coal mine excavation. Currently, research on the dust settlement law and optimization under mixed air flow control in fully mechanized excavation faces is not in-depth enough. Based on a hybrid air flow control system and relying on the fully mechanized excavation face of Shaanxi Coal Group Shenmu Ningtiaota Mining Co., Ltd., the influence of mixed air flow control parameters such as the distance from the pressure air outlet to the working face, the right angle of the pressure air outlet, the pressure air outlet diameter, the distance from the extraction air outlet to the working face, and the pressure extraction ratio on the dust settlement law is analyzed. As the distance between the pressure air outlet and the working face increases, the proportion of large particle dust in the cross-section of the personnel breathing zone on the return air sides and the driver's location first increases, then decreases, and then increases again. The proportion of small particle dust increases. As the right deviation angle of the air inlet increases, the proportion of large particle dust in the personnel breathing zone section on the return air sides and the driver's location changes significantly. As the diameter of the air inlet increases, the proportion of small particle dust in the driver's location section first increases, then decreases, and then increases again. The proportion of large particle dust in the personnel breathing zone section on the return air side first increases and then decreases. As the distance between the extraction air outlet and the working face increases, the proportion of large particle dust at the driver's location section first increases and then decreases. The proportion of small particle dust first increases and then decreases and then increases again. The particle size distribution of dust at the personnel breathing zone section on the return air side does not change much. As the pressure-pumping ratio increases, the proportion of small particle dust in the cross-section of the personnel breathing zone on return air sides and the driver's location decreases. Taking the above air flow control parameters as independent variables, the average concentration of total dust in the personnel breathing zone on the return air side and the average concentration of exhaled dust at the driver's location are the optimization objectives. A dust settlement optimization regression model is established, and the particle swarm optimization algorithm is used to solve the model. The optimal air flow control scheme is obtained. The distance between the pressure air outlet and the working face is 8.9 meters, the right angle of the compressed air outlet is 14.8°, the diameter of the compressed air outlet is 0.9 meters, the distance between the extraction air outlet and the working face is 4.3 meters, and the pressure-pumping ratio is 1.1. The experimental platform for dust settlement under wind flow control is built. The experimental results show that the error between the test values and the simulated values of the dust settlement optimization regression model is within 13%, which verifies the accuracy of the model. The optimized dust with particle sizes of 71-100 μm is significantly affected by the wind flow regulation parameters and settles in front of the roadheader. After optimization, the average dust concentration of total dust in the personnel breathing zone on the return air side and the average dust concentration at the driver's location decrease by 47.4% and 42.4%, respectively, indicating a significant dust reduction effect.

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To better control the PEMFC air flow, this paper introduces a distributed deep reinforcement learning-based adaptive proportional integral (PI) controller for controlling air flow in a proton exchange membrane fuel cell (PEMFC). In this paper a novel algorithm for tuning the controller is proposed, termed the multi-role exploration strategy distributed deep deterministic policy gradient (MESD-DDPG), which builds upon the deep deterministic policy gradient (DDPG) by employing various trick including a multi-role exploration strategy. In this strategy, explorers and followers with different exploration principles are used for distributed exploration to enhance the exploration efficiency. Moreover, a probability experience replay mechanism is included to foster the training efficiency. In addition, hot start mechanism of experience pool is applied to deal with the reward sparsity problem. The MESD-DDPG also includes a number of innovations for solving the problem of Q-value overestimation. The proposed MESD-DDPG algorithm considers the PI coefficients naturally in the objective and enables the controller better online coefficient adjusting ability via learning, which leads to improved controller adaptability. The simulation results demonstrate the adaptability and the excellent performance of the MESD-DDPG adaptive PI controller.

At present, it is difficult to adjust the air flow at the outlet of the wind pipe dynamically by the total ventilation control method commonly used in the excavating face, resulting in insufficient air volume or unreasonable air flow distribution, and causing safety hazards such as gas and dust accumulation. Taking S1200-Ⅲexcavating face of Ningtiaota Mine as an example, by analyzing the problems of the original wind field and the requirements of wind flow control, the air flow control device is designed, which installed a mechanical structure driven by a pneumatic cylinder or a pneumatic motor. The device is able to realize the dynamic adjustment of outlet deflection angle, caliber size and front-back displacement. This paper introduces the design scheme of mechanical system, pneumatic actuation system and control system of the device. ANSYS Workbench software is used to conduct finite element analysis on the safety of the mechanical system. The results show that the maximum stress is 87.2 MPa, the safety factor is 2.69, the maximum deformation is 0.84 mm, and the average deformation is 0.42 mm. FluidSIM software is applied to simulate and analyze the pneumatic actuation system. The results show that the device can complete the predetermined action and run smoothly and reliably. Underground test results show that after adopting this device, the air flow distribution at the driver and pedestrian breathing zone height is more reasonable. When the air duct outlet is 5 m away from the working surface, the dust concentration at the driver and pedestrian breathing zone is reduced by 45.3% and 33.4% respectively compared with situation before the control. When the air outlet is 10 m away from the working face, the concentration is reduced by 40.4% and 34.3% respectively.

This paper presents a novel technique of an active control to suppress sheet flutter. In this technique, sheet flutter is actively and non-contactly suppressed by injection and suction air flows through a nozzle. A nozzle is combined with a speaker as an actuator, and this device is drove in a sheet displacement feedback system. PET sheet is used as a controlled object, and the sheet is supported upper end in a wind tunnel. To show the effectiveness of this technique for sheet flutter suppression, the suppression characteristics are experimentally examined. Then, the suppression effectiveness is evaluated at the increased rate of the flutter velocity with control as compared to it without control. Moreover, air flow patterns around the nozzle and the sheet during control are visualized by the smoke wire method. Lastly, the control effects by injection and suction air flows to the sheet are examined in terms of air flow patterns, frequency response characteristics, and unsteady pressure. As a result, this paper shows the effectiveness of the proposed device and technique for sheet flutter suppression, and the flutter velocity is increased by 50 % with control as compared to without control. In this technique, the injection and suction air flows from the nozzle change the airflow around the sheet, not directly apply momentum on the sheet. Therefore, this technique is an air flow control.

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• Thorough investigation of the helical and kink buckling behaviors of thick-walled elastic tubes during twisting is performed. • The forming mechanism and geometrical characteristics of periodic kink structures in the torsional post-buckling process of tubes are revealed. • Efficient prediction and interpretation of kink structures using an equivalent plate model are provided. • The self-locking mechanism of kinks in twisting tubes is identified, enhancing the air-blocking of soft valves. • Soft robotic applications of twisting tubes as soft valves and rotation selectors are demonstrated with pre-stretch effect. Soft materials and structures have been blooming with utmost popularity, showing great potential as soft machines for delicate design and new application. Among them, the simple structures of soft tubes are widely applied in engineering. However, a comprehensive understanding of their twisting behaviors is still lacking. In this study, the complete response of hyperelastic tubes under large-scale torsion is explored. The helical-buckling critical conditions and post-buckling characteristics of twisting tubes are revealed via simulations and experiments. Notably, it is found that a sequence of equal-length kinks along the tubing axis appear as the subsequent buckling of twist after the first helical buckling. And the factors determining the geometry of the periodic kink structure are discussed. To efficiently interpret and predict the kink responses, we employ an equivalent plate model based on finite element analysis. Additionally, the self-locking mechanism of kink for gas-blocking purpose and the pre-stretch effect on the twisting behaviours are investigated. Finally, mechanics design of twisting tubes served as soft valves and its application in soft robotics are demonstrated. This study with insights in extreme twist of elastic tubes is hoped to provide a reference to the off-the-shelf tubes widely applied in industry and inspire new flashes of soft machines. [Display omitted] [ABSTRACT FROM AUTHOR]

The air installation consists of high-capacity centrifugal compressors which pumps in parallel in an industrial pipe. The total air flow rate of the compressors in the pipe can be adjusted by acting on the air suction valve of each compressor so that the shut-off or opening of the compressor valve can regulate the flow rate of each compressor, which results in total flow control. The problem is to replace the analog control of the compressors with a digital control. If we have two types of compressors in the plant, the automatic setting involves closing or opening the suction valve of the compressors in a certain order so that besides the total objective to pump a particular flow we also have high energy efficiency. [ABSTRACT FROM AUTHOR]

In this paper it is presented an optimized practical solution for controlling the temperature and flow of a multivariable process. The solution is based on software architecture that solves the technical problem of coupling between the two parameters. Combining the theoretical analysis with the experimental analysis, it was established the transfer functions of the MIMO system (two input and two output), decomposing the process in several SISO systems. Compared with the multivariable solution which is difficult to implement on a classical real-time structure, it was designed a control system based on numerical PI regulators. The implementation on a PLC demonstrated that this method is effective ensuring robustness performance for large areas of temperature and pressure parameters.

Highlights: [•] Minimizing hydrogen consumption in fuel cell applications. [•] Perturbation strategy for optimization. [•] Virtual sensing of the oxygen excess ratio. [•] Hardware in the loop test of a FPGA controller. [ABSTRACT FROM AUTHOR]

Abstract: In this study, a heating, ventilating and air-conditioning (HVAC) system with different zones was designed and tested. Its fan motor speed and damper gap rates were controlled by two controllers (i.e. a PID controller and an intelligent controller) in real time to minimize its energy consumption. The desired temperatures were realized by variable flow-rate by considering the ambient temperature for each zone and evaporator. The PID parameters obtained in our previous theoretical work using fuzzy logic were utilized in this study. The experimental data used in this study was collected using a HVAC system built in a laboratory environment. The fan motor speed and damper gap rates were predicted using wavelet packet decomposition (WPD), entropy, and neural network (NN) techniques. WPD was used to reduce the input vector dimensions of the intelligent model. The suitable architecture of the NN model is determined after certain trial and error steps. According to test results, the developed model performance is at desirable level. Efficiency of the developed method was tested and a mean 95.62% recognition success was obtained. This model is an efficient and robust tool to predict damper gap rates and fan motor speed to minimize energy consumption of the HVAC system. [Copyright &y& Elsevier]

Abstract: In this paper, a heating, ventilating and air-conditioning (HVAC) system was designed and two different damper gap rates (actuators position) of the HVAC system were controlled by a conventional PID (proportional–integral–derivative) controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the required humidity for the same indoor volume. The realized system has a zone with variable flow-rate by considering the ambient temperature and humidity. The required air flow was supplied by controlled of the dampers placed on the entrance ducts of indoor. Programmable Logic Controller (PLC) used PID control algorithm was utilized to control the system. This system has been controlled by a PLC based closed-loop controller. In this work, the realized system has been controlled by PLC used PID control algorithm. The optimal values of PID parameters were obtained by using Fuzzy sets. Fuzzy adaptive control has been performed to maximize the performance of the system. Efficiency of fuzzy adaptive control (FAC) developed method was successfully obtained. [Copyright &y& Elsevier]

Abstract: The aim of this study is to design a HVAC system which damper gap rates have been controlled by PID controller. One of the dampers was controlled by using the required temperature for the interested indoor volume while the other damper was controlled by using the required humidity for the same indoor volume. The realized system has a zone with variable flow-rate by considering the ambient temperature and humidity. In the authors’ previous theoretical work, PID parameters were theoretically obtained by using fuzzy sets for the same HVAC system. Optimization with Fuzzy Modeling Approach of PID parameters has been performed to maximize the performance of the system. The obtained PID parameters in the previous theoretical work were used in this study. Besides, the damper gap rates of a HVAC system with only one zone were predicted by using Artificial Neural Fuzzy Interface System (ANFIS) method. The input–output data sets of this system were first stored and then these data sets were used to obtain its intelligent model and control based on ANFIS. Efficiency of the developed ANFIS method was tested and a mean 99.98% recognition success was obtained. This paper shows that the values predicted with the ANFIS can be used to predict damper gap rate of HVAC system quite accurately. Therefore, faster and simpler solutions can be obtained based on ANFIS. [Copyright &y& Elsevier]

Abstract: In this paper, a HVAC (heating, ventilating and air-conditioning) system has two different zones was designed and fan motor speed to minimize energy consumption of the HVAC system was controlled by a conventional (proportional–integral-derivative) PID controller. The desired temperatures were realized by variable flow-rate by considering the ambient temperature for each zone. The control algorithm was transformed for a programmable logic controller (PLC). The realized system has been controlled by PLC used PID control algorithm. The input–output data set of the HVAC system were first stored and than these data sets were used to predict the fan motor speed based on adaptive network based fuzzy inference system (ANFIS). In simulations, root-mean-square (RMS) and the coefficient of multiple determinations (R 2) as two performance measures were obtained to compare the predicted and actual values for model validation. All simulations have shown that the proposed method is more effective and controls the systems quite well. [Copyright &y& Elsevier]

Abstract: For PEM fuel cells supplied with air, pressure and flow control is a key requirement for an efficient and dynamic operation because fuel cells are in risk of starvation when the partial pressure of oxygen at the cathode falls below a critical level. To avoid oxygen starvation and, at the same time, to allow for a dynamic operation of the fuel cell system, both excess ratio of oxygen and cathode pressure need to be adjusted rapidly. In this paper a model-based control structure is proposed that comprises a multivariable control of the cathode pressure and the excess ratio of oxygen using the mass flow controller (MFC) and the outlet throttle as actuators. For both controlled variables appropriate desired values can be specified independently. As the derived dynamic model of the air supply system is nonlinear, advanced control techniques using differential flatness are applied. Since the partial pressure of oxygen in the cathode flow field is a state variable that is hardly accessible by measurement, a tracking observer is employed to estimate this pressure using the measured air pressure at the outlet throttle. Thereby, the observer enables the control system to detect both temporary shortages of oxygen and peak pressures at the cathode and to counteract accordingly. [Copyright &y& Elsevier]