Fault Detection and Diagnosis of Pneumatic Control Valve Based on a Hybrid Deep Learning Model

As the growing requirements for the stability and safety of process industries,the fault detection and diagnosis of pneumatic control valves have crucial practical significance.Many of the approaches were presented in the literature to diagnose faults through the comparison of residual sequences with thresholds.In this study,a novel hybrid neural network model has been developed to address the issue of pneumatic control valve fault diagnosis.First,the feature extractor automatically extracts in-depth features of the signals through multi-scale convolutional neural networks with different kernel sizes,which not only adequately explores the local distinguishable features,but also takes into account the global features.The extracted features are then fused by the feature fusion layer to reduce redundant features.Finally,the long short-term memory for fault identification and the dense layer for fault classification.Experimental results demonstrate that the average test accuracy is above 94%and 16 out of the 19 conditions can be successfully detected in the simulated actual industrial environment.The effectiveness and practicability of the proposed method have been verified through a comparative analysis with existing intelligent fault diagnosis methods,and the results suggest that the developed model has better robustness.

A rotary pneumatic actuator for the actuation of the exoskeleton knee joint

Rotary pneumatic actuators that are made out of linear one are always best suited for exoskeleton joint actuation due to its inherent power to weight ratio. This work is a modified version of knee actuation system that has already been developed and major modifications are made in order to make it more suitable for human wearing and also to reduce its bulkiness and complexity. The considered actuator system is a rotary actuator where a pulley converts the linear motion of the standard pneumatic piston into the rotary motion. To prove the capability of the actuator, its performance characteristics such as torque and power produced are compared to the required torque and power at the knee joint of the exoskeleton in swing phase and are found to be excellent. The two-way analysis of variance（ANOVA）is performed to find the effect of the throat area valve on knee angle. The ANOVA shows the significant effect of the throat area variation on the knee angle flexion made by the proposed actuator. A relationship between the throat area of flow control valve, that is connected to the exit port of the direction control valve, and angular displacement of the knee joint has been formulated. This relationship can be used to design a control system to regulate the mass flow rate of air at the exit and hence the angular velocity of the knee joint can be controlled.