Fault diagnosis method for hydraulic waterproof valves based on a multi-sensor information fusion and CNN-BIGRU-Attention model
In the field of construction engineering,particularly with respect to mixing equipment in projects,the complexity of hydraulic working media often resulted in varying degrees of malfunction in hydraulic waterproof valves.Moreover,harsh working environments and complex noise backgrounds made fault diagnosis of hydraulic waterproof valves difficult.To address this issue,a fault diagnosis method of waterproof valves based on multi-sensor information fusion and a convolutional neural network-bidirectional gated recurrent unit-attention mechanism model was proposed.Firstly,considering that a single sensor's vibration signal might inadequately express fault characteristics,three sensors were employed to collect noisy vibration signals,and the necessary preprocessing was performed.Secondly,16 time-domain features,5 frequency-domain features and 3 time-frequency domain features of the signal were extracted.These features were fused using the entropy weight method to enhance their representativeness.Then the fused multi-dimensional feature set was input into the CNN-BIGRU-Attention model for feature recognition.Finally,the effectiveness of this method was validated through practical hydraulic waterproof valve fault diagnosis experiments.The research results indicate that features extracted with multiple sensors are more comprehensive.The fusion of information helps capture a more complete set of hidden data features,and significantly improves diagnostic accuracy.Comparing to other feature recognition methods,the fault diagnosis accuracy of hydraulic waterproof valves using the proposed method increased by 6.7%,4.6%,and 14.2%,reaching 96.86%,which proves the effectiveness of the method.This method provides a novel,efficient solution to a prevalent issue in construction engineering,combining advanced machine learning techniques with practical engineering applications.
hydraulic transmission systemhydraulic waterproof valvemulti-sensorsliding time windowTeager energy operator(TEO)entropy weight methodconvolutional neural network-bidirectional gated recurrent unit-attention(CNN-BIGRU-Attention)model
万方数据
维普
