scholarly journals Failure Type Prediction Using Physical Indices and Data Features for Solenoid Valve

2020 ◽  
Vol 10 (4) ◽  
pp. 1323 ◽  
Author(s):  
Jun Peng ◽  
Xuanheng Tang ◽  
Bin Chen ◽  
Fu Jiang ◽  
Yingze Yang ◽  
...  
Keyword(s):  
Frequency Band ◽  
High Speed ◽  
Current Data ◽  
Solenoid Valve ◽  
Data Set ◽  
Energy Characteristics ◽  
Band Energy ◽  
Failure Type ◽  
Braking System ◽  
Frequency Band Energy

A high-speed solenoid valve is a key component of the braking system. Accurately predicting the failure type of the solenoid valve is an important guarantee for safe operation of the braking system. However, electrical, magnetic, and mechanical coupling aging mechanism; individual differences; and uncertainty of aging processes have remained major challenges. To address this problem, a method combining physical indices and data features is proposed to predict the failure type of solenoid valve. Firstly, the mechanism model of the solenoid valve is established and five physical indices are extracted from the driven current curve. Then, the frequency band energy characteristics are obtained from the current change rate curve of the solenoid valve by wavelet packet decomposition. Combining physical indices and frequency band energy characteristics into a comprehensive feature vector, we applied random forest to both predict and classify the failure type. We generate a data set consisting of 60 high-speed solenoid valves periodically switched under accelerated aging test conditions, including driven current, final failure type, and switching cycles. The prediction result shows that the proposed method achieves 95.95% and 94.68% precision for the two failures using the driven current data of the 3000th cycle and has better prediction performance than other algorithms.

scholarly journals Lubrication State Recognition Based on Energy Characteristics of Friction Vibration with EEMD and SVM

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Hai-jie Yu ◽  
Hai-jun Wei ◽  
Jing-ming Li ◽  
Da‐ping Zhou ◽  
Li‐dui Wei ◽  
...  
Keyword(s):  
Frequency Band ◽  
Ensemble Empirical Mode Decomposition ◽  
Experimental Results ◽  
Support Vector ◽  
Intrinsic Mode Functions ◽  
Vibration Signals ◽  
Energy Characteristics ◽  
State Recognition ◽  
Band Energy ◽  
Frequency Band Energy

In order to identify different lubrication states, lubrication experiments were carried out on a Bruker UMT-3 tester. The experimental results show that the frequency band energy characteristics of friction vibration signals are different under different lubrication states. Based on this, a lubrication state recognition method with ensemble empirical mode decomposition (EEMD) and support vector machine (SVM) was proposed. The vibration signals were decomposed into a finite number of stationary intrinsic mode functions (IMFs) with the EEMD method. The first six IMF components containing the main friction information were retained to calculate the energy ratio and construct the feature vector. The experimental results show that the mixed lubrication state can be identified by hundred percent, and there is a slight confusion between boundary lubrication and dry friction. The results show that frequency band energy of friction vibration signals is an effective feature to identify different lubrication states, and the proposed method can be used to identify different lubrication states.

Research of Automobile Engine Fault Diagnosis Based on Wavelet Packet

2012 ◽  
Vol 472-475 ◽  
pp. 795-798
Author(s):  
Min Yong Tong
Keyword(s):  
Fault Diagnosis ◽  
Frequency Band ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Wavelet Packet ◽  
Automobile Engine ◽  
Band Energy ◽  
Diagnosis Method ◽  
S Model ◽  
Frequency Band Energy

A diagnosis method using wavelet packet, frequency band energy analysis and neural network was presented for the automobile engine fault diagnosis. Fault signal of automobile engine was decomposed at different frequency band by wavelet packet. According to the change of frequency band energy, fault frequency band of the automobile engine was found. Fault diagnosis knowledge is described by means of applying T-S model. Results from the experimental signal analysis show that the proposed method is effective in diagnosing the automobile engine faults.

Wavelet Packet analyses of Acoustic Emission Signal for Tool Wear in High Speed Milling

2013 ◽  
Vol 589-590 ◽  
pp. 600-605
Author(s):  
Shun Xing Wu ◽  
Peng Nan Li ◽  
Zhi Hui Yan ◽  
Li Na Zhang ◽  
Xin Yi Qiu ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Acoustic Emission Signal ◽  
High Speed ◽  
Feature Vector ◽  
Wavelet Packet ◽  
High Speed Milling ◽  
Band Energy ◽  
Emission Signal ◽  
Frequency Band Energy

Tool wear condition monitoring technology is one of the main parts of advanced manufacturing technology and is a hot research direction in recent years. A method based on the characteristics of acoustic emission signal and the advantages of wavelet packets decomposition theory in the non-stationary signal feature extraction is proposed for tool wear state monitoring with monitor the change of acoustic emission signal feature vector. In this paper, through the method, firstly, acoustic emission signal were decomposed into 4 layers with wavelet packet analysis, secondly, the frequency band energy of the have been decomposed signal were extracted, thirdly, the frequency band energy that are sensitive to tool wear were selected as feature vector, and then the corresponding relation between feature vector and tool wear was established , finally, the state of the tool wear can be distinguished according to the change of feature vector. The results show that this method can be feasibility used to monitor tool wear state in high speed milling.

Prediction Method of Grinding Chatter Based on ARIMA

2014 ◽  
Vol 971-973 ◽  
pp. 1288-1291 ◽  
Author(s):  
Zi Liang Yao ◽  
Min Wang ◽  
Tao Zan ◽  
Guo Fu Liu
Keyword(s):  
Natural Frequency ◽  
Frequency Band ◽  
Prediction Method ◽  
Vibration Monitoring ◽  
Energy Ratio ◽  
Grinding Process ◽  
Band Energy ◽  
Grinding Chatter ◽  
Chatter Prediction ◽  
Frequency Band Energy

The process of grinding chatter is divided into three states: stable grinding state, chatter gestation state and chatter state. The vibration signals of grinding process contain chatter features can correspond well to the changes of grinding process. By analyzing the natural frequency band energy ratio of grinding process, a method of grinding chatter prediction is proposed. Experimental results show that the natural frequency band energy ratio is beyond a certain threshold, chatter occurred, otherwise no chatter happened. The method of grinding prediction can provide reference for vibration monitoring in practice.

scholarly journals Researching Coal and Rock Character Recognition Based on Wavelet Packet Frequency Band Energy

2014 ◽  
Vol 6 (1) ◽  
pp. 1793-1797 ◽  
Author(s):  
Guanghui Xue ◽  
Xinying Zhao ◽  
Ermeng Liu ◽  
Weijian Ding ◽  
Baohua Hu
Keyword(s):  
Frequency Band ◽  
Character Recognition ◽  
Wavelet Packet ◽  
Band Energy ◽  
Frequency Band Energy

scholarly journals Mechanistic Characteristics of Double Dominant Frequencies of Acoustic Emission Signals in the Entire Fracture Process of Fine Sandstone

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3959 ◽  
Author(s):  
Chuangye Wang ◽  
Xinke Chang ◽  
Yilin Liu ◽  
Shijiang Chen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Fracture Process ◽  
Low Frequency ◽  
High Amplitude ◽  
Dominant Frequency ◽  
Band Energy ◽  
Ae Signal ◽  
Low Amplitude ◽  
Frequency Band Energy

To determine the intrinsic relationship between the acoustic emission (AE) phenomenon and the fracture pattern pertaining to the entire fracture process of rock, the present paper proposed a multi-dimensional spectral analysis of the AE signal released during the entire process. Some uniaxial compression AE tests were carried out on the fine sandstone specimens, and the axial compression stress–strain curves and AE signal released during the entire fracture process were obtained. In order to deal with tens of thousands of AE data efficiently, a subroutine was programmed in MATLAB. All AE waveforms of the tests were denoised by wavelet threshold firstly. The fast Fourier transform (FFT) and wavelet packet transform (WPT) were applied to the denoised waveforms to obtain the dominant frequency, amplitude, fractal, and frequency band energy ratio distribution. The results showed that the AE signal in the entire fracture process of fine sandstone had a double dominant frequency band of the low and high-frequency bands, which can be subdivided into low-frequency low-amplitude, high-frequency low-amplitude, high-frequency high-amplitude, and low-frequency high-amplitude signals, according to the magnitude. The low-frequency amplitude relevant fractal dimension and the high-frequency amplitude relevant fractal dimension each had turning points that corresponded to significant decreases in the middle and end stages of loading, respectively. The frequency band energy was mainly concentrated in the range of 0–187.5 kHz, and the energy ratios of some bands had different turning points, which appeared before the complete failure of the rock. It is suggested that the multi-dimensional spectral analysis may understand the failure mechanism of rock better.

scholarly journals Experimental Study on Influence of Borehole Arrangement on Energy Conversion and Acoustic Characteristics of Coal-Like Material Sample

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Chuanbo Hao ◽  
Zhiyuan Hou ◽  
Fukun Xiao ◽  
Gang Liu
Keyword(s):  
Acoustic Emission ◽  
Energy Conversion ◽  
Frequency Band ◽  
Acoustic Emission Signal ◽  
Conversion Ratio ◽  
Acoustic Characteristics ◽  
Band Energy ◽  
Emission Signal ◽  
Material Sample ◽  
Frequency Band Energy

This paper examines the effects of borehole arrangement on the failure process of coal-like materials based on its energy conversion and acoustic characteristics from the perspectives of energy, AE energy, AE spectrum, and frequency band. Findings from the study revealed that the presence of borehole can significantly reduce the conversion ratio and growth rate of elastic energy during the loading of coal-like material sample and delay the release of internal energy of the sample. Also, it can reduce the frequency band energy of the main frequency of acoustic emission signal but has little effect on the size and richness of the peak frequency of acoustic emission signal. The practice that makes drilling diameter and depth increase stepwise can minimize the elastic energy conversion ratio, the growth rate, and the main frequency band energy of acoustic emission signal of coal-like material sample and postpone the internal energy release of the sample to the greatest extent, so as to enrich the richness of the secondary frequency of acoustic emission signal. The results of this study have certain guiding significance for the layout of pressure relief boreholes in the production process of coal mines.

Analysis of Pressure Response Characteristics and Influencing Factors of the Automatic Pressure Regulating Valve in Electronic-Controlled Pneumatic Braking System of Commercial Vehicle

2021 ◽  
Author(s):  
Hanwei Bao ◽  
Zaiyu Wang ◽  
Xiaoxu Wei ◽  
Gangyan Li
Keyword(s):  
High Speed ◽  
Commercial Vehicle ◽  
Structural Parameters ◽  
Solenoid Valve ◽  
Pressure Response ◽  
Response Characteristics ◽  
Braking System ◽  
Automatic Pressure ◽  
Simulation And Experiment ◽  
Working Principle

Abstract Automatic pressure regulating valve is the core pressure regulating element in electronic-controlled pneumatic braking system of commercial vehicle, its pressure response characteristics directly affect the real-time and rapid pressure regulation. In this paper, the influence of structural parameters of high-speed solenoid valve on its pressure response characteristics is studied. By analyzing the working principle and structure of high-speed solenoid valve, the mathematical model was established by AMESim. Through the combination of simulation and experiment the correctness of the model is verified. Finally, according to the influence law of key structural parameters in high-speed solenoid valve on the pressure response characteristics of automatic pressure regulating valve, a set of optimized parameters are obtained to realize the improvement and optimization of the pressure response characteristics of the automatic pressure regulating valve.

Application of Wavelet Packet Energy Spectrum in Micro Motor Fault Diagnosis

2013 ◽  
Vol 726-731 ◽  
pp. 3159-3162
Author(s):  
Sheng Yi Chen ◽  
Gui Tang Wang ◽  
Shou Lei Sun ◽  
Qiang Zhou
Keyword(s):  
Fault Diagnosis ◽  
Energy Spectrum ◽  
Frequency Band ◽  
Wavelet Packet ◽  
Reconstruction Algorithm ◽  
Mechanical Equipment ◽  
Vibration Signals ◽  
Band Energy ◽  
Status Information ◽  
Frequency Band Energy

To diagnosis vibration signals of micro motor in several different fault types a method based on wavelet packet energy spectrum is presented, the energy on each Sub-frequency band, which are Calculated by Wavelet packet decomposition and reconstruction algorithm, are used to normalization process.Under both circumstances of normal working and unmoral working of mechanical equipment,there exist evident differences among the Sub-frequency band energy after the decomposition of wavelet packet, which energy contains a wealth of micro motor running status information and the eigenvectors is structured by the Sub-frequency band energy spectrum can establish energy and Fault mapping relationship.The preliminary experimental results show that it is effective to use the wavelet packet-energy spectrum in micro motor fault diagnosis .

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