scholarly journals Vibration Test Measures for Pump Fault Diagnosis

2021 ◽  
Vol 5 (6) ◽  
pp. 6-10
Author(s):  
Lian Shi ◽  
Lei Liu
Keyword(s):  
Fault Diagnosis ◽  
Industrial Production ◽  
Mechanical Vibration ◽  
Vibration Test ◽  
Vibration Intensity ◽  
Calculating Method ◽  
Proper Functioning ◽  
Vibration Measuring ◽  
Detecting Method

The vibration measuring standard for compound machinery utilized in modern industrial production will be employed for the application of detecting technologies. The vibration intensity can be obtained by selecting the detecting method to obtain the speed of mechanical vibration, and technicians can examine whether the vibrating machinery is in a proper functioning state based on the value of vibration intensity, allowing for thorough fault diagnosis. In order to provide useful diagnosis ideas for technicians, this study examines the measurement of mechanical vibration and investigates the calculating method of mechanical vibration intensity.

A Fault Diagnosis Method for the Roller-Marks in Offset Printing Machine Based on Texture Recognition

2012 ◽  
Vol 262 ◽  
pp. 361-366
Author(s):  
Zhuo Fei Xu ◽  
Hai Yan Zhang ◽  
Ling Hui Ren
Keyword(s):  
Fault Diagnosis ◽  
High Speed ◽  
Solution Method ◽  
Offset Printing ◽  
Texture Recognition ◽  
Defect Image ◽  
Diagnosis Method ◽  
The Difference ◽  
Detecting Method ◽  
Printing Machine

Roller-mark is a common problem in offset printing and its solution method is important for printing. A new detecting method of texture analysis was given in this paper. In this study, printing image was acquired with high-speed CCD. Compared the difference between printing image and standard image, a defective image was obtained. Then the reason of roller-marks was given by the texture recognition of defect image. Finally, experiments were taken to prove the feasibility and effectiveness of this new method for the roller-marks diagnosis in the offset printing machine.

FAULT DIAGNOSIS IN A PROCESS EXPERIMENTAL CONTROL SYSTEM WITH UNKNOWN FACTORS

2008 ◽  
Vol 07 (01) ◽  
pp. 151-155 ◽  
Author(s):  
AKIRA INOUE ◽  
MINGCONG DENG
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Experimental System ◽  
Detection Problem ◽  
Experimental Control ◽  
Blind System Identification ◽  
Experimental Process ◽  
Identification Approach ◽  
Simulation Results ◽  
Detecting Method

A fault detection problem in a process control experimental system with unknown factors is presented in this paper. The fault detecting method is based on blind system identification approach. The experimental system actuator output includes unknown dynamics and unknown fault signal. By using the fault detecting method, the fault signal is detected. Simulation results for the experimental process are presented to show the effectiveness.

Signal Acquisition and Analysis of Shaft Unbalance Vibration Test

2014 ◽  
Vol 945-949 ◽  
pp. 1090-1093
Author(s):  
Hai Peng Zhang ◽  
Hong Wu Chen ◽  
Bin Hu ◽  
Cheng Tian
Keyword(s):  
Fault Diagnosis ◽  
Time Domain ◽  
Time Domain Analysis ◽  
Rotating Machinery ◽  
Vibration Test ◽  
Signal Acquisition ◽  
Analysis Method ◽  
Characteristic Parameters ◽  
Test Platform ◽  
The Time Domain

This paper simulated the unbalance vibration conditions by the vibration test platform, measuring some common characteristic parameters of unbalance vibration fault diagnosis. This paper chose the time-domain analysis method, processing the characteristic parameters of the test, so as to achieve the purpose of vibration diagnosis. Through a large number of experimental data, this paper verified the feasibility and the effectiveness of the proposed approach to the unbalance fault diagnosis. The method proposed in this paper not only can be applied to unbalance fault diagnosis, but also can be promoted to apply to the fault diagnosis of other rotating machinery.

Design of Mechanical Vibration Test System Based on Virtual Instrument Technology

2011 ◽  
Vol 322 ◽  
pp. 291-295 ◽  
Author(s):  
Hua Zhao
Keyword(s):  
Data Acquisition ◽  
Virtual Instrument ◽  
Mechanical Vibration ◽  
Domain Analysis ◽  
Test System ◽  
Acquisition Time ◽  
Vibration Test ◽  
Time Frequency ◽  
Development Platform ◽  
Instrument Technology

With piezoelectric acceleration sensor, charge voltage filter amplifier, data acquisition card, PC and vibration experiment table for hardware development platform, and LABVIEW for software development platform, virtual instrument technology was applied to the design of mechanical vibration test system. This test system mainly consists of data acquisition, time domain analysis, amplitude domain analysis, frequency domain analysis, time-frequency analysis module. Experimental results indicate: The system not only can perform real-time data acquisition of multiple channels signal, waveform display, data storage, signal analysis, playback measurement and output printing etc, but also has good expansibility, high speed, high accuracy and friendly interface. It is suitable for engineering personnel and laboratory use.

Fault Diagnosis of Wind Turbines Based on Noise Detection

2013 ◽  
Vol 718-720 ◽  
pp. 405-408
Author(s):  
Jing Cheng ◽  
Wei Qing Wang ◽  
Shan He
Keyword(s):  
Fault Diagnosis ◽  
Engineering Application ◽  
Noise Measurement ◽  
Measurement Technology ◽  
Noise Detection ◽  
Vibration Detection ◽  
Technology Standard ◽  
Testing Technology ◽  
Diagnosis Method ◽  
Detecting Method

Aiming at backward current situation of testing technology and fault diagnosis technology of wind power generation in China, a fault diagnosis method based on based on noise detection is put forward. Studied IEC 61400-11 noise measurement technology standard, this paper elaborates the noise detecting method, analyzes the feasibility and diagnostic steps of fault diagnosis, proposes fault signal extracting method based on wavelet analysis. According to analysis and simulation, it is shown that noise measurement is earlier than vibration detection, and the fault signal can be extracted effectively, so it has important value for engineering application.

Research on the Distributings of Vibration Sensors for Fault Diagnosis in Axial Piston Pump

2012 ◽  
Vol 472-475 ◽  
pp. 1155-1159
Author(s):  
Sheng Qiang Wu ◽  
Cai Qin Liu ◽  
Er Ling Cao
Keyword(s):  
Experimental Data ◽  
Fault Diagnosis ◽  
Research Result ◽  
Mechanical Vibration ◽  
Strong Support ◽  
Piston Pump ◽  
Axial Piston Pump ◽  
Vibration Sensors ◽  
Axial Piston ◽  
Feature Frequency

Considering that the distributings of sensors will affect the fault diagnosis results directly, how to distribute vibration sensors for fault diagnosis in axial piston pump are researched. The corresponding feature frequency bands of various faults are analyzed, effects of collecting signals are compared in differrent fixings of vibration sensors, placements scheme of the sensors is proposed. Combined with the experimental data, the best distributings of vibration sensors is obtained. Research result provide a strong support in the pump monitoring and fault diagnosis field and reference in other complex mechanical vibration fault diagnosis field.

Shaft Vibration Signal Denoising Based on Wavelet Analysis

2013 ◽  
Vol 300-301 ◽  
pp. 1110-1113
Author(s):  
Tie Qiang Sun ◽  
Rong Liu ◽  
Zhi Qi Qiu
Keyword(s):  
Fault Diagnosis ◽  
Condition Monitoring ◽  
Wavelet Packet ◽  
Mechanical Vibration ◽  
Vibration Signal ◽  
Signal Denoising ◽  
Axial Vibration ◽  
Denoising Method ◽  
Original Source ◽  
Separation Result

In actual , there exist inevitably a lot of interference from neighbor machine and noise from surrondings in mechanical vibration signal measured by sensor ,which is disadvantageous for condition monitoring and fault diagnosis. In order to eliminate the axial vibration signal in the noise, using Wavelet packet denoising method in this article, Emulating experiment s were carried out under the MATLAB software ,original signals adopted vibration impulsion signal produced by vice position of faulty bear. Separation result s confirm this method successfully ext ract original source ,efficiently removes noise.

Machinery fault diagnosis based on time–frequency images and label consistent K-SVD

2017 ◽  
Vol 232 (7) ◽  
pp. 1317-1330
Author(s):  
HD Yuan ◽  
J Chen ◽  
GM Dong
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Image Classification ◽  
Mechanical Vibration ◽  
Gray Level ◽  
Time Frequency ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Occurrence Matrix ◽  
Machinery Fault Diagnosis

Wavelet time–frequency analysis has been widely used for machinery fault diagnosis. Mechanical vibration signals can be converted to time–frequency images using wavelet transform, so machinery fault diagnosis can be transformed to the problem of image classification. Label consistent K-SVD algorithm has been proven to be effective in image classification, which incorporates a label consistent term namely discriminative sparse code error into the objective function. Therefore, in this paper, a novel bearing fault diagnosis method based on wavelet time–frequency image and label consistent K-SVD is proposed. Firstly, continuous wavelet transform is utilized to generate wavelet time–frequency images that can fully reflect bearing fault characteristics. Then texture feature extraction based on gray level co-occurrence matrix is implemented on the wavelet time–frequency images. Finally, label consistent K-SVD is conducted for classification of the time–frequency images, and thus bearing fault diagnosis is realized. The experiment results show that the texture features based on gray level co-occurrence matrix of wavelet time–frequency images can effectively extract the fault characteristics of rolling bearings, and label consistent K-SVD performs better than other classification methods based on dictionary learning under the same parameters.

The Study of Vibration Diagnosis Method for GIS

2013 ◽  
Vol 295-298 ◽  
pp. 2429-2432
Author(s):  
Pei Ding ◽  
Zhen Hua Yan ◽  
Fei Yue Ma ◽  
Liang Zhang ◽  
Jun Hao Li ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Field Test ◽  
Detection Method ◽  
Detection System ◽  
Vibration Signal ◽  
Normal Operation ◽  
Vibration Test ◽  
Test Results ◽  
Vibration Detection ◽  
Diagnosis Method

Gas insulated switchgear (GIS) will generate vibration during normal operation for the electromagnetic force. There will be generate abnormal vibration when the contacts are undesirable, the guide rod stressed unevenness. Therefore, it can be effective in fault diagnosis of this machineries through the vibration test of GIS in field. The vibration detection method of GIS equipment in field is studied in this paper, the composition of the vibration detection system is described. The field test has been done using vibration detection system and the test results show that through the vibration signal detected from the GIS equipment, the vibration characteristics of GIS can be clarified and make the fault diagnosis effectively.

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