Research on the Fault Diagnosis of Mechanical Equipment Vibration System Based on Expert System

2018 ◽  
Author(s):  
Yun Wang
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Mechanical Equipment ◽  
Vibration System

A Fault Diagnosis Expert System for Building Chillers

2017 ◽  
Vol 11 (4) ◽  
pp. 270
Author(s):  
C. N. Tan ◽  
C. F. Tan ◽  
M. A. Abdullah
Keyword(s):  
Fault Diagnosis ◽  
Expert System

scholarly journals A Novel Domain Adaptation-Based Intelligent Fault Diagnosis Model to Handle Sample Class Imbalanced Problem

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3382
Author(s):  
Zhongwei Zhang ◽  
Mingyu Shao ◽  
Liping Wang ◽  
Sujuan Shao ◽  
Chicheng Ma
Keyword(s):  
Fault Diagnosis ◽  
Domain Adaptation ◽  
Class Imbalance ◽  
Rolling Bearing ◽  
Industrial Applications ◽  
Mechanical Equipment ◽  
Reliable Operation ◽  
Cross Domain ◽  
Geometric Difference ◽  
Model Generalization

As the key component to transmit power and torque, the fault diagnosis of rotating machinery is crucial to guarantee the reliable operation of mechanical equipment. Regrettably, sample class imbalance is a common phenomenon in industrial applications, which causes large cross-domain distribution discrepancies for domain adaptation (DA) and results in performance degradation for most of the existing mechanical fault diagnosis approaches. To address this issue, a novel DA approach that simultaneously reduces the cross-domain distribution difference and the geometric difference is proposed, which is defined as MRMI. This work contains three parts to improve the sample class imbalance issue: (1) A novel distance metric method (MVD) is proposed and applied to improve the performance of marginal distribution adaptation. (2) Manifold regularization is combined with instance reweighting to simultaneously explore the intrinsic manifold structure and remove irrelevant source-domain samples adaptively. (3) The ℓ2-norm regularization is applied as the data preprocessing tool to improve the model generalization performance. The gear and rolling bearing datasets with class imbalanced samples are applied to validate the reliability of MRMI. According to the fault diagnosis results, MRMI can significantly outperform competitive approaches under the condition of sample class imbalance.

Intelligent fault diagnosis of mechanical equipment under varying working condition via iterative matching network augmented with selective Signal reuse strategy

2020 ◽  
Vol 57 ◽  
pp. 400-415
Author(s):  
Kaiyu Zhang ◽  
Jinglong Chen ◽  
Tianci Zhang ◽  
Shuilong He ◽  
Tongyang Pan ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Working Condition ◽  
Mechanical Equipment ◽  
Intelligent Fault Diagnosis ◽  
Matching Network

Application of expert system techniques to fault diagnosis

1984 ◽  
Vol 29 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Hiromitsu Kumamoto ◽  
Kenji Ikenchi ◽  
Koichi Inoue ◽  
Ernest J. Henley
Keyword(s):  
Fault Diagnosis ◽  
Expert System

General Fault Monitoring and Diagnosis Expert System Based on Fault Tree and Multi-Sensor Information

2011 ◽  
Vol 121-126 ◽  
pp. 4481-4485
Author(s):  
Ai Yu Zhang ◽  
Xiao Guang Zhao ◽  
Lei Zhang
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Expert Knowledge ◽  
Sensor Failure ◽  
Fault Trees ◽  
Intelligent Algorithms ◽  
Monitoring And Diagnosis ◽  
Backward Reasoning ◽  
Fault Monitoring ◽  
Sensor Information

Due to the limited generality of traditional fault diagnosis expert system and its low accuracy of extracting failure symptoms, a general fault monitoring and diagnosis expert system has been built. For different devices, users can build fault trees in an interactive way and then the fault trees will be saved as expert knowledge. A variety of sensors are fixed to monitor the real-time condition of the device and intelligent algorithms such as wavelet transform and neural network are used to assist the extraction of failure symptoms. On the basis of integration of multi-sensor failure symptoms, the fault diagnosis is realized through forward and backward reasoning. The simulation diagnosis experiments of NC device have shown the effectiveness of the proposed method.

A Knowledge-Based Expert System Based on OKRA Fault Diagnosis in Industrial Process

1992 ◽  
Vol 25 (28) ◽  
pp. 263-265
Author(s):  
Yan Yang
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Industrial Process ◽  
Knowledge Based

Graphical Fault Diagnosis Expert System of CNC Machine Tool Based on B/S

2014 ◽  
Vol 945-949 ◽  
pp. 1707-1712
Author(s):  
Bin Shen ◽  
Shu Yu Zhao ◽  
Jia Hai Wang ◽  
Juergen Fleischer
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Machine Tool ◽  
Case Based Reasoning ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Rule Based ◽  
Detailed Case ◽  
Case Based ◽  
Remote Fault Diagnosis

Based on the authors previous work of developing an expert system for fault diagnosis of CNC machine tool, this paper studied the theory and method of CNC remote fault diagnosis expert system based on B/S, and presents schema and structure of the expert system in detailed. Case based reasoning is used for the multi-alarm diagnosis, and rule based reasoning is used for single-alarm diagnosis. At last fault diagnosis expert system was designed and developed making use of C# and ASP.NET.

Sign in / Sign up

Export Citation Format

Share Document