Research on Fault Diagnosis Based on Virtual Prototype Technology of Mechanical System

2021 ◽  
Author(s):  
Wen Chen ◽  
Zongde Lin
Keyword(s):  
Fault Diagnosis ◽  
Mechanical System ◽  
Virtual Prototype ◽  
Virtual Prototype Technology

Motion Analysis & Simulation of Cloth Rolling Machine

2012 ◽  
Vol 157-158 ◽  
pp. 41-44
Author(s):  
Cong Min Wu ◽  
Qing Zhang
Keyword(s):  
Mechanical System ◽  
Engineering Design ◽  
Motion Analysis ◽  
System Performance ◽  
Simulation Analysis ◽  
Virtual Prototype ◽  
Adams Software ◽  
Virtual Prototype Technology

Virtual prototype technology as a new design means, is applied in engineering design and mechanical system performance more and more. In this paper, the change rule of the speed of cloth rolling machine was inferred according to the work principle of the machine. And then the model of the cloth rolling machine was designed, and imported it into the ADAMS software. At last, have a simulation analysis of the cloth rolling machine with the ADAMS software. From the simulation analysis can know that the characteristic of motion of the cloth rolling machine is reasonable.

Virtual Prototype Modeling of Biped Robot with Heterogeneous Legs

2013 ◽  
Vol 307 ◽  
pp. 117-120
Author(s):  
Hua Long Xie ◽  
Fei Li ◽  
Ning Weng ◽  
Zhong Qi Sheng
Keyword(s):  
Control System ◽  
Mechanical System ◽  
Biped Robot ◽  
Virtual Prototype ◽  
Matlab Simulink ◽  
Environment Perception ◽  
Virtual Prototypes ◽  
Virtual Prototype Technology ◽  
And Control

Biped robot with heterogeneous legs (BRHL) can simulate amputees dressed with intelligent above/knee (A/K) prosthesis and can be used to evaluate intelligent prosthesis (IP) performance. First the concept of virtual prototype technology and BRHL is introduced. Then virtual prototypes of BRHL mechanical system, ground environment, perception and control system are established. In the end, the continuously walking simulation of BRHL based on virtual prototype is done. The research indicates that virtual prototype modeling based on Pro/E, ADAMS and MATLAB/Simulink is feasible.

Analysis of Influence Parameters of the Project Ribbed Bar Machining Quality

2013 ◽  
Vol 328 ◽  
pp. 426-431 ◽  
Author(s):  
Xi Jian Zheng ◽  
Zhong Nan Wang ◽  
Lei Ma
Keyword(s):  
Mechanical System ◽  
Dynamic Simulation ◽  
Virtual Prototype ◽  
Flexible Coupling ◽  
Machining Quality ◽  
Steel Bar ◽  
Rigid Model ◽  
Virtual Prototype Technology

This paper presents the method of calculating roller spacing and press amount of straightening roll. based on rigid-flexible virtual prototype technology, the entities model of straightening block was established by Pro/E, then it was imported into the ADAMS environment and constraints were added to create a rigid model, the model neutral file generated by ANSYS, thereby the rigid-flexible coupling virtual prototype was established. The distance of the point in the steel-bar relative to the end in Y direction is obtained through simulation, the acceleration curve and the range of roller spacing and press amount which consist with theory and the straightness of the ribbed bar after being straightened are obtained, which are reference to the dynamic simulation of the same complicated mechanical system and the theory of steel-bar straightening.

Research and Application on Fault Simulation Technology Based on Virtual Prototype

2012 ◽  
Vol 184-185 ◽  
pp. 389-392
Author(s):  
Yan Feng Yang ◽  
Jian Zheng ◽  
Chang Chun Di
Keyword(s):  
Dynamic Response ◽  
Mechanical System ◽  
Fatigue Failure ◽  
Fault Injection ◽  
Fault Simulation ◽  
Virtual Prototype ◽  
Research Subject ◽  
Simulation Technology ◽  
Virtual Prototype Technology ◽  
Injection Technology

Aiming at the present application of fault simulation technology based on virtual prototype, virtual prototype technology and fault injection technology were studied and analyzed, and the fault injection technology was improved. Taking a mechanical system as research subject, the mechanism of fault caused by a spring's fatigue failure was analyzed. The system's dynamic response of different fault phases was analyzed based on the system's virtual prototype. Finally, the occasion of fault occurrence, spring's stiffness dropping to between 90% and 91% of primary value, is confirmed. The simulation result provides characteristic information for preventing and diagnosing fault.

Research on Internet-Based Reconfigurable Distance Mechanical System Fault Diagnosis

2011 ◽  
Vol 52-54 ◽  
pp. 109-114
Author(s):  
Yun Jie Xu
Keyword(s):  
Fault Diagnosis ◽  
Mechanical System ◽  
High Speed ◽  
Structural Model ◽  
Component Technology ◽  
The Internet ◽  
Diagnostic Systems ◽  
Diagnosis System ◽  
J2ee Framework ◽  
Fault Diagnosis System

In order to meet requirements of increasingly high-speed, large and intelligent mechanical equipments on fault diagnosis, the Internet-based reconfigurable mechanical system fault diagnosis program was presented. The overall structure and networking schema of distance mechanical fault diagnosis system were analyzed, and the distance fault diagnosis network model based on J2EE framework was also described. The structural model and reconfigurable manner of the reconfigurable distance diagnosis system was provided, which used CORBA component technology to achieve reconfiguration. The detail steps of system that take some type of diesel engine as diagnosis object was described, and the intelligent diagnosing methods were also researched. The Internet-based fault diagnosis technology effectively improves the efficiency and accuracy of diagnostic systems.

ON-LINE PERFORMANCE ASSESSMENT AND FAULT DIAGNOSIS OF MECHANICAL SYSTEMS

2015 ◽  
Vol 39 (3) ◽  
pp. 705-715 ◽  
Author(s):  
Shang-Liang Chen ◽  
Yin-Ting Cheng ◽  
Hsien-Cheng Liu ◽  
Yun-Yao Chen
Keyword(s):  
Fault Diagnosis ◽  
Performance Assessment ◽  
Mechanical System ◽  
High Speed ◽  
Mechanical Performance ◽  
Wavelet Packet ◽  
Principal Component ◽  
Spindle Motor ◽  
Diagnostic Model ◽  
On Line

This study integrates sensors, signal capture equipment, industrial computers and machinery health check-up software to develop an On-line Performance Assessment and Fault Diagnosis of Mechanical System, helping engineers predict mechanical conditions. Physical quantities captured by the sensors is utilized to process physical signals, and the Wavelet Packet Energy method is used for the feature extraction of non-stationary signals in coordination with the Principal Component Analysis for feature selection. This study establishes On-line Performance Assessment and Fault Diagnosis of Mechanical System based on Discriminant Analysis which is able to immediately determine the mechanical performance. When abnormal mechanical conditions occur, Bayesian Network will be activated to construct error diagnostic model and determine possible causes of error or malfunction of the machinery. Finally, the system is applied to the fan motor, high-speed spindle motor and AC motor of the machine tool. Experimental results show that the theory can effectively diagnose mechanical performance remarkable with an accuracy rate of 92.50% or higher.

scholarly journals Comparisons of different deep learning-based methods on fault diagnosis for geared system

2019 ◽  
Vol 15 (11) ◽  
pp. 155014771988816 ◽  
Author(s):  
Bing Han ◽  
Xiaohui Yang ◽  
Yafeng Ren ◽  
Wanggui Lan
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Mechanical System ◽  
Network Model ◽  
Learning Theory ◽  
Neural Network Model ◽  
Deep Neural Network ◽  
Gear Fault

The running state of a geared transmission system affects the stability and reliability of the whole mechanical system. It will greatly reduce the maintenance cost of a mechanical system to identify the faulty state of the geared transmission system. Based on the measured gear fault vibration signals and the deep learning theory, four fault diagnosis neural network models including fast Fourier transform–deep belief network model, wavelet transform–convolutional neural network model, Hilbert-Huang transform–convolutional neural network model, and comprehensive deep neural network model are developed and trained respectively. The results show that the gear fault diagnosis method based on deep learning theory can effectively identify various gear faults under real test conditions. The comprehensive deep neural network model is the most effective one in gear fault recognition.

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