The Integrated Test Platform Design of Wireless Communication Equipment Based on the Circuit Analysis and Fault Diagnosis

2015 ◽  
Vol 738-739 ◽  
pp. 1225-1230
Author(s):  
Da Wei Wang ◽  
Wei Zhang ◽  
Chuan Fei Qiu ◽  
Jian Hua Tu ◽  
Quan Zhi Zhou
Keyword(s):  
Fault Diagnosis ◽  
Wireless Communication ◽  
Signal Acquisition ◽  
Key Technology ◽  
Detection Techniques ◽  
Detection Point ◽  
Test Platform ◽  
Equipment Type ◽  
Software And Hardware ◽  
Communication Equipment

Aiming at the study of key technology of the integrated test platform of wireless communication equipment, this paper consists of several technology contents, mainly including criterion of detection, fault diagnosis evaluation, equipment type matching, optimization of circuit detection point, signal acquisition and so on. Combined with the intelligent circuit detection techniques and the development of software and hardware, the specific testing and repairing techniques of the wireless communication equipment are given to realize the steps, methods and processes, and the testing platform united with technology verification and software and hardware is developed and achieved.

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 and Implementation of Knowledge System of Wireless Communication Equipment Fault Diagnosis

2014 ◽  
Vol 945-949 ◽  
pp. 1108-1111 ◽  
Author(s):  
Yu Yang
Keyword(s):  
Fault Diagnosis ◽  
Wireless Communication ◽  
Domain Knowledge ◽  
Prototype System ◽  
Task Knowledge ◽  
Development Tool ◽  
Knowledge Reasoning ◽  
Diagnosis Model ◽  
Sql Server 2005 ◽  
Communication Equipment

Through analyzing the fault characteristics of the wireless communication equipment and according to the object oriented method, the fault diagnosis model based on knowledge for wireless communication equipment fault characteristics was designed. In order to expand and maintenance knowledge conveniently, and realize the reuse of knowledge, the fault diagnosis model were modeled in the way of domain knowledge, reasoning knowledge and task knowledge according to CommonKADS ideology. In the end VC++6.0 and SQL Server 2005 were used as the development tool and database, the development of prototype system was realized.

scholarly journals Intelligent Fault Diagnosis and Forecast of Time-Varying Bearing Based on Deep Learning VMD-DenseNet

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7467
Author(s):  
Shih-Lin Lin
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Fault Diagnosis ◽  
Vibration Signal ◽  
Image Feature ◽  
Signal Acquisition ◽  
Time Varying ◽  
Intelligent Fault Diagnosis ◽  
Image Block ◽  
Wide Range

Rolling bearings are important in rotating machinery and equipment. This research proposes variational mode decomposition (VMD)-DenseNet to diagnose faults in bearings. The research feature involves analyzing the Hilbert spectrum through VMD whereby the vibration signal is converted into an image. Healthy and various faults show different characteristics on the image, thus there is no need to select features. Coupled with the lightweight network, DenseNet, for image classification and prediction. DenseNet is used to build a model of motor fault diagnosis; its structure is simple, and the calculation speed is fast. The method of using DenseNet for image feature learning can perform feature extraction on each image block of the image, providing full play to the advantages of deep learning to obtain accurate results. This research method is verified by the data of the time-varying bearing experimental device at the University of Ottawa. Through the four links of signal acquisition, feature extraction, fault identification, and prediction, a mechanical intelligent fault diagnosis system has established the state of bearing. The experimental results show that the method can accurately identify four common motor faults, with a VMD-DenseNet prediction accuracy rate of 92%. It provides a more effective method for bearing fault diagnosis and has a wide range of application prospects in fault diagnosis engineering. In the future, online and timely diagnosis can be achieved for intelligent fault diagnosis.

Design of Automatic Test Platform for the Gyroscope Group Based on Pertinence Matrix

2014 ◽  
Vol 556-562 ◽  
pp. 2567-2570
Author(s):  
He Jia Li ◽  
Xue Wang ◽  
Hai Feng Xu ◽  
Cheng Yao ◽  
Wen Ju Gao ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Performance Test ◽  
Gun Control ◽  
Automatic Test ◽  
Optimal Test ◽  
Fault Dictionary ◽  
Dependency Matrix ◽  
Optimal Criterion ◽  
Test Platform ◽  
Test Points

Aiming the problem of the armored vehicle's gun control system that there are many kinds of internal devices, complex fault reasons ,but no all-around and online fault diagnosis and state inspection mean, The automatic test platform for the gyroscope group with performance test and fault diagnosis for component and circuit is designed .The platform based on dependency matrix and optimal criterion of the maximum failure feature information entropy optimize test points ,choose optimal test points design. Performance test module is created and provides test result information for fault dictionary in fault diagnosis module. Automatic test platform is able to locate the circuit component failure.The platform is tested by actual vehicle experiment, and the results prove the reliability and validity of the platform.

Research on the Equipment Overhaul Management System

2012 ◽  
Vol 198-199 ◽  
pp. 1006-1011
Author(s):  
Jia Ni Liu ◽  
Yuan Li ◽  
Le Chen ◽  
Jian Bin Sun ◽  
Xin Shi
Keyword(s):  
Information Technology ◽  
Management System ◽  
System Construction ◽  
Office Staff ◽  
Key Technology ◽  
Development Platform ◽  
Satellite Positioning ◽  
Software And Hardware ◽  
Two Sides ◽  
Business Flow

Based on the demonstration of some problems exposed in the fields of PLA equipment overhaul, this paper put forward the design scheme of the equipment overhaul management system in view of information technology. It described the design objective of system, analysed system business flow, built system construction from two sides of software and hardware, and introduced the key technology and development platform for system implementation. This system has reading/encoding RFID card, photography, satellite positioning functions, which can automatically collect and transfer information during the process of the equipment overhaul. It is convenient for analysing system to office staff, and ensures the equipment overhaul expenditures was used reasonably.

Rotor Crack Detection Based on Multi-Vibration Signal Fusion Collected from the Basement of Machinery Using SVM and Statistical Characteristics Methodology

2010 ◽  
Vol 34-35 ◽  
pp. 1000-1004
Author(s):  
Xue Jun Li ◽  
K. Wang ◽  
Ling Li Jiang ◽  
T. Zhang
Keyword(s):  
Fault Diagnosis ◽  
Crack Detection ◽  
Feature Fusion ◽  
Vibration Signal ◽  
Statistical Characteristics ◽  
Support Vector ◽  
Signal Acquisition ◽  
Multiple Sensors ◽  
Signal Fusion ◽  
Diagnosis Method

As the poor generability of special sensor support frame and the inconvenience of signal acquisition in the process of common fault diagnosis for cracked rotor, a new fault diagnosis method is presented in this paper. this method takes the basement of rotor test rig as the monitoring objects and makes feature fusion for time-domain statistics of multiple sensors using SVM (support vector machine). The result of experiment showed that the method using the multi-sensor signal fusion technology collected from the basement of machinery has the advantages of better diagnostic precision for rotor crack diagnosis, furthermore, it supplies a new way for rotor fault diagnosis.

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