Mechanical Diagnosis Based on Similarity Extraction of Time Series

Chun Jie Lv; Yong Yu Yao

doi:10.4028/www.scientific.net/AMR.753-755.2159

Paper Titles

Signal Acquisition and Process on Tower Crane Safety Control System
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Design of Monitor and Control System of Screw Pump Oil Production Based on ATT7022
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Measurement of Linearly Polarized Light Rotation Applied in Atomic Magnetometer
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Double Interpolation Method in Time-Interval Measurement
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Mechanical Diagnosis Based on Similarity Extraction of Time Series
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Machine Vision Inspection of In Vitro Diagnostic Kits
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Measurement and Protection of Human Body Electrostatic of Mobile User Terminal
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Research on Intelligent Fault Diagnosis Methods of Armored Vehicles Electrical System
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Analysis and Design of On-Line Monitoring and Fault Prewarning System for Mine Ventilator
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 753-755Mechanical Diagnosis Based on Similarity...

Mechanical Diagnosis Based on Similarity Extraction of Time Series

Abstract:

The intelligent diagnosis emphasizes the processing method of knowledge of the historical data. The capability of an intelligent diagnosis system depends on the knowledge possessed by the system, especially by the specific knowledge in application. Currently, most of the important equipment have their own the inspection systems. With the help of these systems, plenty of historical data can be collected in real time. This paper discusses the possibility of the application of similarity extraction and pattern discovery of time series in fault diagnosis by using these historical data, presents the method of time series feature extraction and pattern matching, and advances the possibility of data clustering and pattern discovery based on dimension reduction.

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Periodical:

Advanced Materials Research (Volumes 753-755)

Pages:

2159-2163

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.753-755.2159

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Online since:

August 2013

Authors:

Chun Jie Lv, Yong Yu Yao

Keywords:

Dimension Reduction, Fault Diagnosis, Historical Data, Similarity

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