A Novel Signal Processing Approach for Valve Health Condition Classification of a Reciprocating Compressor with Seeded Faults Considering Time-Frequency Partitions

This study deals with a novel signal processing approach for automated valve condition classification of a reciprocating compressor with seeded faults. The classification system consists of a front end time-frequency analysis platform for the vibration signal measured, fault feature vectors for making the formidable amount of time-frequency data manageable, and a probabilistic neural network for automatic classification without the intervention of human experts. Rather than representing each time-frequency data set with one single feature vector comprising three indices, namely time, frequency, and amplitude, the time-frequency plane is further partitioned into an appropriate number of sub-regions to enhance the characteristics representation of the time-frequency data. This study shows that a flawless classification can be realized by using the proposed approach with appropriate selections of index modification method and number of time-frequency sub-regions without resorting to the removal of similar fault cases.

並列關鍵字

automated condition classification ； reciprocating compressor ； time-frequency analysis

參考文獻

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被引用紀錄

邱敬越（2015）。應用於行動終端裝置的景點智慧推薦模組〔碩士論文，淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2015.00154

Huang, S. G. (2016). 時頻分析與線性完整轉換 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU201601090

延伸閱讀

Chen, P. C. (2017). Matrix Characterization for Generalized Frequency Division Multiplexing Systems and its Applications in Low-Complexity Transceivers and Optimal Prototype Filter Designs [master's thesis, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU201701053
Masuike, H., & Ikuta, A. (2008). Statistical Signal Processing by Using the Higher-Order Correlation between Sound and Vibration and Its Application to Fault Detection of Rotational Machine. Advances in Acoustics and Vibration, 2008(), 92-98. https://doi.org/10.1155/2008/828562
Shih, Y. T. (2021). Combining Empirical Mode Decomposition with Constant Q Cepstral Coefficients and Mel-Frequency Cepstral Coefficients on Automatic Speaker Verification System [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-0209202114091450
余長霖（2012）。Application of Empirical Mode Decomposition and Multi-scale Entropy Analysis to the Roller Bearing Fault Diagnosis under Variable Rotation Speed via Order Tracking Technology〔碩士論文，國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-1903201314440023
呂霽軒、陳彥翔、吳天堯（2019）。Application of Constrained Independent Component Analysis and Empirical Mode Decomposition to Diagnose Synchronous Multiple Bearing Faults。應用聲學與振動學刊，11(1&2)，9-17。https://doi.org/10.6282/JASV.201912_11(1_2).0002

國際替代計量

A Novel Signal Processing Approach for Valve Health Condition Classification of a Reciprocating Compressor with Seeded Faults Considering Time-Frequency Partitions

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