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Gearbox Fault Diagnosis System Based on DSP and Hierarchical Temporal Memory

Author: GaoYang
Tutor: PanHongXia
School: University of North
Course: Pattern Recognition and Intelligent Systems
Keywords: Gearbox DSP Embedded data processing Hierarchical timing memory Fault Diagnosis
CLC: TH165.3
Type: Master's thesis
Year: 2011
Downloads: 113
Quote: 2
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Abstract


The gear box is the key components widely used in machinery and equipment , real-time monitoring and fault diagnosis of gearbox has a significant economic and security implications for industrial production . The gearbox as the research object , using the DSP processor developed an on-line monitoring and diagnosis system , diagnostic identification and stratification the timing memory algorithm is applied to the common failure of the gearbox , designed to detect the gearbox fault diagnosis use of effects. Embedded fault diagnosis system based on embedded hardware platforms , signal acquisition , data processing and feature extraction , fault classification and recognition integration in one run on embedded hardware platforms , can achieve automatic fault diagnosis and means of communication . TI's DSP - TMS320F2812 as the core processor and integrated collection and communication module circuit . The system can be achieved analog acquisition, digital input and output and speed measurement function , but also has Ethernet communication , GSM network communications and CAN bus communication function . In order to achieve online data processing system embedded DSP-based FIR digital filter , FFT power spectrum, refined spectral analysis , Hilbert envelope processing algorithms and wavelet analysis . Finally, the characteristics of fault diagnosis extraction function is also embedded DSP Gearbox Fault Feature automatic extraction . This paper introduces the principle and structure of the hierarchical the timing memory ( HTM ) algorithm , algorithm testing experimental basis and gearbox fault diagnosis . Fusion experiment gearbox plurality of measurement points extracted feature quantity , and transformed into a bitmap format to meet the input requirements of the HTM , and then design an HTM region to carry out the various conditions of the input bitmap mode for learning . When the HTM regional input bitmap to the conditions stable sparse representation , calculate the area of conditional probability matrix to achieve fault diagnosis . The system uses VC prepared the hierarchical timing memory algorithm , combined with the front-end DSP diagnostic module to become a complete fault diagnosis system . Experimental results show that the system can accurately diagnose the fault , and the use of hierarchical timing memory algorithm system with online learning, the advantages of multi-sensor fusion and real - time prediction .

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CLC: > Industrial Technology > Machinery and Instrument Industry > Machinery Manufacturing Technology > Flexible manufacturing systems and flexible manufacturing cell > Fault diagnosis and maintenance
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