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Gearbox Fault Diagnosis System Based On DSP And Hierarchical Temporal Memory

Posted on:2012-11-05Degree:MasterType:Thesis
Country:ChinaCandidate:Y GaoFull Text:PDF
GTID:2132330335978174Subject:Pattern Recognition and Intelligent Systems
Abstract/Summary:PDF Full Text Request
Gearbox is a key part that widely used in many mechanical equipments. Performing monitoring and fault diagnosis on gearbox plays an important role in industry security and productivity effect. In this paper, an online monitoring and diagnosis system is developed based on DSP in order to realize online diagnosis of gearbox, and a new algorithm named Hierarchial Temporal Memory (HTM) is applied on the system for testing the diagnosis performance.Using embedded system makes it easy to intergrate data acquisition, signal processing, feature extraction and fault diagnosis on embedded platfom as well as automatic fault diagnosis and many communication protocols. The system takes DSP-TMS320F2812 as the core processor. The hardware is builded by various peripheral modules of TMS320F2812, which include data acquisition of vibration signal, rotation speed signal and digital signal. The system can communicate with the upper monitor by GSM protocol, TCP/IP protocol and CAN bus. A lot of signal processing algorithms are embedded in TMS320F2812 for feature extraction of the gearbox such as FIR digital filter, power spectrum, zoom power spectrum and wavelet envelope analysis, etc. In additon, feature extraction functions are also embedded on DSP to realize automatic feature extraction of gearbox faults.This paper proposes a scheme that using Hierarchial Temporal Memory on the gearbox fault detection. First, the structure and principle of Hierarchical Temporal Memory is introduced. Then we transform the feature vector that obtained from vibration signal of six testing points on gearbox into bitmap format in order to meet the request of a HTM region. 60 sample vectors of 6 working states of gearbox are selected for training the HTM region until the region gets stable sparse distribute representation. After that, a conditional probability matrix is calculated according to the stable sparse distribute representation. In the end, using the conditional probability matrix and current input bitmap, HTM region can compute the probability of each working state. The HTM algorithm is programmed using VC2008 in personal computer, it receives the feature vector from embedded DSP system in the front end. So that all of the parts of this sysytem are integrated and can realize online gearbox fault diagnosis. Tests show that the system can diagnose gearbox faults correctly and possess capability of online study, multisensor information fusion inference and prediction.
Keywords/Search Tags:Gearbox, DSP, Embedded data processing, Hierarchical Temporal Memory, Fault diagnosis
PDF Full Text Request
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