Dissertation > Excellent graduate degree dissertation topics show

Study on Repeated Blind Separation of Independent Component Analysis and Its Application in Mechanical Fault Diagnosis

Author: HuangLiKun
Tutor: LengYongGang
School: Tianjin University
Course: Mechanical Manufacturing and Automation
Keywords: Independent Component Analysis Blind Source Separation Feature Extraction Heavy blind separation Mechanical fault diagnosis
CLC: TH165.3
Type: Master's thesis
Year: 2010
Downloads: 96
Quote: 1
Read: Download Dissertation

Abstract


Independent component analysis (independent component analysis, ICA) is the end of the last century developed a new signal processing method . It belongs to a special method of blind source separation method is widely used in mechanical vibration signal processing , biomedical signal processing, communication , display , signal processing , speech signal processing and other fields , and achieved good results . In short , independent component analysis functions are multiple source signal linear optimization algorithm by a mixture of mixed-signal decomposition . Assuming that the source signals are independent of each other and individually extracted from the source signal by means of a specific optimization algorithm based on blind source separation . ICA evolved by blind source separation and it is also known as the blind separation . ICA good signal feature extraction , a weak signal extraction utility . The topic of the ICA knowledge , principles, applications, and methods are described in detail to illustrate the possibility of ICA features , and through the idealized simulation experiments to verify its feasibility . Any method has its advantages and disadvantages , independent component analysis is no exception . Advantages should be inherited disadvantage should be innovative . This topic is a drawback for independent component analysis method ( number of channels can not be less than the number of source signals ) tentative breakthrough study , heavy blind separation methods (Re-ICA) and has been successful . In this study, independent component analysis virtual channel based on spectral analysis to be combined with the most classic frequency domain analysis method , in order to achieve the increase in the number of measurement channels , independent component analysis . The method and is not departing from the essence of the ICA , but to some extent overcome the shortcomings of the above ICA . Through simulation and practical application , this study prove the feasibility of this innovative approach , and hope that the results of research projects to promote the application to other areas .

Related Dissertations

  1. Research on Automatic Detection Algorithm for Substructure Distress of Highway Pavement Based on SVM,U418.6
  2. ISAR Imaging Simulation of Space Targets and Target Recognition Based on ISAR Images,TN957.52
  3. Research on Feature Extraction and Classification of Pulse Waveform for Cholecystitis and Nephrotic Syndrome Diagnosis,TP391.41
  4. Application of Q-Learning in the Content-Based Image Retrieval Technology,TP391.41
  5. Research on Transductive Support Vector Machine and Its Application in Image Retrieval,TP391.41
  6. Research on Feature Extraction and Classification of Tongue Shape and Tooth-Marked Tongue in TCM Tongue Diagnosis,TP391.41
  7. Research on Visual Measurement for Spacecraft Rendezvous and Approach,TP391.41
  8. Research on the Image Real-Time Acquisition, Storage and Image Processing System,TP391.41
  9. Feature Extraction, Selection and Combination in Lipreading,TP391.41
  10. Multi-currency Notes Technology Research and Implementation,TP391.41
  11. The Research on Paper Currency Classification Method Based on Harr-Like Feature and Minimal Ball Including Samples,TP391.41
  12. Pavement Distress Recognition Based on Image,TP391.41
  13. Research on Visual Detection and Tracking of Mobile Robots,TP242.62
  14. Research on Fusion Algorithm of Hyper Spectral and High Spatial Resolution Remote Sensing Image,TP751
  15. An Approach for Identifying a Plant Resistance Gene Based on the Random Forest,Q943
  16. Tobacco Diseases Auto-Recognition Research Based on Image Processing Technology,S435.72
  17. Research on Nondestructive Detection Technology for External Qualities of Papayas Based-on Vision,S667.9
  18. Research on Identification System of Cashmere and Wool Fiber,TS101.921
  19. Research for Infrared Image Target Identification and Tracking Technology,TP391.41
  20. The Compression and Fusion Technique Research of Underwater Target Feature,TN911.7
  21. Research of Diagnosing Cucumber Diseases Based on Hyperspectral Imaging,S436.421

CLC: > Industrial Technology > Machinery and Instrument Industry > Machinery Manufacturing Technology > Flexible manufacturing systems and flexible manufacturing cell > Fault diagnosis and maintenance
© 2012 www.DissertationTopic.Net  Mobile