The traditional fault diagnosis method is completely based on the fault symptom without considering failure rate,so the fault diagnosis accuracy is not ideal.To improve the correctness rate of fault diagnosis,the pape...The traditional fault diagnosis method is completely based on the fault symptom without considering failure rate,so the fault diagnosis accuracy is not ideal.To improve the correctness rate of fault diagnosis,the paper proposes a fault diagnosis method of equipment based on failure rate and fault symptom.Firstly,an algorithm for calculating the equipment failure rate is proposed based on Weibull distribution model;Secondly,the probability of fault existence is evaluated based on fault symptom;Thirdly,a new fault diagnosis model is herein presented based on fault rate and fault symptom;Finally,the method is proved to be applicable through an example.The method takes failure rate,fault mechanism,fault symptom,difficulty degree of symptom acquisition and other factors into consideration,so the fault diagnosis accuracy is improved greatly.展开更多
The technology of diagnostic symptom identification of nonlinear vibration is based on a database of a diagnostic case. This paper defines the periodic degree, quasi periodic degree, and chaotic degree of a Poincare ...The technology of diagnostic symptom identification of nonlinear vibration is based on a database of a diagnostic case. This paper defines the periodic degree, quasi periodic degree, and chaotic degree of a Poincare map, an iterated map, and adopts the image identification theory, so the three states of periodic, quasi periodic, and chaotic running states of a machine can be distinguished. It also defines the variable identity, rotating angle and spread degree. The database of diagnostic case is expressed by means of an access database. The diagnostic symptoms are identified using the difference between the Poincare maps of samples and the fault case.Finally, we demonstrate an identification system of a nonlinear vibration diagnostic symptom of large rotating machinery.展开更多
基金supported by Jiangsu Key Laboratory of Recycling and Reuse Technology for Mechanical and Electronic Products(RRME-KF1605)。
文摘The traditional fault diagnosis method is completely based on the fault symptom without considering failure rate,so the fault diagnosis accuracy is not ideal.To improve the correctness rate of fault diagnosis,the paper proposes a fault diagnosis method of equipment based on failure rate and fault symptom.Firstly,an algorithm for calculating the equipment failure rate is proposed based on Weibull distribution model;Secondly,the probability of fault existence is evaluated based on fault symptom;Thirdly,a new fault diagnosis model is herein presented based on fault rate and fault symptom;Finally,the method is proved to be applicable through an example.The method takes failure rate,fault mechanism,fault symptom,difficulty degree of symptom acquisition and other factors into consideration,so the fault diagnosis accuracy is improved greatly.
文摘The technology of diagnostic symptom identification of nonlinear vibration is based on a database of a diagnostic case. This paper defines the periodic degree, quasi periodic degree, and chaotic degree of a Poincare map, an iterated map, and adopts the image identification theory, so the three states of periodic, quasi periodic, and chaotic running states of a machine can be distinguished. It also defines the variable identity, rotating angle and spread degree. The database of diagnostic case is expressed by means of an access database. The diagnostic symptoms are identified using the difference between the Poincare maps of samples and the fault case.Finally, we demonstrate an identification system of a nonlinear vibration diagnostic symptom of large rotating machinery.
