Research On Slip Vector Sequence Based Singular Value Decomposition For Rolling Element Bearing Fault Diagnosis

Rolling element bearings which are common in rotating machines are the researchobjects of the paper. Based on the fault mechanism of the rolling element bearing, alternateload of the rotor-bearing system is introduced into the rolling element bearing signal modeland slip Vector sequence singular value decomposition based fault diagnosis method ofrolling element bearing is proposed. In some operation conditions, rolling bearings arerunning in strong background noise environment where the fault feature recognition andextraction will be influenced by the noise. Therefore, a precise fault signal model for faultcharacteristic description is becoming important. The given of the new model needs detailedinvestigation of physical essence and fault mechanism. A conditional no-stationary faultsignal model is proposed where slip Vector sequence singular value decomposition method isapplied into the rolling bearing fault signal process. The proposed fault diagnosis method canimprove the fault impulses recognition accuracy and the weak fault feature extraction abilityin strong background noise environment. The contents are as follows:1) From the viewpoint of theoretical analysis and engineering application, thebackground and significance of the selected topic are discussed. The development of rollingelements fault mechanism, fault diagnosis methods, fault feature extraction methods arereviewed. Based on the existed problem which need to be solved, the research contends of thepaper are introduced.2) The alternated load of the rotor is considered in the new fault signal model. Theintroducing of the alternate load influence into the new model will give a more precisedescription of the rolling element bearing fault in the rotor-bearing system. At the same time,the alternate load introduction will increase the complexity of the fault signal model whichmay bring some new demands to the fault signal processing methods.3) Impulse fluctuation non-stationary model is proposed in the paper according to theimpulse fluctuation characteristic of the rolling bearing fault. Rolling element bearing faultsignal represents as a quasi-cyclostationary characteristic because of the existence of impulseslip and fluctuation. Therefore, the impulse fluctuation non-stationary fault signal model isproposed to give a more precise description of rolling bearing fault and more accurateprediction of the rolling element bearing fault expression.4) A slip vector design approach is realized in the paper which is related to the impulsefluctuation and strong background noise interference. First the vibration signal is divided intoa series of slip vectors which is helpful to the zoom analysis of time domain signal. Then theslip vector sequence can be obtained by a circulating interception method. In additional to the“microscope” analyzing result to the vibration signal, the slip Vector sequence design methodprovides en effective analyzing foundation and support for the subsequent singular value decomposition feature extraction method.5) A slip vector sequence singular value decomposition based fault feature extractionmethod is proposed by the design of slip vector, introducing of the singular valuedecomposition algorithm, calculation of the main singular value ratio as the analyzing feature.A singular value matrix can be obtained by the singular value decomposition processing ofeach slip vector. A new feature series can be obtained according to the calculation of the mainsingular value ratio. The feature series will reflect the impulse characteristic in the originalvibration signal which can be used to recognize and extract the fault features of the vibrationsignal.6) A slip vector singular value decomposition based fault diagnosis model is proposed bymaking full use of the parameters of the impulse feature. The proposed model has fully takenboth the impulse feature parameters and optimize filter design request in which a (fc, Δf)based filter design method is proposed. Both of the filter stability and fault extraction abilityare taken into account in the proposed filter design method. The fault extraction ability ismaximized based on the precondition of stability and accuracy of fault detection in the newmodel which can extract the weak fault feature in the rolling bearings.In summary, the proposed slip vector singular value decomposition based featureextraction and fault diagnosis method has a good effect on the weak fault feature extraction,accurate fault diagnosis and intelligent assessment. It provides a reliable thinking to theproblem of impulse fluctuation and nonstationarity in the rolling element bearings.