Based on the multi-loop method, the rotating torque and speed of theinduction machine are analyzed. The fluctuating components of the torque and speed caused by rotorwinding faults are studied. The models for calculat...Based on the multi-loop method, the rotating torque and speed of theinduction machine are analyzed. The fluctuating components of the torque and speed caused by rotorwinding faults are studied. The models for calculating the fluctuating components are put forward.Simulation and computation results show that the rotor winding faults will cause electromagnetictorque and rotating speed to fluctuate; and fluctuating frequencies are the same and their magnitudewill increase with the rise of the severity of the faults. The load inertia affects the torque andspeed fluctuation, with the increase of inertia, the fluctuation of the torque will rise, while thecorresponding speed fluctuation will obviously decline.展开更多
In order to address the issues of traditional resampling algorithms involving computational accuracy and efficiency in rolling element bearing fault diagnosis, an equal division impulse-based（EDI-based） resampling a...In order to address the issues of traditional resampling algorithms involving computational accuracy and efficiency in rolling element bearing fault diagnosis, an equal division impulse-based（EDI-based） resampling algorithm is proposed. First, the time marks of every rising edge of the rotating speed pulse and the corresponding amplitudes of faulty bearing vibration signal are determined. Then, every adjacent the rotating pulse is divided equally, and the time marks in every adjacent rotating speed pulses and the corresponding amplitudes of vibration signal are obtained by the interpolation algorithm. Finally, all the time marks and the corresponding amplitudes of vibration signal are arranged and the time marks are transformed into the angle domain to obtain the resampling signal. Speed-up and speed-down faulty bearing signals are employed to verify the validity of the proposed method, and experimental results show that the proposed method is effective for diagnosing faulty bearings. Furthermore, the traditional order tracking techniques are applied to the experimental bearing signals, and the results show that the proposed method produces higher accurate outcomes in less computation time.展开更多
The layout features of unit shafting and their effects on vibration, as well as evaluation criteria, were introduced for a 1000-MW ultra-supercritical turbine-generator unit with Simens technology. Based on vibration ...The layout features of unit shafting and their effects on vibration, as well as evaluation criteria, were introduced for a 1000-MW ultra-supercritical turbine-generator unit with Simens technology. Based on vibration diagnosis and treatment for more than 10 units, some typical vibration faults were summarized, such as the vibration fluctuation of the high pressure (HP) rotor, abnormal vibration increases of the No.3 bearing pedestal and large vibration of the exciter rotor during its critical speed range. The vibration characteristics and the causes of faults and countermeasures were analyzed. Three applications for further illustration were given. The vibration fault identification method, control measures, and applications can provide a reference for vibration diagnoses and treatment of same type units.展开更多
Wavelet denoising is an effective approach to extract fault features from strong background noise.It has been widely used in mechanical fault detection and shown excellent performance.However,traditional thresholds ar...Wavelet denoising is an effective approach to extract fault features from strong background noise.It has been widely used in mechanical fault detection and shown excellent performance.However,traditional thresholds are not suitable for nonstationary signal denoising because they set universal thresholds for different wavelet coefficients.Therefore,a data-driven threshold strategy is proposed in this paper.First,the signal is decomposed into different subbands by wavelet transformation.Then a data-driven threshold is derived by estimating the noise power spectral density in different subbands.Since the data-driven threshold is dependent on the noise estimation and adapted to data,it is more robust and accurate for denoising than traditional thresholds.Meanwhile,sliding window method is adopted to set a flexible local threshold.When this method was applied to simulation signal and an inner race fault diagnostic case of dedusting fan bearing,the proposed method has good result and provides valuable advantages over traditional methods in the fault detection of rotating machines.展开更多
文摘Based on the multi-loop method, the rotating torque and speed of theinduction machine are analyzed. The fluctuating components of the torque and speed caused by rotorwinding faults are studied. The models for calculating the fluctuating components are put forward.Simulation and computation results show that the rotor winding faults will cause electromagnetictorque and rotating speed to fluctuate; and fluctuating frequencies are the same and their magnitudewill increase with the rise of the severity of the faults. The load inertia affects the torque andspeed fluctuation, with the increase of inertia, the fluctuation of the torque will rise, while thecorresponding speed fluctuation will obviously decline.
基金Fundamental Research Funds for the Central Universities(No.2016JBM051)
文摘In order to address the issues of traditional resampling algorithms involving computational accuracy and efficiency in rolling element bearing fault diagnosis, an equal division impulse-based（EDI-based） resampling algorithm is proposed. First, the time marks of every rising edge of the rotating speed pulse and the corresponding amplitudes of faulty bearing vibration signal are determined. Then, every adjacent the rotating pulse is divided equally, and the time marks in every adjacent rotating speed pulses and the corresponding amplitudes of vibration signal are obtained by the interpolation algorithm. Finally, all the time marks and the corresponding amplitudes of vibration signal are arranged and the time marks are transformed into the angle domain to obtain the resampling signal. Speed-up and speed-down faulty bearing signals are employed to verify the validity of the proposed method, and experimental results show that the proposed method is effective for diagnosing faulty bearings. Furthermore, the traditional order tracking techniques are applied to the experimental bearing signals, and the results show that the proposed method produces higher accurate outcomes in less computation time.
文摘The layout features of unit shafting and their effects on vibration, as well as evaluation criteria, were introduced for a 1000-MW ultra-supercritical turbine-generator unit with Simens technology. Based on vibration diagnosis and treatment for more than 10 units, some typical vibration faults were summarized, such as the vibration fluctuation of the high pressure (HP) rotor, abnormal vibration increases of the No.3 bearing pedestal and large vibration of the exciter rotor during its critical speed range. The vibration characteristics and the causes of faults and countermeasures were analyzed. Three applications for further illustration were given. The vibration fault identification method, control measures, and applications can provide a reference for vibration diagnoses and treatment of same type units.
基金supported by the National Natural Science Foundation of China(Grant No.51275384)the Key project of National Natural Science Foundation of China(Grant No.51035007)+1 种基金the National Basic Research Program of China("973"Project)(Grant No.2011CB706805)the Specialized Research Fund for the Doctoral Program of Higher Education(Grant No.20110201130001)
文摘Wavelet denoising is an effective approach to extract fault features from strong background noise.It has been widely used in mechanical fault detection and shown excellent performance.However,traditional thresholds are not suitable for nonstationary signal denoising because they set universal thresholds for different wavelet coefficients.Therefore,a data-driven threshold strategy is proposed in this paper.First,the signal is decomposed into different subbands by wavelet transformation.Then a data-driven threshold is derived by estimating the noise power spectral density in different subbands.Since the data-driven threshold is dependent on the noise estimation and adapted to data,it is more robust and accurate for denoising than traditional thresholds.Meanwhile,sliding window method is adopted to set a flexible local threshold.When this method was applied to simulation signal and an inner race fault diagnostic case of dedusting fan bearing,the proposed method has good result and provides valuable advantages over traditional methods in the fault detection of rotating machines.
