33results about How to "Enhanced fault signature" patented technology

The invention discloses a method for strengthening weak faults of rolling bearings based on matrix recovery, which belongs to the technical field of fault diagnosis of rotating machinery. By constructing the fault information matrix, the collected one-dimensional vibration signal is expressed in the form of a two-dimensional fault information matrix, so as to meet the input requirements of the matrix recovery theory, and use the matrix recovery algorithm to restore the shock characteristics from the two-dimensional fault information matrix. Based on the low-rank matrix, the cumulative average algorithm is used to restore the vibration signal without noise interference from the low-rank matrix. At the same time, considering the inevitable tail truncation phenomenon when constructing the fault information matrix, the positive sequence and reverse sequence fault information matrices are respectively constructed for the positive sequence and reverse sequence vibration signals, and the above three steps are carried out for the two fault information matrices respectively, and The denoising information obtained through the above two fault information matrices is synthesized to obtain a final denoising signal. The method is applicable to the analysis of vibration signals of rotating machinery in the field of fault diagnosis of rotating machinery.

The invention discloses an improved keyless phase fault feature order extraction method, comprising the following steps: 1) Obtaining the state information of the equipment through a vibration acceleration sensor, and preprocessing the obtained state information by using a time-frequency analysis method to obtain the instantaneous frequency ; 2) Carry out conventional integral operation on the estimated instantaneous frequency to obtain a roughly estimated instantaneous phase, and then use the Romberg integral rule to correct the roughly estimated instantaneous phase, and finally obtain an accurate estimated instantaneous phase; 3) According to the time domain and The mapping relationship in the angle domain uses the accurately estimated instantaneous phase information to resample the original signal in the angle domain; 4) uses the flexible angle domain synchronous averaging method to perform noise reduction processing on the angle domain resampled signal, and then the angle domain after noise reduction The fault characteristic order of the equipment is extracted by performing order spectrum analysis on the domain resampled signal. This method can accurately extract the fault characteristic order of the equipment under the condition of keyless phase change speed.

The invention relates to a distribution network single-phase grounding protection method based on active and passive joint detection of weak faults, and belongs to the technical field of electric power system relay protection. When the distribution network is running abnormally, use the bus zero-sequence voltage wavelet transform mutation energy in the low frequency band to judge whether the system has a single-phase ground fault, and start protection; if a fault occurs, the bus zero-sequence voltage when the neutral point is not regulated The zero-sequence current is sampled, decomposed by 6-layer wavelet, and the characteristic frequency band is determined by using the energy and maximum principle; the fault passive detection criterion is constructed after the wavelet coefficients under the characteristic frequency band are cross-overlapped and differentially transformed. According to whether the first non-zero value of the passive detection discriminant exceeds the threshold, it is judged whether a single-phase ground fault occurs in the feeder. The present invention utilizes whether the zero-sequence voltage can be continuously detected multiple times within a fixed time limit, can preliminarily judge the nature of the fault, and avoid repeated tripping to reduce power supply reliability.

The invention provides a rolling bearing slip rate evaluation method based on vibration information demodulation analysis, which uses a vibration sensor to collect high-frequency vibration signals, and simultaneously uses a key phase sensor to synchronously collect key phase signals, and obtains the packet of the original signal through Hilbert transform. The envelope demodulation signal, and then use the key phase information to perform linear equiangular interpolation on the envelope demodulation signal, obtain the envelope signal of the narrow-band impact by setting the narrow-band filter, and calculate its phase, use the phase calculation of the narrow-band impact envelope signal, etc. Using the equivalent reference shaft phase and speed, the envelope order spectrum analysis is performed again using the equivalent reference shaft phase, and the slip rate of the bearing is calculated using the equivalent reference shaft speed. The present invention can effectively suppress the order migration caused by slipping And fuzzy phenomenon, enhance the fault characteristics, and can estimate the bearing slip rate, and the evaluation accuracy is high.

The invention relates to a diagnosis method for impact type failure between a rolling bearing and a gear based on an optimal self-adaptive wavelet filter, which comprises the following steps: firstly establishing an exponentially damped sinusoidal impact type failure signal model, using a mode self-adaptive wavelet generation algorithm publicly disclosed by Hector Mesa to generate a self-adaptive wavelet filter which is matched with the signal model, then utilizing a fast FIR (finite impulse response) filtering algorithm to execute the wavelet filter to obtain the filtering result, then calculating the kurtosis value of the filtering result, and using an evolution differential algorithm to repeat the steps so as to finally obtain an optimized envelope spectrum. By adopting the method, impact failure characteristics in vibration signals can be precisely extracted, and a clearer envelope spectrum can be given out, thereby ensuring that failure symptoms can be displayed more clearly.