Based on wavelet packet decomposition （WPD） algorithm and Teager energy operator （TEO）, a novel gearbox fault detection and diagnosis method is proposed. Its process is expatiated after the principles of WPD and TEO modulation are introduced respectively. The preprocessed sigaaal is interpolated with the cubic spline function, then expanded over the selected basis wavelets. Grouping its wavelet packet components of the signal based on the minimum entropy criterion, the interpolated signal can be decomposed into its dominant components with nearly distinct fault frequency contents. To extract the demodulation information of each dominant component, TEO is used. The performance of the proposed method is assessed by means of several tests on vibration signals collected from the gearbox mounted on a heavy truck. It is proved that hybrid WPD-TEO method is effective and robust for detecting and diagnosing localized gearbox faults.
In the mechanical fault detection and diagnosis field, it is more and more important to analyze the instantaneous frequency （IF） character of complex vibration signal. The improved IF estimation method is put forward aiming at the shortage of traditional Hilbert transform. It is based on Hilbert transform in wavelet domain. With the help of relationship between the real part and the imaginary part obtained from the complex coefficient of continuous wavelet transform or the analyti- cal signal reconstructed in wavelet packet decomposition, the instantaneous phase function of the subcomponent is extracted. In order to improve the precise of IF estimated out, some means such as Linear regression, adaptive filtering, resampling are applied into the instantaneous phase obtained, then, the central differencing operator is used to get desired IF. Simulation results with synthetic and gearbox fault signals are included to illustrate the proposed method.
Based on the theory of adaptive time-frequency decomposition and Time-Frequency Dis- tribution Series (TFDS), this paper presents a novel denoising method for non-stationary signal. Ac- cording to the input signal features, an appropriate kind of elementary functions with great concen- tration in the Time-Frequency (TF) plane is selected. Then the input signal is decomposed into a linear combination of these functions. The elementary function parameters are determined by using ele- mentary function TF curve surface to fit the input signal’s TFDS. The process of curved surface fitting corresponds to the signal structure matching process. The input signal’s dominating component whose structure has the resemblance with elementary function is fitted out firstly. Repeating the fitting process, the residue can be regarded as noises, which are greatly different from the function. Selecting the functions fitted out initially for reconstruction, the denoised signal is obtained. The performance of the proposed method is assessed by means of several tests on an emulated signal and a gearbox vi- brating signal.
A novel measurement system specially used in noise emission assessment and verification of wind turbine generator systems is presented that complies with specifications given in IEC 61400-11 to ensure the process consistency and accuracy. Theory elements of the calculation formula used for the sound power level of wind turbine have been discussed for the first time, and detailed calculation procedure of tonality and audibility integrating narrowband analysis and psychoacoustics is described. With a microphone and two PXI cards inserted into a PC, this system is designed in Qin′s model using VMIDS development system. Benefiting from the virtual instrument architecture, it′s the first time that all assessment process have been integrated into an organic whole, which gives full advantages of its efficiency, price, and facility. Mass experiments show that its assessment results accord with the ones given by MEASNET member.
Timing jitter is one of the main factors that influence on the accuracy of time domain precision measurement. Timing jitter compensation is one of the problems people concern. Because of the flaws of median method, PDF deconvolution method and synthetic method, we put forward a new method for timing jitter compensation, which is called advanced median method. The theory of the advanced median method based on probability and statistics is analyzed, and the process of the advanced median method is summarized in this paper. Simulation and experiment show that compared with other methods, the new method could compensate timing jitter effectively.
Wang ChenZhu JiangmiaoJan VerspechtLiu MingliangLi Yang
