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Abstract:In view of the problem that the fault signal of the rolling bearing is weak and the fault feature is difficult to extract in the strong noise environment, a method based on minimum entropy deconvolution (MED) and local mean deconvolution (LMD) is proposed to extract the weak fault features of the rolling bearing. Through the analysis of the simulation signal, we find that LMD has many limitations for the feature extraction of weak signals under strong background noise. In order to eliminate the noise interference and extract the characteristics of the weak fault, MED is employed as the pre-filter to remove noise. This method is applied to the weak fault feature extraction of rolling bearings; that is, using MED to reduce the noise of the wind turbine gearbox test bench under strong background noise, and then using the LMD method to decompose the denoised signals into several product functions (PFs), and finally analyzing the PF components that have strong correlation by a cyclic autocorrelation function. The finding is that the failure of the wind power gearbox is generated from the micro-bending of the high-speed shaft and the pitting of the #10 bearing outer race at the output end of the high-speed shaft. This method is compared with LMD, which shows the effectiveness of this method. This paper provides a new method for the extraction of multiple faults and weak features in strong background noise.

In recent years, a new method of fault diagnosis, named variational mode decomposition (VMD), has been widely used in industrial production, but the decomposition accuracy of VMD is determined by two parameters, which are respectively the decomposition layer number k and the penalty factor α, if the parameters are not properly selected, there will be over-decomposition or under-decomposition. In order to find an approach to determine the parameters adaptively, a method to optimize VMD by using the immune fruit fly optimization algorithm (IFOA) is proposed in this paper. In this method, permutation entropy is used as the fitness function, firstly, the immune fruit fly optimization algorithm is used to search the combined parameters of k and α in VMD, searching for the best combination parameters of k and α by iteration, and then uses the combined parameters to perform VMD, finally, the center frequency is determined through frequency spectrum analysis. The method mentioned is applied to the fault extraction of a simulated signal and a measured signal of a wind turbine gearbox, and the fault frequency is successfully extracted. Using ensemble empirical mode decomposition (EEMD) and singular spectrum decomposition (SSD) to compare with the proposed method, which validated feasibility of the proposed method.

Water hammer analysis is a fundamental work of pipeline systems design process for water distribution networks. The main characteristics for mine drainage system are the limited space and high cost of equipment and pipeline changing. In order to solve the protection problem of valve-closing water hammer for mine drainage system, a water hammer protection method for mine drainage system based on velocity adjustment of HCV (Hydraulic Control Valve) is proposed in this paper. The mathematic model of water hammer fluctuations is established based on the characteristic line method. Then, boundary conditions of water hammer controlling for mine drainage system are determined and its simplex model is established. The optimization adjustment strategy is solved from the mathematic model of multistage valve-closing. Taking a mine drainage system as an example, compared results between simulations and experiments show that the proposed method and the optimized valve-closing strategy are effective.

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The lay length is one of the important parameters for the wire rope and its detection can indirectly characterize its stress and surface damage state. The eddy current testing (ECT) method is advantageous because of its easy operation, single-side detection, low requirement of surface preparation, applicability in harsh environment, and other properties. Hence the lay length of the wire ropes is measured by ECT in this paper. The eddy current (EC) response to the wire rope is simulated. The EC on the surface of the strand below the pancake coil forms a vortex, and the distribution of the EC on the curved surfaces on both sides of the strand is symmetrical. The spacing between the adjacent peaks or troughs of the scanning signal is the distance between the adjacent strands, and the number of peaks or troughs of the scanning signal in a range of the lay length is related to the number of strands of the wire rope. Finally, the experimental validation is performed. The relative error of the lay length of the wire rope assessed by the EC method is less than 0.28%.