| Abstract [eng] |
This special issue titled “Fault Identification, Diagnosis, and Prognostics Based on Complex Signal Analysis” is a truly interdisciplinary issue. Manuscripts published in this special issue do represent such diverse fields as mechanical engineering, aviation engineering and technology, electric and electronic engineering, statistics, and so on. The geography of authors spans over three continents, Asia, Europe, and America. A total of 18 manuscripts were published in this issue. This special issue gathered several studies that focus on fault detection and diagnosis of mechanical products, such as bolts, rolling bearings, gears, and hydraulic servo systems. For example, G. Wu et al. proposed a modified time reversal method and successfully realized bolt loosening detection and localization in simulated thermal protection system panels. Two studies aim to reduce the background noise in monitoring signal of rolling bearings, thus improving the effectiveness of fault diagnosis. R. Yuan et al. reported an adaptive high-order local projection denoising method and demonstrated the characteristic frequencies of simulated signals can be well extracted by the proposed method. D. Zhong et al. proposed a novel fault signal denoising scheme based on improved sparse regularization via convex optimization to extract the fault feature of rolling bearing. Experiments show that the proposed method has a better performance than traditional methods. In an interesting study, a method based on the multiscale chirplet path pursuit and the linear canonical transform is proposed by X. Shuiqing et al. and applied to diagnose the gear fault in the variable speed condition for the first time. This method can diagnose the gear faults availably. In another study, Y. Ding et al. presented a fault diagnosis scheme for hydraulic servo system using compressed random subspace based ReliefF (CRSR) method. The proposed CRSR method is able to enhance the robustness of the feature information against interference while selecting the feature combination with balanced information expressing ability. Finally, dealing with sliding mode Fault Tolerant Control (FTC) problem for nonlinear system, two adaptive sliding mode FTC schemes for an uncertain nonlinear system subject to multiplicative and process faults were presented by A. Ben Brahim et al. By solving a single-step multiobjective LMI optimization problem, the observer and controller gains are obtained, offering a solution to stabilize the closed-loop nonlinear system despite the occurrence of real fault effects. |
