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Wei He,Zhinong Jiang,Qiang Qin 대한기계학회 2010 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.24 No.8
Periodical impulses are vital indicators of rotating machinery faults. Therefore, the extraction of weak periodical impulses from vibration signals is of great importance for incipient fault detection. However, measured signals are often severely tainted by various noises,which makes the detection of impulses rather difficult. As such, a proper signal processing technique is necessary. In this paper, a hybrid method comprised of wavelet filter and morphological signal processing (MSP) is proposed for this task. The wavelet filter is used to eliminate the noise and enhance the impulsive features. Then, the filtered signal is processed by the morphological closing operator and a local maximum algorithm to isolate periodical impulses. To select the proper parameters of the joint approach, i.e., the center frequency,the bandwidth of wavelet filter, and the length of flat structuring elements (SE), a novel optimization algorithm based on differential evolution (DE) is developed. The results of simulated experiments and bearing vibration signal analysis verify the effectiveness of the proposed method.
Binbin Yan,Minghui Hu,Kun Feng,Zhinong Jiang 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.12
To minimize the simulated performance error of gas turbines, traditional adaptive methods are mainly concerned with the tuning of cycle design point and component maps given by the manufacturer, usually ignoring the fact that performance at cycle design point may not match the field data due to the deviation between test-rig conditions and field conditions. In this paper, a new tuning scheme of the cycle reference point is proposed to minimize the simulated errors simultaneously at design point and off-design points. The scheme is composed of a backward iteration algorithm and a genetic algorithm. During the backward iteration, the field data at the maximum operating condition is selected to obtain the initial cycle reference point with several undetermined parameters. Further, the genetic algorithm is used to optimize the undetermined parameters. The accuracy of the proposed method was validated by the simulated performance of a PGT25+ gas turbine.