Abstract：Bolt looseness is a common mechanical fault with potential harm. Considering that the bolt looseness induces the variation of dynamic parameters of joint of bolt connection, a detection method is proposed based on vibration signals of two connected parts. The proposed method calculates probability density of two signals at first. The probability density curves are processed by a mesh to obtain probability matrixes, and the probability matrixes are transformed by using principal component analysis (PCA) method. After PCA, two projection matrixes of probability matrixes are merged to one matrix. To this matrix, PCA and projection are implemented again. According to the peculiarity of bolt looseness, tow detection modes are designed based on the proposed method. The mode 1 carries out training work using foregone samples to generate projection points of each looseness condition employing the proposed method, then in detection, using Euclidean distance between projection point and each foregone projection points as estimation criterion. The mode 2 directly detects looseness condition by using proposed method based on the signals of tight bolt connection condition and field measurement，and a criterion for judging bolt looseness is designed. The experimental verification shows that the proposed method can distinguish different looseness condition, and the detection mode 2 is easy and simple to be handled without foregone fault sample, then the propose method has some application prospect.
李允公 孔祥娜 高玉勇. 基于两被联件振动信号概率密度和PCA的螺栓松动识别方法研究[J]. 振动与冲击, 2015, 34(1): 63-67.
LI Yungong KONG Xiangna GAO Yuyong. A Method for Detecting Bolt Looseness Base on Probability Density of Vibration Signals of Two Connected Parts and Principal Component Analysis. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(1): 63-67.
2015, Vol. 34 
