Abstract
A new AE location method using tri-variate kernel density estimator is developed in this paper. Firstly, combinations of every six arrivals are obtained from a multi-sensor location system, and the preliminary location results are obtained by solving the systems of linear equations constructed by these arrival combinations. Secondly, the tri-variate scaled kernel functions at each AE source coordinate are established. The tri-variate kernel density estimator is constructed by adding and normalizing these scaled kernel functions. Finally, the extreme value of the density function is calculated and the coordinate corresponding to the extreme value is extracted as the final location result. Pencil-lead break experiments were carried out. The results verified that the proposed method was more accurate and effective than traditional methods in the location performance. Moreover, the influence of outlier scales and proportions of the proposed method were investigated by simulation tests. Results showed that the location performance of the proposed method was higher than that of traditional methods under different outlier scales and proportions.
Highlights
The location technology of acoustic emission (AE) sources by passive sensor arrays has been widely used in the structural integrity monitoring, mine risk warning, material damage mechanism research and other fields [1]–[5]
Due to the difficulty in obtaining the prior knowledge of distribution of the arrival errors or AE source coordinates, a new AE source location method using tri-variate kernel density estimator is proposed in this paper, so as to further improve the location accuracy
The AE source coordinates are drawn by solving these linear equations, and all the real source coordinates constitute the preliminary location results
Summary
The location technology of acoustic emission (AE) sources by passive sensor arrays has been widely used in the structural integrity monitoring, mine risk warning, material damage mechanism research and other fields [1]–[5]. A distribution model of arrival errors is assumed in advance to estimate the location of an AE source by measured arrivals [12], [13]. Jiang and Azimi-Sadjadi [21] derived a new source location method by modeling arrival errors as Cauchy-Lorentz distribution. The overlook of correlation among AE source coordinates lead to errors in the final result. To this end, a new AE source location method using tri-variate kernel density estimator is proposed. The AE source coordinates and two additional variates of each arrival combination are obtained through the above equations without any additional assumption on arrival errors. The m-group preliminary location results usually differ in a great degree due to the presence of the arrival errors
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