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Gas Leak Location Detection Based on Data Fusion with Time Difference of Arrival and Energy Decay Using an Ultrasonic Sensor Array

机译:基于数据融合的时差到达和能量衰减的超声传感器阵列气体泄漏定位检测

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摘要

Ultrasonic gas leak location technology is based on the detection of ultrasonic waves generated by the ejection of pressured gas from leak holes in sealed containers or pipes. To obtain more accurate leak location information and determine the locations of leak holes in three-dimensional space, this paper proposes an ultrasonic leak location approach based on multi-algorithm data fusion. With the help of a planar ultrasonic sensor array, the eigenvectors of two individual algorithms, i.e., the arrival distance difference, as determined from the time difference of arrival (TDOA) location algorithm, and the ratio of arrival distances from the energy decay (ED) location algorithm, are extracted and fused to calculate the three-dimensional coordinates of leak holes. The fusion is based on an extended Kalman filter, in which the results of the individual algorithms are seen as observation values. The final system state matrix is composed of distances between the measured leak hole and the sensors. Our experiments show that, under the condition in which the pressure in the measured container is 100 kPa, and the leak hole–sensor distance is 800 mm, the maximum error of the calculated results based on the data fusion location algorithm is less than 20 mm, and the combined accuracy is better than those of the individual location algorithms.
机译:超声波气体泄漏定位技术基于对超声波的检测,该超声波是由密封容器或管道泄漏孔中的加压气体喷射产生的。为了获得更准确的泄漏位置信息并确定三维空间中的泄漏孔位置,本文提出了一种基于多算法数据融合的超声泄漏定位方法。在平面超声传感器阵列的帮助下,两种独立算法的特征向量,即到达时间差(由到达时间差(TDOA)定位算法确定)和到达距离与能量衰减之比(ED )定位算法,然后提取并融合以计算泄漏孔的三维坐标。融合基于扩展的卡尔曼滤波器,其中各个算法的结果被视为观察值。最终的系统状态矩阵由测得的泄漏孔和传感器之间的距离组成。我们的实验表明,在被测容器中的压力为100 kPa,泄漏孔与传感器的距离为800 mm的条件下,基于数据融合定位算法的计算结果的最大误差小于20 mm ,并且合并后的精度优于各个定位算法。

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