High-accuracy detection and location of gas leaks based on adaptive weighted data fusion using an ultrasonic transducer array

This paper proposes a gas leak detection and location method with high accuracy based on an adaptive weighted data fusion algorithm using an ultrasonic transducer array. First, the approximate entropy theory is combined with a support vector machine (SVM) to judge whether there is a gas leak, achieving a recognition accuracy of 95.69%. Once a leak is identified, a leak localisation algorithm is applied. To obtain more stable features and reduce environmental noise, the sound pressure amplitude and time-delay difference are extracted using an optimised signal processing method and normalised least mean squares (NLMS) adaptive filter, respectively. The energy decay (ED) localisation algorithm is then fused with the time difference of arrival (TDOA) algorithm to determine the location of the leak. Experimental results demonstrate that under a pressure of 15 kPa in the measured container with a distance of 1 m between the leak and transducer array, the location error is within 5 mm, which is more accurate than previously proposed methods. Additionally, the adaptive weighted data fusion algorithm overcomes the limitations of the TDOA and ED algorithms.