Valves on natural gas transmission pipelines are prone to internal leakage due to the influence of environment, transportation medium, misoperation and other factors. Therefore, timely and accurate detection of valve internal leakage is of great significance to the safe operation of the pipelines. As a non-destructive testing method, acoustic emission (AE) technology can be used for online detection of internal leakage of valve. In order to improve the accuracy of AE technology for detecting valve internal leakage, a ball valve internal leakage detection method based on acoustic emission technology is proposed. Firstly, the AE signal generated by the internal leakage of the ball valve is detected by AE sensor, and the AE signal is denoised by wavelet packet threshold denoising. Secondly, the characteristic parameters with high correlation with the internal leakage rate of the ball valve are selected by using the correlation coefficient method to form the sample feature set. Finally, the mathematical model between the internal leakage rate of the ball valve and the characteristic parameters is established by using the sparrow search algorithm to optimize the backpropagation neural network, and to predict the internal leakage rate of the ball valve. An experimental platform is built to verify that the proposed method can predict the internal leakage rate of the ball valve more accurately. It provides strong technical support for the safe operation of natural gas transmission pipelines.

天然气输送管道上的阀门受环境、输送介质、误操作等因素的影响，容易发生内漏。因此，及时准确地检测阀门内漏对管道的安全运行具有重要意义。声发射（AE）技术作为一种无损检测方法，可用于阀门内漏的在线检测。为了提高声发射技术检测阀门内漏的准确性，提出了一种基于声发射技术的球阀内漏检测方法。首先通过声发射传感器检测球阀内泄漏产生的声发射信号，并通过小波包阈值去噪对声发射信号进行去噪。第二，采用相关系数法选取与球阀内漏率相关性高的特征参数，形成样本特征集。最后，通过使用麻雀搜索算法优化反向传播神经网络，建立球阀内漏率与特征参数之间的数学模型，预测球阀内漏率。搭建实验平台，验证所提方法能够更准确地预测球阀的内漏率。为天然气输送管道的安全运行提供了强有力的技术支撑。采用麻雀搜索算法优化反向传播神经网络，建立球阀内漏率与特征参数之间的数学模型，预测球阀内漏率。搭建实验平台，验证所提方法能够更准确地预测球阀的内漏率。为天然气输送管道的安全运行提供了强有力的技术支撑。采用麻雀搜索算法优化反向传播神经网络，建立球阀内漏率与特征参数之间的数学模型，预测球阀内漏率。搭建实验平台，验证所提方法能够更准确地预测球阀的内漏率。为天然气输送管道的安全运行提供了强有力的技术支撑。搭建实验平台，验证所提方法能够更准确地预测球阀的内漏率。为天然气输送管道的安全运行提供了强有力的技术支撑。搭建实验平台，验证所提方法能够更准确地预测球阀的内漏率。为天然气输送管道的安全运行提供了强有力的技术支撑。