The Coriolis mass flowmeter (CMF) is widely used to measure mass flow, mainly in petrochemical, medical, pharmaceutical, food manufacturing, and other industries. The measuring tube is the crucial component of CMF, which affects the measurement accuracy and causes losses to the production of enterprises. Wall-mounted failure of the measuring tube affects measurement accuracy. A real-time detection method based on acceleration sensor array signal processing and pattern recognition are proposed to detect such failure. Two acceleration sensors are arranged outside the CMF to compose a five-channel sensor array. The signals of the multichannel array are decomposed through a blind source separation algorithm, and array signal features are extracted by a wavelet scattering network. Support vector data description (SVDD) is used to detect the hanging state of CMF at last. The experimental results show that the proposed method can be used to detect the CMF wall-mounted failure in real-time with an accuracy of 89.59%, and the method can reduce production losses.
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