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《Automation & Information Engineering》 2019-02
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Acoustic Detection Method for Vacuum Degree of Canned Foods Based on NMF

Han Wei;Li Chang;Zhou Songbin;Liu Weixin;Qiu Zefan;Guangdong Institute of Intelligent Manufacturing, Guangdong Key Laboratory of Modern Control Technology;Guangdong University of Technology;  
At present the spectral peak method is widely used to detect the vacuum degree of canned foods. Whether the spectral peak frequency of the sound produced by the vibration of the can lid is in the appropriate range is taken as the detection basis of this method. However, the spectral peak frequency of some unqualified products is also within the set appropriate range appeared in practical application, which leads to the misjudgment of this method. In order to improve the detection performance, this paper firstly proposes to treat the vacuum degree detection of canned food as a one-class classification problem, and presents a one-class classification algorithm based on non-negative matrix factorization. The classifier only needs to be learned from the dataset of qualified products in this algorithm, and then it can be used to judge whether the vacuum of the detected product is qualified or not. We constructed an experimental system for the vacuum degree detection of canned food, and compared the proposed method with the traditional spectral peak method and the typical one-class classification methods.
【Fund】: 国家自然科学基金项目(61803107);; 广州市科技计划项目(201803020025 201906010036);; 广东省科学院人才项目(2019GDASYL-0105069)
【CateGory Index】: TS207.3
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