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A method for identifying ethylene gas leakage based on multi-feature joint detection and risk analysis

机译:基于多特征联合检测和风险分析的乙烯泄漏识别方法

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In view of the fact that the leakage of ethylene gas in the production process of petrochemical enterprises can easily cause major safety accidents, infrared video real-time imaging is used to monitor possible ethylene gas leakage points, and ethylene gas is achieved through real-time processing and analysis of acquired infrared video images. Real-time detection of leakage, a multi-feature joint detection of ethylene gas leakage, using the loss function to carry out risk analysis of the test results, and ultimately to determine whether there is ethylene gas leakage determination of ethylene gas leakage identification method. Firstly, by establishing a global energy function model, the interrelationships between intra-frame and inter-frame neighboring pixels in the video sequence and the spatial domain information are used, and by adding a neighborhood constraint, an integrated spatio-temporal consistency feature set, etc., a leak suspecting segmentation is achieved. Then, an ethylene gas leak detection and identification method based on multi-feature joint detection was proposed by analyzing and detecting the characteristics of area variation in suspected areas of gas leakage, wavelet domain energy variation characteristics, and transient gray value “nine-square grid” distribution characteristics. Finally, through the further determination of the leakage state based on the loss function and risk analysis, the misjudgment and missed-judgement conditions are eliminated as much as possible, and the accuracy of the recognition is improved. The experimental results show that the ethylene gas leakage detection and identification method in this paper has the characteristics of good real-time performance and high recognition rate, which can meet the real-time warning requirements.
机译:鉴于石化企业生产过程中乙烯气体的泄漏很容易造成重大安全事故,因此采用红外视频实时成像监控可能的乙烯气体泄漏点,并通过实时获取乙烯气体来实现。采集的红外视频图像的处理和分析。实时检测泄漏量,采用多特征联合检测乙烯气体泄漏量,利用损失功能对检测结果进行风险分析,最终确定是否存在乙烯气体泄漏量的确定是确定乙烯气体泄漏量的方法。首先,通过建立全局能量函数模型,使用视频序列中帧内和帧间相邻像素与空间域信息之间的相互关系,并通过添加邻域约束,集成的时空一致性特征集,等等,实现了泄漏怀疑分割。然后,通过分析检测漏气可疑区域的面积变化特征,小波域能量变化特征和暂态灰度值“九方格”,提出了一种基于多特征联合检测的乙烯漏气识别方法。分布特征。最终,通过基于损失函数和风险分析的泄漏状态进一步确定,尽可能地消除了误判和漏判情况,提高了识别的准确性。实验结果表明,本文的乙烯气体泄漏检测与识别方法具有实时性好,识别率高的特点,可以满足实时预警的要求。

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