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首页> 外文期刊>Journal of Mechanical Science and Technology >A novel antibody population optimization based artificial immune system for rotating equipment anomaly detection
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A novel antibody population optimization based artificial immune system for rotating equipment anomaly detection

机译：基于旋转设备异常检测的新型抗体种群优化基于人工免疫系统

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摘要

Rotating machines are one of the most common equipments in modern industry, effective fault detection and diagnosis methods are vital to equipment health monitoring. In industrial production, the known information of fault types is insufficient generally, especially for constructing complex equipment and components. In previous studies of equipment fault detection, accurate fault classification and diagnosis methods have been presented, while seldom takes the condition of paucity of fault data into account. Therefore, this paper presents a novel antibody population optimization based artificial immune system (APO-AIS) for rotating equipment anomaly detection. The proposed approach can detect abnormal events while monitoring the operating condition. Meanwhile, an antigen-based antibody selecting method, a density-based antibody screening method and an optimized judgment rule based on individual difference are presented for improving the iteration evolution. The presented methods and optimized judgment rule enhance the robustness and reduces training burden for the proposed approach, which leads to accurate anomaly detection in strong background noise and in practical industrial environment. The effectiveness and robustness of the proposed method has been proven experimentally by bearing fault diagnosing and centrifugal pump condition monitoring in this paper.
机译：旋转机器是现代工业中最常见的设备之一，有效的故障检测和诊断方法对设备健康监测至关重要。在工业生产中，故障类型的已知信息通常不足，特别是用于构建复杂的设备和部件。在先前的设备故障检测的研究中，已经提出了准确的故障分类和诊断方法，虽然很少考虑故障数据的缺乏缺陷的条件。因此，本文提出了一种基于新的抗体群体优化的基于人工免疫系统（APO-AIS），用于旋转设备异常检测。所提出的方法可以在监控操作条件的同时检测异常事件。同时，提出了一种基于抗原的抗体选择方法，基于密度的抗体筛选方法和基于个体差异的优化判断规则以改善迭代演化。呈现的方法和优化的判断规则提高了鲁棒性，并降低了提出的方法的培训负担，这导致精确的异常检测强大的背景噪音和实际工业环境。通过本文的故障诊断和离心泵状态监测，通过实验证明了该方法的有效性和稳健性。

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