个人信息
参与实验室科研项目
人机智能协同关键技术及其在智能制造中的应用
非可信智能驱动的可靠智造
学术成果
共撰写/参与撰写专利 1 项,录用/发表论文 2 篇,投出待录用论文0篇。
patent
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贴片机的健康度评估方法及系统
李鹏飞,
赵昀昇,
康宇,
赵云波,
and 王涛
[Abs]
本发明公开了一种贴片机的健康度评估方 法及系统,属于工业制造装备技术领域,包括:获 取贴片机当前运行状态数据;采用主成分分析法 对当前运行状态数 据进行特征提取 ,得到i个健 康监 测指标 ;采 用标准化欧氏 距离法 ,根据健康 监测指标在贴片机整体健康情况中的健康权重, 计算各健康监测指标的向量与理想健康向量之 间的距离;采用负向函数将距离换算成贴片机的 健康值。整个预测过程,简单易操作,可解释性很 强,不需要进行复杂地配置,贴合工业环境,无需 占 用过多的计算资源,即实现对贴片机的健康程 度评估。
Journal Articles
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A Health Indicator Enabling Both First Predicting Time Detection and Remaining Useful Life Prediction: Application to Rotating Machinery
Yun-Sheng Zhao,
Pengfei Li,
Yu Kang,
and Yun-Bo Zhao
Measurement
2024
[Abs]
[doi]
[pdf]
Remaining Useful Life (RUL) prediction is vital for system functionality. Non-end-to-end approaches is an important type of RUL prediction approaches for their important application in industrial scenarios. In non-end-to-end approaches, Health Indicator (HI) construction is a critical aspect. However, existing HI construction approaches ignore First Predicting Time (FPT) detection, leading to increased domain knowledge demand and system health comprehension difficulty. To address this issue, this paper proposes a multi-objective-optimization-based HI construction approach enabling both FPT detection and RUL prediction. A novel metric called the monotonicity strength index is proposed to address the limitation of the conventional monotonicity. The constructed HI possesses the ability to indicate FPT by taking the detectability metric as an optimization objective. The optimization problem is solved by the combination of the multi-objective ant lion optimizer and the entropy weight method. The superiority of this HI is demonstrated through experiments on the widely used IMS bearing dataset and a gearbox dataset.
Conference Articles
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Equipment Health Assessment Based on AHP-CRITIC Dynamic Weight
Yunsheng Zhao,
Pengfei Li,
Tao Wang,
Yu Kang,
and Yun-Bo Zhao
In 2022 41st Chin. Control Conf. CCC
2022
[Abs]
[doi]
[pdf]
Prognostics Health and Management (PHM) has become a hot research problem with the improvement of different equipment. Besides, it is significant to assess the health status of equipment in PHM because an accurate health assessment can guide maintenance plans for engineers. To accurately reflect equipment health status by an index, an assessment method based on AHP-CRITIC dynamic weight is proposed in this paper. Analytic Hierarchy Process (AHP) is a subjective method used to evaluate the importance of different indicators. The criteria importance through inter-criteria correlation (CRITIC) method is used to calculate the contrast intensity of the same indicator and the conflict between indicators and obtain the objective weights. A set of more scientific weights is gained by combining the weights obtained from AHP and CRITIC, respectively. Moreover, to reflect each indicator’s real impact on overall health status, a dynamic weight adjustment mechanism is used. The case study of suction nozzles of a specific type of chip mounter shows that this method can reflect the health status accurately.