基于PCA的采煤机健康状态云模型评估分析  

Cloud model evaluation for health state of coal shearer based on PCA

作　　者：闫向彤[1] 董鹏辉 熊友錕 张健 YAN Xiangtong;DONG Penghui;XIONG Youkun;ZHANG Jian(School of Mechanical Engineering,Xi′an University of Science and Technology,Xi′an 710054,China)

机构地区：[1]西安科技大学机械工程学院,陕西西安710054

出　　处：《煤炭工程》2023年第6期152-157,共6页Coal Engineering

基　　金：国家自然科学基金项目(51875451)。

摘　　要：为了有效评估采煤机健康状态,本研究提出了一种基于PCA和云模型的采煤机健康状态评估方法。以某矿场采煤机作为研究背景,选取截割部、牵引部、变频部、调高调压四个方面共10个影响因素作为评价指标,建立采煤机健康状态评价体系;为了避免决策者的主观影响,本研究从定量角度对采煤机健康状态进行评估,运用PCA对数据进行降维并计算各指标权重,构建基于云理论的采煤机健康状态云模型,依据云模型特征参数确定采煤机健康状态等级。通过实例分析表明,基于PCA的采煤机健康状态云模型评估方法可准确的判断当前采煤机的健康状态,为煤矿企业安排维护计划提供一定的参考。In order to effectively evaluate the health status of shearer,a health status evaluation model based on PCA and cloud model is proposed.Taking the shearer in a mine as the research background,10 influencing factors from four aspects of cutting department,traction department,frequency conversion department and height and pressure regulation are selected as the evaluation indexes to establish the health status evaluation system.In order to avoid the subjective influence of decisionmakers,the shearer health state is evaluated from a quantitative point of view,and PCA is applied to reduce the data dimension and the weight of each index is calculated.A shearer health state cloud model is constructed based on cloud theory,and the health state level is determined according to the characteristic parameters of the cloud model.The results show that the cloud model evaluation method can accurately judge the current shearer health state,and provide a certain reference for coal mining enterprises to arrange maintenance plans.

关 键 词：采煤机 评价指标 健康状态评估 PCA 云模型 

分 类 号：TD-05[矿业工程]