基于功率信息的机床设备综合效率智能识别方法
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作者单位:

1.重庆大学;2.重庆邮电大学

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基金项目:

国家自然科学基金青年基金(NO.51805066);国家自然科学基金面上项目(NO.51975076);重庆市自然科学基金(NO. cstc2018jcyjAX0579)


An intelligent identification approach of overall equipment effectiveness for machine tool based on power information
Author:
Affiliation:

1.Chongqing University;2.Chongqing University of Posts and Telecommunications;3.Chongqing university

Fund Project:

National Natural Science Foundation of China (NSFC) (NO.51805066), National Natural Science Foundation of China (NSFC) (NO.51975076), Natural Science Foundation of Chongqing (NO. cstc2018jcyjAX0579)

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    摘要:

    机床作为工业母机,其量大面广,但存在能耗高、设备综合效率低等问题。针对传统方法在获取时间稼动率、性能稼动率和产品合格率指标时存在难度大、成本高、普适性差的缺点,提出了一种基于功率信息的设备综合效率智能识别方法。首先获取机床功率信息时频域特征,构建采样周期特征向量,并采用主成分分析构建状态匹配库,结合最近邻算法识别运行状态,量化运行状态持续时间,计算时间稼动率;同时借助滑动移窗构建加工周期特征向量,采用距离匹配获取实际加工件数,结合MES系统计算性能稼动率与产品合格率。最后,以铣削加工为例,其设备综合效率理论值与实际值相对误差为4.99%,验证了该方法的可行性与实用性。

    Abstract:

    Machine tool, as the mother machine, has been wildly employed in manufacturing industry, which consumed a large amount of energy with low overall equipment effectiveness (OEE). The conventional approaches have the disadvantages of inconvenience, high cost and poor universality in calculating the availability, performance and quality rate indicators of OEE. Hence, an intelligent identification approach of OEE based on power information is proposed. Firstly, the time-frequency characteristics of machine tool power information were obtained, and the sampling period feature vector was established. Then, the principal component analysis was employed to construct the status matching library. Combined with the nearest neighbor algorithm, the running status was identified, and its duration was quantified to calculate the availability. In addition, the sliding window was applied to develop the processing period feature vector, and the distance matching was used to obtain the actual number of processing pieces. The performance and quality rate were calculated through combining the MES system. To verify the feasibility and practicability of the approach, the experimental study of the milling was performed, and the relative error between the theoretical value and the actual value is 4.99%.

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  • 收稿日期:2021-02-04
  • 最后修改日期:2021-04-08
  • 录用日期:2021-04-09
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