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On-line detection algorithm of ore grade change in grinding grading system
Open Physics ( IF 1.9 ) Pub Date : 2020-11-07 , DOI: 10.1515/phys-2020-0142
Jianjun Zhao 1, 2 , Junwu Zhou 2, 3
Affiliation  

Abstract In process industry control, process data is critical for both control and fault diagnosis. Timely detection of outliers and mutation point in process data can quickly adjust control parameters or discover potential failures throughout the system. Aiming at the shortcomings of the traditional mutation point detection method, such as the detection time delay and not being suitable for the process industrial data that mixed outliers, this paper proposes a mutation point and outliers detection method that is suitable for the grinding grading system using the wavelet method to analyze the “Efficient Scoring Vector.” In this algorithm, to distinguish between outliers and mutation points in the detection process, we propose a detection framework based on the relationship between Lipschitz index and wavelet coefficients. Under this framework, the detection algorithm proposed in this paper can detect outliers and mutation points simultaneously. The advantage of this is that the accuracy of the mutation point detection is not affected by the outliers. This means that the method can process grinding grading system process data containing outliers and mutation points under actual operating conditions and is more suitable for practical applications. Finally, the effectiveness and practicability of the proposed detection method are proved by simulation results.

中文翻译:

磨矿分级系统矿石品位变化在线检测算法

摘要 在过程工业控制中,过程数据对于控制和故障诊断都至关重要。及时检测过程数据中的异常值和突变点,可以快速调整控制参数或发现整个系统的潜在故障。针对传统突变点检测方法存在检测时间延迟、不适合混合异常值的过程工业数据等缺点,提出一种适用于磨矿分级系统的突变点和异常值检测方法。小波方法分析“有效评分向量”。在该算法中,为了区分检测过程中的异常点和突变点,我们提出了一种基于Lipschitz指数和小波系数之间关系的检测框架。在这个框架下,本文提出的检测算法可以同时检测异常点和变异点。这样做的好处是突变点检测的准确性不受异常值的影响。这意味着该方法可以处理实际工况下含有异常值和突变点的磨矿分级系统工艺数据,更适合实际应用。最后,仿真结果证明了所提出的检测方法的有效性和实用性。这意味着该方法可以处理实际工况下含有异常值和突变点的磨矿分级系统工艺数据,更适合实际应用。最后,仿真结果证明了所提出的检测方法的有效性和实用性。这意味着该方法可以处理实际工况下含有异常值和突变点的磨矿分级系统工艺数据,更适合实际应用。最后,仿真结果证明了所提出的检测方法的有效性和实用性。
更新日期:2020-11-07
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