Memory attitude monitoring method for hydraulic support based on grey theory
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摘要: 针对现有液压支架监测方法大多只能监测单台支架、无法对成组液压支架监测数据进行融合分析、监测数据利用率低等问题，提出了一种基于灰色理论的液压支架记忆姿态监测方法。该方法采用灰色理论，根据液压支架记忆姿态监测值得出记忆姿态相关参数预测值；可根据监测到的同一个循环内前几台液压支架实际姿态预测下一台液压支架姿态，实现横向循环监测，也可根据前几个循环的液压支架实际姿态预测下一循环内该液压支架姿态，实现纵向循环监测。液压支架支撑高度监测试验结果表明，该方法对于液压支架记忆姿态的预测值与实际值相差不大，验证了该方法的有效性。Abstract: Existing hydraulic support monitoring methods can only monitor single support without fusion analysis of monitoring data of united hydraulic supports and have low utilization ratio of monitoring data. For above problems, a memory attitude monitoring method for hydraulic support based on grey theory was proposed. The method calculates predictive value of related memory attitude parameters according to monitored value of memory attitude of hydraulic support by use of grey theory. It can predict attitude of the next hydraulic support according to actual attitude of previous hydraulic supports in the same monitoring cycle, so as to realize horizontal cycle monitoring, and also predict attitude of a hydraulic support in the next monitoring cycle according to actual attitude of the hydraulic support in the last few cycles, so as to realize longitudinal cycle monitoring. The support height of hydraulic support monitoring test results show that predictive value of memory attitude of hydraulic support is similar to the actual value, which verifies the validity of the method.
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期刊类型引用(4)
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