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Fault Identification in Hydraulic Rock Drills from Indirect Measurement During Operation

机译:液压岩钻故障识别在运行过程中间接测量

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This work presents a method for on-line condition monitoring of a hydraulic rock drill, though some of the findings can likely be applied in other applications. A fundamental difficulty for the rock drill application is discussed, namely the similarity between frequencies of internal standing waves and rock drill operation. This results in unpredictable pressure oscillations and superposition, which makes synchronization between measurement and model difficult. To overcome this, a data driven approach is proposed. The number and types of sensors are restricted due to harsh environmental conditions, and only operational data is available. Some faults are shown to be detectable using hand-crafted engineering features, with a direct physical connection to the fault of interest. Such features are easily interpreted and are shown to be robust against disturbances. Other faults are detected by classifying measured signals against a known reference. Dynamic Time Warping is shown to be an efficient way to measure similarity for cyclic signals with stochastic elements from disturbances, wave propagation and different durations, and also for cases with very small differences in measured pressure signals. Together, the two methods enables a step towards condition monitoring of a rock drill, robustly detecting very small changes in behaviour using a minimum amount of sensors.
机译:这项工作提出了一种用于液压钻钻的在线状态监测的方法,但一些发现可能适用于其他应用。讨论了岩石钻应用的基本困难,即内部站立波和凿岩机操作频率之间的相似性。这导致不可预测的压力振荡和叠加,这使得测量和模型之间的同步困难。为了克服这一点,提出了一种数据驱动方法。由于苛刻的环境条件,传感器的数量和类型受到限制,并且只有运营数据可用。使用手工制作的工程特征显示一些故障可检测到可检测的,直接与感兴趣的故障的物理连接。这些特征很容易被解释,并且被证明是稳健的抗扰动。通过对已知参考分类测量信号来检测其他故障。动态时间翘曲被证明是测量具有来自干扰,波传播和不同持续时间的随机元件的循环信号的相似性,以及对于测量压力信号的差异非常小的情况。在一起,这两种方法使得能够迈向岩石钻头的条件监测,鲁棒地检测使用最小量的传感器的行为的非常小的变化。

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