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EMD-based fault diagnosis for abnormal clearance between contacting components in a diesel engine

机译：基于EMD的故障诊断，用于柴油机中接触部件之间的异常间隙

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The accuracy of fault diagnostic systems for diesel engine-type generators relies on a comparison of the currently extracted sensory features with those captured during normal operation or the so-called "baseline." However, the baseline is not easily obtained without the required expertise. Even worse, in an attempt to save costs, many of the diesel engine generators in manufacturing plants are second hand or have been purchased from unknown suppliers, meaning that the baseline is unknown. In this paper, a novel vibration-based fault diagnostic method is developed to identify the vital components of a diesel engine that have abnormal clearance. The advantage of this method is that it does not require the comparison of current operating parameters to those collected as the baseline. First, the nominal baseline is obtained via theoretical modeling rather than being actually captured from the sensory signals in a healthy condition. The abnormal clearance is then determined by inspecting the timing of impacts created by the components that had abnormal clearance during operation. To detect the timing of these impacts from vibration signals accurately, soft-re-sampling and empirical mode decomposition (EMD) techniques are employed. These techniques have integrated with our proposed ranged angle (RA) analysis to form a new ranged angle-empirical mode decomposition method (RA-EMD). To verify the effectiveness of the RA-EMD in detecting the impacts and their times of occurrence, their induced vibrations are collected from a series of generators under normal and faulty engine conditions. The results show that this method is capable of extracting the impacts induced by vibrations and is able to determine their times of occurrence accurately even when the impacts have been overwhelmed by other unrelated vibration signals. With the help of the RA-EMD, clearance-related faults, such as incorrect open and closed valve events, worn piston rings and liners, etc., become detectable even without the comparison to the baseline. Hence, proper remedies can be applied to defective diesel engines to ensure that valuable fuel is not wasted due to the incorrect timing of combustion as well as unexpected fatal breakdown, which may cause loss of production or even human casualties, can be minimized.
机译：用于柴油发动机型发电机的故障诊断系统的准确性取决于将当前提取的感官特征与正常运行或所谓的“基线”中捕获的那些感官特征进行比较。但是，如果没有所需的专业知识，就很难获得基线。更糟糕的是，为了节省成本，制造工厂中的许多柴油发电机都是二手的，或者是从未知的供应商那里购买的，这意味着基准是未知的。本文提出了一种基于振动的新型故障诊断方法，用于识别柴油机具有异常间隙的重要部件。该方法的优点在于，它不需要将当前操作参数与作为基准收集的参数进行比较。首先，标称基线是通过理论模型获得的，而不是在健康条件下实际从感觉信号中捕获的。然后，通过检查运行期间具有异常间隙的组件产生的碰撞的时间来确定异常间隙。为了准确地从振动信号中检测出这些撞击的时间，采用了软重采样和经验模式分解（EMD）技术。这些技术已与我们提出的距离角（RA）分析集成在一起，形成了一种新的距离角-经验模式分解方法（RA-EMD）。为了验证RA-EMD在检测冲击及其发生时间方面的有效性，在正常和故障发动机条件下，从一系列发电机中收集了它们的感应振动。结果表明，该方法能够提取由振动引起的冲击，并且即使在其他无关的振动信号使冲击不堪重负的情况下，也能够准确地确定其发生的时间。在RA-EMD的帮助下，即使不与基线进行比较，也可以检测到与间隙相关的故障，例如不正确的阀门开合，活塞环和衬套磨损等。因此，可以对有缺陷的柴油发动机采取适当的补救措施，以确保不会因不正确的燃烧正时以及有可能导致生产损失甚至人员伤亡的意外致命故障而浪费宝贵的燃料。

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