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Effective combination of motor fault diagnosis techniques

机译:电机故障诊断技术的有效结合

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Induction motors are widely used across all the industries and accounts for major source of energy consumption. Inception of faults in motors may reduce its operational efficiency. Over a period of time, the propagation of fault in the motor may leads to the further drop in the efficiency. Various motor fault diagnosis techniques which use current signal, vibration signal and infrared thermography (IRT) to diagnose motor fault prior to its failure are available. Inspite of all these fault diagnosis techniques still failure of induction motor are reported in industries. The main reason is the mismanagement of the available fault diagnosis technique. No single fault diagnosis technique is effective in diagnosing every fault present in the motor. Therefore, a combination of these techniques is required to diagnose fault effectively. This paper proposed an effective combination of two fault diagnosis technique which could diagnose most of motor faults. Fuzzy arithmetic operation is used to identify this effective combination which helps in increasing motor availability and reduces downtime cost.
机译:感应电动机在所有行业中被广泛使用,并且是主要的能源消耗来源。电机出现故障可能会降低其运行效率。在一段时间内,电动机中的故障传播可能导致效率进一步下降。提供了各种电机故障诊断技术,这些技术使用电流信号,振动信号和红外热成像(IRT)来在电机故障之前进行诊断。尽管有所有这些故障诊断技术,但仍在工业中报告了感应电动机的故障。主要原因是现有故障诊断技术管理不善。没有任何一种故障诊断技术可以有效地诊断电动机中存在的每个故障。因此,需要将这些技术结合起来才能有效地诊断故障。本文提出了两种故障诊断技术的有效组合,可以诊断大多数电动机故障。模糊算术运算用于确定这种有效的组合,这有助于增加电动机的可用性并减少停机时间的成本。

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