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作 者:赵军 孙云岭[2] 徐孙庆 Zhao Jun;Sun Yunling;Xu Sunqing(Unit 9249360th Squadron,Huludao,Liaoning 125000,China;Naval University of Engineering,Wuhan 430030,China)
机构地区:[1]92493部队60分队,辽宁葫芦岛125000 [2]海军工程大学,武汉430030
出 处:《机电工程技术》2024年第7期130-132,共3页Mechanical & Electrical Engineering Technology
摘 要:通过在线监控柴油机瞬时转速信号,进一步研究与柴油机燃烧有关的故障诊断,已成为柴油机故障诊断技术中最有应用价值的技术之一。但是,柴油机结构复杂导致瞬时转速的波动变化复杂,信息辨识困难,尤其是在柴油机早期故障的瞬时转速特征信息提取难度较大。针对瞬时转速在柴油机早期故障中信号微弱,故障特征提取困难,而传统的故障特征优化方法在处理柴油机瞬时转速数据时,存在准确率不高、效率底下等问题,引用遗传算法对柴油机瞬时转速信号6个较能反映故障的无量纲化特征参数作为原始特征进行提取优化,得到最佳特征参数,用以故障诊断,通过故障模拟实验验证了遗传算法在优化柴油机瞬时转速故障特征上的有效性,对于超过15%幅度的功率不平衡性故障,使用瞬时转速信号可以进行准确诊断。Studying fault diagnosis related to diesel engine combustion through online monitoring of instantaneous speed signals is one of the most practical and valuable technologies in diesel engine fault diagnosis in recent years.However,the complex structure of diesel engines leads to complex fluctuations and changes in instantaneous speed,making information identification difficult,especially in the extraction of instantaneous speed feature information for early faults in diesel engines.The weak signal of instantaneous speed in early faults of diesel engines is focused on,making it difficult to extract fault features.However,traditional fault feature optimization methods have problems such as low accuracy and low efficiency when processing instantaneous speed data of diesel engines.Six dimensionless feature parameters are extracted and optimized using a genetic algorithm,offering optimal parameters for diagnosing faults in diesel engine instantaneous speed signals.Through conducting fault simulation experiments,the effectiveness of this genetic algorithm in optimizing these specific fault features is confirmed.For power imbalance faults exceeding 15% amplitude,accurate diagnosis can be achieved using instantaneous speed signals.
分 类 号:TK428[动力工程及工程热物理—动力机械及工程]
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