功率谱分析是机械故障诊断技术中精密诊断的常用方法。
Power Spectrum Analysis is a common method for precise detection in mechanical fault diagnosis.
机组运行状态的监测与评估一直是机械故障诊断技术研究的关键。
The condition monitoring and evaluation is one of the key techniques in machinery diagnostics.
故障机理的研究振动信号分析是机械故障诊断技术中采用的最主要的方法之一。
Failure mechanism of vibration signal analysis is the mechanical fault diagnosis technology used in one of the main method.
随后论文介绍了机械故障诊断的理论和技术基础。
Then, this paper introduces the theory and technique of mechanical fault diagnosis.
信号处理技术是旋转机械故障诊断的核心。
The core of rotating machinery fault diagnosis technology is signal processing.
磨损规律和机械故障诊断等研究都离不开磨粒分析技术。
The study of wearing rules and mechanical fault diagnoses is based on wear particle analysis.
在研究数据挖掘技术的基础上，建立了旋转机械故障诊断的特征挖掘模型。
A feature mining model was set up for rotating machine fault diagnosis, based on data mining.
利用面向对象程序设计(OOP)技术实现该模型，使工程机械故障诊断专家系统的诊断效率和适应性得到极大的提高。
The model is realized by the OOP technology, causing the prodigious improvement of the efficiency and the adaptability of the construction machinery's fault-diagnosis expert system.
转子横向裂纹的早期捕捉问题一直是久久困扰现场、在机械故障诊断领域亟待解决的关键技术之一。
The early capturing technique of lateral crack faults is one of the most important techniques to be tackled.
对全息谱技术在回转机械故障诊断、起停车分析以及非稳态信息处理中的应用进行了全面的回顾和总结。
A detailed overview of its applications to fault diagnosis, condition monitoring in run - up and shutdown stages as well as non - stationary vibration is presented.
为此，研究信息融合技术在旋转机械故障诊断中的应用，降低故障诊断的不确定性，提高设备的诊断精度显得尤为必要。
For decreasing uncertainty and improving accuracy of fault diagnosis, it is very necessarily to research the application of information fusion technology in rotating machinery fault diagnosis.
为此，研究信息融合技术在旋转机械故障诊断中的应用，降低故障诊断的不确定性，提高设备的诊断精度显得尤为必要。
For decreasing uncertainty and improving accuracy of fault diagnosis, it is very necessarily to research the application of information fusion technology in rotating machinery fault diagnosis.
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