对滚动轴承的故障模式识别方法进行了研究。
最后将粒子群算法优化神经网络引入故障模式识别中。
Finally, the paper used particle swarm optimized neural network into fault pattern recognition.
将灰色系统理论应用于设备的故障诊断，较好地解决了设备状态预测和故障模式识别的问题。
By applying the theory of grey system to diagnosing equipment breakdown, the problems of state prediction and trouble-mode recognition of equipment can be solved.
针对电机振动信号的频谱特点，提出基于小波神经网络技术的电机故障模式识别与诊断的新方法。
A novel method of pattern recognition and fault diagnosis in electrical machine based on the wavelet-neural network is proposed according to the frequency spectrum characteristics of vibration signal.
结果表明，以CP神经网络构筑的故障模式识别器有很强的非线性映射能力，可对机械设备故障模式进行正确分类。
The result indicates that based on CP neural network, the fault pattern recognition system has strong nonlinear mapping ability, therefore it can be used to correctly classify the mechanical faults.
此模型可用于模式识别和故障诊断。
This model can apply to pattern identification and fault diagnosis.
应用模糊模式识别方法及最大隶属原则，建立了凝汽器故障诊断模型，并以实例验证该模型识别故障的准确性。
By applying fuzzy pattern recognition and maximum membership rule, fault diagnosis model for condenser has been established and its accuracy for identifying faults is tested and verified.
AFS理论已初步应用于数据挖掘，模式识别，故障诊断等领域。
AFS theory has been applied to data mining, pattern recognition and failure diagnosis.
深入探讨并初步解决了根据元件软故障的统一特性，采用人工智能方法实现软故障的模式识别诊断的问题。
The article discusses problem of solving the soft fault diagnosis by artificial intelligence according to the invariable general characterization of the component in the circuit.
故障诊断是计算机模式识别领域的一个活跃课题。
Fault diagnosis is an active subject in the area of computer pattern recognition.
该文介绍了BP网络的学习过程以及从模式识别角度应用BP神经网络作为分类器进行机械故障诊断。
The paper introduces the studying process of the BP network and USES the BP network for the mechanical failure diagnoses as assorted organ in the mode identification.
局部放电模式识别是一种高电压设备绝缘故障诊断的有效方法。
Partial discharge pattern recognition is considered as an effective tool for insulation fault diagnosis on high voltage electric equipment.
该系统能实现模式识别、故障诊断、多目标优化等功能。
Many functions such as pattern recognition, fault diagnosis and multi-objective optimization could be realized by the system.
声音模式识别在无人职守、故障检测、灾害预防等方面具有很广阔的应用前景。
Voice pattern recognition has broad prospects of application in unmanned guard, defect detecting, disaster-preventing and so on.
目前，粗糙集理论已被成功地应用在人工智能、机器学习、数据挖掘、决策支持与分析、过程控制、模式识别、故障检测等领域。
Currently, RST has been applied in many fields as artificial intelligence, machine learning, data mining, decision support and analysis, process control, pattern recognition, fault detection.
目前已经将AFS理论成功的应用在聚类分析、模式识别和故障诊断等领域。
Currently the AFS theory has been applied in the many realms successfully, such as cluster analysis, pattern recognition and hitch diagnosis etc.
近年来，人工神经网络广泛应用于故障诊断、模式识别、水文预报等领域。
In recent years, artificial neural network is widely applied in breakdown diagnosis, pattern recognition, hydrology forecast and so on.
试验表明，该系统可以获得不同缺陷电容器发生局部放电时放电幅值的时间分布谱图，这为直流局部放电的统计分析和模式识别、判断故障类型和介质老化程度打下了良好的基础。
Through the experiments, the magnitude of PD over time in different capacitors were got, which would be used to recognize the PD patterns and to determine fault types and aging degree.
归纳了支持向量机在诸如模式识别、函数逼近、时间序列预测、故障预测和识别、信息安全、电力系统以及电力电子领域中的应用。
SVM applications, such as pattern recognition, function approaching, time series prediction, fault prediction and recognition, information security, power system and power electronics, are described.
该方法利用模式识别中的近邻准则，使用元胞蚂蚁算法实现故障的分类，达到故障诊断的目的。
The method realizes classification of fault by near-neighborhood criteria of pattern recognition and cellular ant algorithm.
提出了一种基于核的多类别模式识别算法(简称核子空间法，KSPM)，依据此算法建立了多故障分类器。
A novel multi-class classifier with kernels, namely kernel Subspace Methods (KSPM), was presented, and a multi-fault classifier based on the algorithm was constructed.
介绍了凝汽器的故障诊断常用的三种诊断方法，BP神经网络法、模糊诊断法、模糊模式识别法。
This paper introduces three kinds of commonly used diagnosis methods, which are BP neural network method, fuzzy diagnosis method and, fuzzy pattern recognition method.
现已在图像处理、人工智能、计算机识别、模式识别与分类、故障检测等方面得到了广泛应用。
Edge detection has been extensively applied in a lot of fields, such as image processing, artificial intelligence, computer recognition, pattern recognition and classification, fault detection etc.
本文根据机械设备故障诊断系统的特性和现有诊断方法的不足，阐述了基于模式识别的故障诊断方法。
Considering the characteristics of the mechanical equipment and the weakness of the existing diagnosis methods, a new failure detection based on recognition analysis is defined.
综合信号处理及模式识别理论，根据柴油机振动信号的特点，提出了一种柴油机气门故障诊断综合方法。
A new diagnosis method for diesel engine faults is presented, which is based on the principle of mixing signal processing and model-recognition.
通过实验提取一些常见故障模式的特性曲线，运用BP神经网络，实现了电液伺服阀的故障诊断和模式识别。
We picked the characteristic curve of the usual fault modal by the experiment and applied a BP network in fault diagnosis. And then we completed the fault diagnosis and modal identification.
对齿轮箱做振动测试和分析，通过模式识别找到齿轮箱损坏时呈现的特性，为齿轮箱故障诊断提供依据。
Vibration data acquisition and signal processing has been done for gear box, by criterion of fault model, we find the characteristic of fault gear box and make contribution to fault diagnosis for it.
试验结果表明，所提出的故障诊断方法能够较精确实现滚动轴承多部位的单一、复合故障的定位和模式识别，效果明显好于单一网络。
The results show that this method is available to recognize the fault location and pattern accurately and better than that without knowledge increase ability.
试验结果表明，所提出的故障诊断方法能够较精确实现滚动轴承多部位的单一、复合故障的定位和模式识别，效果明显好于单一网络。
The results show that this method is available to recognize the fault location and pattern accurately and better than that without knowledge increase ability.
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