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.
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。
Aimed at solving the challenging problem of diagnosis for sensor bias and drift faults, a novel approach of sensor fault diagnosis based on generalized regression neural network (GRNN) is proposed.
针对诊断传感器偏置故障与漂移故障的难点问题，提出了一种基于广义回归神经网络(GRNN)的传感器故障诊断方法。
However, support vector machine (SVM) can better solve problem of small-sample learning and provides the foundation for solving intelligent diagnosis problems.
而支持向量机能够较好地解决小样本学习问题，为解决智能诊断的这一问题提供了基础。
The system is open, knowledge sharing. Resources from different developer cooperate to solve the diagnosis problem, so that the ability of problem solving is enhanced.
所设计的系统具有良好的开放性，实现了资源共享，使来源不同的诊断资源能相互协作，共同解决诊断问题，使诊断系统的求解能力得到提高。
For solving the fault diagnosis problem of chemical processes, a new kind of distributed (cooperative) fault diagnosis model based on multi-agent system is provided.
针对化工过程的故障诊断问题，给出了分布式化工过程故障诊断问题的多智能体的合作求解模型。
For solving the fault diagnosis problem of chemical processes, a new kind of distributed (cooperative) fault diagnosis model based on multi-agent system is provided.
针对化工过程的故障诊断问题，给出了分布式化工过程故障诊断问题的多智能体的合作求解模型。
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