In this paper, a new method for vibration fault diagnosis of large steam turbine-generation is proposed based on theory of adaptive wavelet network(AWN). A special adaptive wavelet network classifier for arbitrary nonlinear system is developed, algorithm of back propagation type is proposed. By means of computer simulation and with applying to fault diagnosis, and the performance of the AWN are compared with that of the conventional multilayer perception. The results show that this method has better diagnostic, faster speed of learning properties and it is an efficient new method. And then some important related elements, which affect the performance of classification AWN is analyzed, conclusions that are of great importance in real application, are obtained.

采用一种高分子薄膜电容式湿度传感器做为测量系统的感湿元件实现SF6气体中微水含量的在线测量，并通过温度补偿、曲线拟合等方法提高测量的准确性。模拟试验结果表明：研究的在线监测系统能反映SF6气体中微水含量的变化，为在线监测系统的现场实施提供了良好的技术基础。

变压器油中溶解气体在线监测对变压器绝缘状态分析具有积极的指导作用，在线监测用气体传感器是实施该技术的关键。本文针对半导体气体传感器的交叉敏感特性，提出了将气体传感器阵列与人工神经网络技术相结合，形成一种智能传感器，用于单一气体的定性识别和定量检测；利用六个半导体气体传感器组成传感器阵列，采用BP神经网络进行模式识别。通过大量的试验证明了本文提出的智能传感器可有效提高H2、CO、CH4、C2H4、C2H2、C2H6六种气体的分辨率和检测灵敏度。

This paper illustrates the methods of extracting instinct parameters and deformation recognition by using wavelet transform, which applied in low voltage impulse(LVI) method on the transformer winding deformation detection. The results shows that it is effective to eliminate the noises by using wavelet transform, meanwhile, it can also make measurement repetitive and has a property on model recognition on deformation.

This paper illustrates the methods of extracting instinct parameters and deformation recognition by using wavelet transform, which applied in low voltage impulse(LVI) method on the transformer winding deformation detection. The results shows that it is effective to eliminate the noises by using wavelet transform, meanwhile, it can also make measurement repetitive and has a property on model recognition on deformation.