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.
声信号具有稳定、精确的特点，使用声信号作为目标分类可以使模式识别的领域大大的拓宽。
Acoustic signal is stability and accuracy, so using acoustic signal to classify objects can expand the field of pattern recognition.
现存的基于不变特征的二维模式识别方法在目标被模糊了的情况下都无法精确识别。
The existing approaches to invariant two dimensional pattern recognition are useless when the pattern is blurred.
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