| 1. | New fault recognition method based on multivariate statistical process control
基于多元统计过程控制的故障识别方法 |
| 2. | Then analyze the reason to fault recognition according to the recognition result
论文还根据识别结果，和实验现象，分析了出现误判的原因。 |
| 3. | Fault recognition of automotive transmission based on wavelet packet decomposition and neural network
小波包分解与神经网络相结合的变速箱齿轮故障识别 |
| 4. | To facilitate rapid reaction times , fault recognition is usually carried out by newly developed mechanisms
为了方便快速识别错误，故障识别通常采用新机制。 |
| 5. | Then the inefficiency on fault recognition based on multivariate statistical process control is presented
指出了多元统计过程控制在故障识别上能力的不足。 |
| 6. | The reliable standard image acquiring algorithm and fault recognition algorithm were designed . these algorithms are also putted into use to settle the problems
设计了可靠的标准图像采集算法、故障识别算法并将其用于解决实际问题。 |
| 7. | 3 . to enhance the ability of fault recognition , a new method for searching the fault origin from the multivariate statistical aspect is presented
为了提高多元统计过程控制的故障识别能力，提出了一种基于多元统计过程控制的识别故障源的新方法。 |
| 8. | " energy - fault recognition " , a fault diagnosis method based on wavelet packets analysis for the transport pipeline supervising system is proposed in this dissertation . eigenvector target is presented which reflect the characteristic of leakage pressure signal
本文将基于小波包分析的“能量?故障识别”故障诊断方法引入管道运行状态监测技术，提出了反映泄漏压力信号特性的特征向量指标。 |
| 9. | According to this we can get fault types . whereas the disfigurement and limitation of the fault recognition methods at present and the application background of neural network , the design uses the rbf neural network to recognize fault types . to solve the problems of memory of f149 and training speed or real time recognitions , the design adopts several previous coefficient of dct to describe the input samples of the neural network
鉴于目前油井工况模式识别方法的缺陷和局限性以及神经网络的应用背景,设计了用rbf神经网络和dct相结合的方法实现实时对油井工况模式的识别,解决了单片机存储空间、训练速度和实时识别两方面的问题,提高了主机的控制和处理能力。 |
