根据新的目标函数，设计了一种重要点和自底向上分割相结合的时间序列分段线性化趋势特征提取方法。
The existing algorithms to extract trend features based on time series piecewise linearization representation cannot extract completely correct basic trend features of time series.
统计特征提取技术是建议，以便找到一种趋势，检测的缺陷。
A statistical feature extraction technique is proposed in order to find a trend in detection of defects.
对存储的数据可在时域、频域、幅值域进行特征提取、趋势分析以判定故障的位置与性质。
It also can process the stored data in time-domain, frequency-domain and amplitude-domain so as to extract signature, analyze trend and locate the fault.
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