| 基于切削力的刀具故障诊断 |
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| 引用本文： | 王细洋,李智华,张晓荣.基于切削力的刀具故障诊断[J].工具技术,2006,40(10):45-47. |
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| 作者姓名： | 王细洋 李智华 张晓荣 |
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| 作者单位： | 1. 南昌航空工业学院机械工程系,330034,南昌市
2. 南昌航空工业学院 |
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| 基金项目： | 江西省材料科学与工程中心资助项目 |
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| 摘 要： | 提出和实现了一种基于切削力状态参量判别刀具故障的方法。利用LabVIEW软件平台采集和分析切削力信号。调用MatLAB中的小波包工具将信号分解,并计算各频段的能量谱,输入BP神经网络进行训练。将经过训练后的BP网络用于对刀具故障进行诊断,并给出了应用实例。
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| 关 键 词： | 故障诊断 金属切削 小波包分析 BP神经网络 |
| 收稿时间： | 2005-04 |
| 修稿时间： | 2005-04 |
Research on malfunction diagnosis of cutting tool based on cutting force |
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| Wang Xiyang,Li Zhihua,Zhang Xiaorong.Research on malfunction diagnosis of cutting tool based on cutting force[J].Tool Engineering(The Magazine for Cutting & Measuring Engineering),2006,40(10):45-47. |
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| Authors: | Wang Xiyang Li Zhihua Zhang Xiaorong |
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| Affiliation: | Wang Xiyang Li Zhihua Zhang Xiaorong |
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| Abstract: | An approach to diagnosing the malfunction of cutting tool based on cutting force is presented. The cutting force signal is transformed by the wavelet packet tool of MatLAB and decomposed into the energy in several frequency bands. The BP neural network trained by the energy vectors is used to diagnosis cutting malfunction. The example of diagnosis is introduced. |
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| Keywords: | malfunction diagnosis metal cutting wavelet packet transformation BP neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
