Cutter wear prediction method based on multivariate fast iterative filtering decomposition method

• Main Authors: MENG ZHANBIN, MIAO ZHIBIN, DENG JUNLIN, YIN ZAIHANG, CONG XIAOHONG
• Format: Patent
• Language: Chinese; English
• Published: 27.12.2022
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS

The invention discloses a tool wear prediction method based on a multivariate fast iterative filtering decomposition method, and relates to the field of tool wear prediction. Comprising the following steps: S1, establishing a wear prediction model based on a support vector machine model; s2, acquiring an original machining signal in the milling process of the machine tool through a three-way vibration sensor arranged on a main shaft of the machine tool; s3, decomposing the original processing signal by using a multivariate rapid iterative filtering decomposition method to obtain a plurality of multi-channel intrinsic mode components; on the basis of an indirect monitoring method, the abrasion condition of the cutter can be predicted in the mechanical milling process of the cutter, equipment does not need to be shut down and restarted, the milling precision error caused by frequent shutdown and cutter dismounting is reduced, the cutter detection time can be shortened, and the production efficiency cannot be af