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Speed reducer fatigue acceleration test and residual life prediction method and storage processing system

An accelerated test and life prediction technology, applied in the field of machine learning, can solve the problem of poor accuracy of fatigue life prediction results of reducers

Active Publication Date: 2021-07-06
GUANGZHOU MECHANICAL ENG RES INST +1
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Problems solved by technology

[0005] The purpose of this application is to provide a reducer fatigue acceleration test and remaining life prediction method and storage and processing system in order to solve the accuracy of reducer fatigue life prediction results existing in the prior art. poor problem

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  • Speed reducer fatigue acceleration test and residual life prediction method and storage processing system
  • Speed reducer fatigue acceleration test and residual life prediction method and storage processing system
  • Speed reducer fatigue acceleration test and residual life prediction method and storage processing system

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Embodiment Construction

[0053] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. The drawings are only for the purpose of illustration and description, and are not used to limit the protection scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented in accordance with some embodiments of the application. It should be understood that the operations of the flowcharts may be performed out of order and that steps without logical context may be performed in reverse order or concurrently. In addition, those skilled in the art can add one or more other operations to the flowchart, and can also r...

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Abstract

The invention provides a speed reducer fatigue acceleration test and residual life prediction method and a storage processing system, and relates to the technical field of machine learning. The method comprises the following steps: fatigue performance parameters of a to-be-predicted speed reducer are obtained, the fatigue performance parameters comprise the average fault-free time and the stress cycle number, and the fatigue performance parameters are fatigue life characterization parameters in an ideal state; a performance degradation model of the speed reducer is constructed based on the fatigue performance parameters; a pre-constructed fatigue acceleration model and a pre-constructed performance degradation model are adopted, acceleration factors are screened, an acceleration test is carried out, the fatigue durability of the speed reducer in the current stage and a performance degradation test result are obtained, and the fatigue durability of the current stage comprises the remaining average fault-free time and the remaining stress cycle number; and the residual life of the speed reducer is predicted according to the fatigue durability of the current stage. The method can improve the efficiency and accuracy of residual life prediction of the speed reducer.

Description

technical field [0001] The present application relates to the technical field of machine learning, and in particular, to a reduction gear fatigue acceleration test and remaining life prediction method and storage processing system. Background technique [0002] The precision reducer is a power transmission mechanism, which uses the speed converter of the gear to reduce the number of revolutions of the motor to the required number of revolutions and obtain a larger torque device. As the core component of the robot transmission system, the reducer often bears a huge load during work, and often works uninterruptedly, so the reliability of its work must be strictly required. If it suddenly fails during normal work or degrades and fails when there is no constant attention, it will bring huge troubles to maintenance or maintenance, and even bring huge economic burdens. Therefore, predicting the effective life of the reducer in advance under a reasonable load has become the top pr...

Claims

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Application Information

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IPC IPC(8): G06F30/20G06F30/17G06F119/04
CPCG06F30/20G06F30/17G06F2119/04
Inventor 陈兴彬闵新和李妮妮熊汇捷朱寒张鹏曹伟杜冠廷肖舜仁
Owner GUANGZHOU MECHANICAL ENG RES INST
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