机械制造与自动化2024，Vol.53Issue(2)：50-55,6.DOI:10.19344/j.cnki.issn1671-5276.2024.02.010
基于GAN-GRU的电梯制动力矩预测方法
Prediction Method of Elevator Braking Torque Based on GAN-GRU
摘要
Abstract
The braking torque of elevator brake is a key parameter affecting the safety of elevator operation.Deep learning algorithm is used to predict it,which can provide an important reference for the safe use and subsequent maintenance of the elevator.Based on the Gated Neural Network(GRU)prediction model,this paper combines it with the basic idea of Generative Adversarial Network(GAN),and uses 1D-CNN as the discriminator to enhance the generalization ability of the elevator braking torque prediction model.The experiment data is applied for training to abtain the prediction result with the root mean square error indicating as 1.024 4.Comparison is conducted with commonly used time series analysis models such as GRU and LSTM,and the results show that the proposed method has obvious advantages in the prediction accuracy of elevator braking torque.关键词
电梯/制动力矩/时间序列分析/生成对抗网络/门控循环神经网络Key words
elevator/braking torque/time series analysis/generate adversarial network/gated recurrent neural networks分类
机械制造引用本文复制引用
苏万斌,江叶峰,易灿灿,徐彪..基于GAN-GRU的电梯制动力矩预测方法[J].机械制造与自动化,2024,53(2):50-55,6.基金项目
国家自然科学基金项目(U1709210,51805382) （U1709210,51805382）
2019年浙江省省级市场监管科研计划项目(20190339) （20190339）
2020年浙江省市场监管局质量技术基础建设项目(20200126) （20200126）
