International Journal of Frontiers in Engineering Technology, 2023, 5(3); doi: 10.25236/IJFET.2023.050305.
Mingmin Jiang, Wen Zhou, Yan Gou
College of Information Engineering, Nanjing University of Finance & Economics, Nanjing, 210023, China
In this paper, we conduct a study on failure prediction of industrial machinery and equipment in order to improve the competitiveness of enterprises. We use Bootstrap to resample the dataset before the experiment. Then, we used four algorithms to build the prediction model, and used GridSearchCV to automatically adjust the parameters and train the equipment records extracted from the dataset. We selected the accuracy, F1 score, and ROC curve as the evaluation indexes of the model, and the evaluation results were compared, so we finally chose the fault prediction model built by LightGBMClassifier algorithm, and then used the confusion matrix to evaluate the model performance.
Fault Prediction; Integrated Learning; Decision Trees; Joint Analysis
Mingmin Jiang, Wen Zhou, Yan Gou. Fault prediction of industrial machinery and equipment. International Journal of Frontiers in Engineering Technology (2023), Vol. 5, Issue 3: 26-31. https://doi.org/10.25236/IJFET.2023.050305.
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