Fault diagnosis of HVAC system with imbalanced data using multi-scale convolution composite neural network

Accurate fault diagnosis of heating,ventilation,and air conditioning(HVAC)systems is of significant importance for maintaining normal operation,reducing energy consumption,and minimizing maintenance costs.However,in practical applications,it is challenging to obtain sufficient fault data for HVAC systems,leading to imbalanced data,where the number of fault samples is much smaller than that of normal samples.Moreover,most existing HVAC system fault diagnosis methods heavily rely on balanced training sets to achieve high fault diagnosis accuracy.Therefore,to address this issue,a composite neural network fault diagnosis model is proposed,which combines SMOTETomek,multi-scale one-dimensional convolutional neural networks(M1DCNN),and support vector machine(SVM).This method first utilizes SMOTETomek to augment the minority class samples in the imbalanced dataset,achieving a balanced number of faulty and normal data.Then,it employs the M1DCNN model to extract feature information from the augmented dataset.Finally,it replaces the original Softmax classifier with an SVM classifier for classification,thus enhancing the fault diagnosis accuracy.Using the SMOTETomek-M1DCNN-SVM method,we conducted fault diagnosis validation on both the ASHRAE RP-1043 dataset and experimental dataset with an imbalance ratio of 1:10.The results demonstrate the superiority of this approach,providing a novel and promising solution for intelligent building management,with accuracy and F1 scores of 98.45%and 100%for the RP-1043 dataset and experimental dataset,respectively.

Review of pantograph and catenary interaction

The application of electrified railway directly promotes relevant studies on pantograph-catenary interac- tion. With the increase of train running speed, the operating conditions for pantograph and catenary have become increasingly complex. This paper reviews the related achievements contributed by groups and institutions around the world. This article specifically focuses on three aspects： The dynamic characteristics of the panto- graph and catenary components, the systems＇ dynamic properties, and the environmental influences on the pantograph-catenary interaction. In accordance with the existing studies, future research may prioritize the task of identifying the mechanism of contact force variation. This kind of study can be carried out by simplifying the pantograph-catenary interaction into a moving load problem and utilizing the theory of matching mechanical impedance. In addition, developing a computational platform that accommodates environmental interferences and multi-field coupling effects is necessary in order to further explore applications based on fundamental studies.