Heavy-haul railways play a vital role in freight transportation,and the health of the rails directly impacts the safety and efficiency of railway operations.The heavy axle loads and long train compositions of heavy-ha...Heavy-haul railways play a vital role in freight transportation,and the health of the rails directly impacts the safety and efficiency of railway operations.The heavy axle loads and long train compositions of heavy-haul trains make the rail surface susceptible to damage such as rail corrugation,spalling and abrasion,threatening operational safety.To address the issue,this paper proposes a multi-source data fusion method for identifying rail surface defects on heavy-haul railways.First,complete ensemble empirical mode decomposition with adaptive noise is used to decompose vibration signals and extract multi-dimensional vibration features.Next,dynamic time warping is applied to align rail profile data and extract key geometric features.Then,the vibration features and profile features are fused using Relief-F to select the most discriminative features.Finally,a support vector machine is utilized for defect identification.Experiment results show that the proposed method achieves high accuracy in identifying rail surface defects,with an accuracy of 96.4%.展开更多
Aiming at the problems of single classification method and high classification cost of kiwifruit in China,we proposed a grading method based on kiwifruit surface defects.A set of kiwifruit image acquisition system was...Aiming at the problems of single classification method and high classification cost of kiwifruit in China,we proposed a grading method based on kiwifruit surface defects.A set of kiwifruit image acquisition system was built.The K-means clustering segmentation algorithm was used to segment the surface defects,and then color contrast was performed to determine whether it was a piece of defective fruit.Then,the shape features of normal fruit were extracted and an SVM classifier was designed to further determine its grade.This method has the advantages of low cost,simple algorithm and high efficiency,which opens a new way for fruit classification,and is of great significance to promoting the development of fruit classification industry in China and enhancing international competitiveness.展开更多
基金supported by the National Key R&D Program of China(No.2021YFF0501102)the National Natural Science Foundation of China(Grants No.52202392,U2368202,52372308,U2468203 and U2468206).
文摘Heavy-haul railways play a vital role in freight transportation,and the health of the rails directly impacts the safety and efficiency of railway operations.The heavy axle loads and long train compositions of heavy-haul trains make the rail surface susceptible to damage such as rail corrugation,spalling and abrasion,threatening operational safety.To address the issue,this paper proposes a multi-source data fusion method for identifying rail surface defects on heavy-haul railways.First,complete ensemble empirical mode decomposition with adaptive noise is used to decompose vibration signals and extract multi-dimensional vibration features.Next,dynamic time warping is applied to align rail profile data and extract key geometric features.Then,the vibration features and profile features are fused using Relief-F to select the most discriminative features.Finally,a support vector machine is utilized for defect identification.Experiment results show that the proposed method achieves high accuracy in identifying rail surface defects,with an accuracy of 96.4%.
基金Supported by the Chinese Society of Logistics(2021CSLKT3-286)。
文摘Aiming at the problems of single classification method and high classification cost of kiwifruit in China,we proposed a grading method based on kiwifruit surface defects.A set of kiwifruit image acquisition system was built.The K-means clustering segmentation algorithm was used to segment the surface defects,and then color contrast was performed to determine whether it was a piece of defective fruit.Then,the shape features of normal fruit were extracted and an SVM classifier was designed to further determine its grade.This method has the advantages of low cost,simple algorithm and high efficiency,which opens a new way for fruit classification,and is of great significance to promoting the development of fruit classification industry in China and enhancing international competitiveness.
