Let G be a countable discrete infinite amenable group which acts continuously on a compact metric space X and let μ be an ergodic G-invariant Borel probability measure on X. For a fixed tempered F?lner sequence {Fn} ...Let G be a countable discrete infinite amenable group which acts continuously on a compact metric space X and let μ be an ergodic G-invariant Borel probability measure on X. For a fixed tempered F?lner sequence {Fn} in G with limn→+∞|Fn|/log n= ∞, we prove the following result:h_top^B(G_μ, {F_n}) = h_μ(X, G),where G_μ is the set of generic points for μ with respect to {F_n} and h_top^B(G_μ, {F_n}) is the Bowen topological entropy(along {F_n}) on G_μ. This generalizes the classical result of Bowen(1973).展开更多
Condition monitoring of railway point machines is important for train operation safety and effectiveness.Referring to the fields of mechanical equipment fault detection,this paper proposes a fault detection and identi...Condition monitoring of railway point machines is important for train operation safety and effectiveness.Referring to the fields of mechanical equipment fault detection,this paper proposes a fault detection and identification strategy of railway point machines via vibration signals.A comprehensive feature distilling approach by combining variational mode decomposition(VMD)energy entropy and time-and frequency-domain statistical features is presented,which is more effective than single type of feature.The optimal set of features was selected with ReliefF,which helps improve the diagnosis accuracy.Support vector machine(SVM),which is suitable for a small sample,is adopted to realize diagnosis.The diagnosis accuracy of the proposed method reaches 100%,and its effectiveness is verified by experiment comparisons.In this paper,vibration signals are creatively adopted for fault diagnosis of railway point machines.The presented method can help guide field maintenance staff and also provide reference for fault diagnosis of other equipment.展开更多
基金supported by National Basic Research Program of China (Grant No. 2013CB834100)National Natural Science Foundation of China (Grant Nos. 11271191 and 11431012)
文摘Let G be a countable discrete infinite amenable group which acts continuously on a compact metric space X and let μ be an ergodic G-invariant Borel probability measure on X. For a fixed tempered F?lner sequence {Fn} in G with limn→+∞|Fn|/log n= ∞, we prove the following result:h_top^B(G_μ, {F_n}) = h_μ(X, G),where G_μ is the set of generic points for μ with respect to {F_n} and h_top^B(G_μ, {F_n}) is the Bowen topological entropy(along {F_n}) on G_μ. This generalizes the classical result of Bowen(1973).
基金supported by National Key R&D Program of China (Grant No.2021YFF0501102)National Natural Science Foundation of China (Grant Nos.U1934219,52202392 and 52022010)+1 种基金National Natural Science Foundation of China (Grant No.62120106011)Fundamental Research Funds for the Central Universities (Grant No.2021RC276).
文摘Condition monitoring of railway point machines is important for train operation safety and effectiveness.Referring to the fields of mechanical equipment fault detection,this paper proposes a fault detection and identification strategy of railway point machines via vibration signals.A comprehensive feature distilling approach by combining variational mode decomposition(VMD)energy entropy and time-and frequency-domain statistical features is presented,which is more effective than single type of feature.The optimal set of features was selected with ReliefF,which helps improve the diagnosis accuracy.Support vector machine(SVM),which is suitable for a small sample,is adopted to realize diagnosis.The diagnosis accuracy of the proposed method reaches 100%,and its effectiveness is verified by experiment comparisons.In this paper,vibration signals are creatively adopted for fault diagnosis of railway point machines.The presented method can help guide field maintenance staff and also provide reference for fault diagnosis of other equipment.
