Peridinamik Tabanlı Bulanık Mantık Algoritması Yardımıyla Ray Yüzeyindeki Kusurların Tam Spektrum Görüntü İşleme ile Tespiti

Bu çalışmada tam spektrum görüntü üzerinden ray kusurlarının belirlenmesine yönelik peridinamik tabanlı bulanık mantık algoritması geliştirilmiştir. Örnek uygulama için tam spektrum ray kusuru görüntüsünün, gri skala tanım kümesinde Gaussian maskelemesi gerçekleştirilmiş, görüntünün farklı boyut ve mertebelerden türev alma işlemleri peridinamik sayısal türev alma metodu kullanılarak elde edilmitşir. Alınan türevler bulanık mantık sisteminde değerlendiriltikten sonra görüntünün RGB ve HSV skalaları üzerinde üç temel dalga boyu dönüşümü yapılmıştır. Bulanık mantık çıktısı üzerine tatbik edilen en etkin üç dalga boyu ile ortak noktaların tespiti gerçekleştirilerek ray kusurlarının daha belirgin bir şekilde ortaya çıkması sağlanmıştır. Ayrıca üç farklı tam spektrum örnek ray kusur görüntüsü ile geliştirilen algoritma test edilip, literatürdeki mevcut kenar bulma algoritmalarına göre daha iyi sonuç verdiği tespit edilmiştir

Online Condition Monitoring of a Rail Fastening System on High-Speed Railways Based on Wavelet Packet Analysis

The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management

Online Condition Monitoring of a Rail Fastening System on High-Speed Railways Based on Wavelet Packet Analysis

The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management