Abstract
The incorporation of ultrasonic and moisture sensors represents a significant advancement in railway track maintenance, offering a comprehensive and efficient means of assessing conditions, reducing time, and eliminating manual labor. Mounted on a trolley, these sensors simultaneously measure ballast cushion availability, moisture content, and humidity, providing real-time data stored in a cloud-based account for effective management. This data enables proactive maintenance, calculating ballast requirements using artificial intelligence during normal trolley runs. The system enhances safety and performance by assessing ballast availability and deficiencies along the track. Variations in defect lengths are evident between zones; for instance, the mud pumping zone ranges from 2 to 38 m with an average of 19 m and peak moisture content at 35 %. In contrast, zones with high freightage and track density exhibit more consistent defect lengths, averaging 13 and 10 m respectively, with moisture contents between 5 % and 15 %. The study emphasizes the necessity for tailored maintenance plans for each zone to ensure railway infrastructure effectiveness and safety.
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