From automated visual inspection and data analysis to maintenance optimization through artificial intelligence – PSI Technics offers a sustainable and advanced rolling stock maintenance solution.
(QuickStart: A simplified sensor portal that starts collecting digital train data at the onset of each project to ensure that relevant data is taken into account throughout the course of the project, e. g., for creating artificial intelligence models.)
Since the inspection takes place when the train passes through tunnel, the railway maintenance shop is freed up for other maintenance-related tasks. Trains that do not need to be serviced remain operational, which increases maintenance efficiency and sustainability and improves the availability and timeliness of trains while ensuring process reliability.
The inspection tunnel combines three vital elements of automated train inspection:
To provide customers with a condition-based maintenance solution for the visual inspection of rail vehicles, our engineers developed an automated camera-based system. The system records all damages or anomalies to the wearing strips, roof, sides and the underbody of any train that passes it, for example, when the train enters a depot or drives through a dedicated "inspection tunnel". The recorded data is send directly to the Analytics software module. After the images have been analyzed by the Analytics software, the inspection reports are created automatically and can be viewed directly via an intuitive user interface. The analysis results are repeatable, reliable and immediately available.
Artificial Intelligence (AI) - Data Mining - Deep Learning - Machine Learning
Artificial intelligence algorithms enable camera systems to learn from samples. Based on large volumes of recorded and analyzed data, modern machine learning algorithms help to continuously improve the evaluation of quality-related properties. The obtained data can subsequently be used for further processing and analysis.
The more data is collected, the better the software "learns" to interpret potential correlations. It intelligently and automatically combines recorded data to generate additional information for every train or component, saving valuable time and ensuring precise maintenance planning.
The results of the automated train inspection are stored in the cloud, to ensure that data from various systems at different locations can be shared and used simultaneously. Detecting wear and tear at an early stage contributes to the optimization of rolling stock maintenance processes and ensures the continuous and seamless monitoring of safety-critical components.
VIDEO: Industrial Image Processing for Railway Transport and Logistics
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