Lighting System Diagnosis via Image Feed Analysis
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Solution Overview
Problem
In machines like mining trucks, dark areas can form around the machine due to insufficient light from the lighting system, affecting the quality of images captured by image capturing devices, which rely on machine lighting for clear operation at night, especially when lights are not functioning properly or are displaced.
Innovation Solution
A diagnostic system that includes an image capturing device and a controller to analyze the light feed for dark pixels, determining if their number exceeds a threshold within a predefined area, and providing an alert to the operator to address potential issues with the lighting system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the lighting system is used to provide light for night operation, then the image quality captured by image capturing devices is improved, but dark areas may form when lights malfunction or are insufficient, deteriorating image quality
Solution Approach 1:
The system uses an image capturing device to continuously monitor the light output of the lighting system and provides feedback to a controller. The controller analyzes the captured images to detect dark areas, determining whether the lighting system is functioning properly. This closed-loop feedback mechanism ensures reliable detection of lighting failures and maintains image quality by alerting operators to issues promptly.
2Adaptability or versatility
If multiple image capturing devices are positioned to capture machine surroundings, then the operational awareness is improved, but the system complexity increases
Solution Approach 1:
The image capturing devices serve multiple functions: they capture machine surroundings for operational awareness and simultaneously monitor the lighting system's performance. By making the imaging devices multi-functional, the system avoids adding separate monitoring equipment, thereby reducing overall system complexity while maintaining comprehensive operational awareness.
3Reliability
If the controller continuously monitors image feed for dark pixels, then the lighting system reliability is improved, but the processing time and computational load increase
Solution Approach 1:
Instead of analyzing every pixel in the entire image feed continuously, the controller focuses on detecting dark areas in specific regions of interest where lighting failures are most likely to occur. This partial monitoring approach reduces computational load and processing time while maintaining reliable detection of lighting system issues.
Data Source
AI summary
A control system for a hybrid machine is provided. The control system includes a controller communicably coupled to an energy storage unit of the hybrid machine. The controller is configured to receive data from the energy storage unit. The controller is configured to evaluate a current storage charge state of the energy storage unit based on the received data. The controller is configured to receive historical data related to idle events associated with an engine of the hybrid machine. The controller is configured to receive data related to one or more machine operating parameters. The controller is configured to pre-emptively control at least one of an engine speed and an engine power based on the received data for at least one of shutting down the engine during an idle state and restarting the engine.