Underbody Camera Leak Detection With False Positive Classification
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Solution Overview
Problem
Existing leak detection systems in vehicles are inefficient and prone to false positives, failing to accurately and promptly identify leaks beneath the vehicle.
Innovation Solution
Equipping commercial vehicles with cameras aligned to capture a region of interest beneath the vehicle, coupled with a processing unit to analyze images at regular intervals, distinguishing between leak, animal, shadow, and precipitation hypotheses, and verifying leak spots through multiple image comparisons.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional leak detection systems are used, then leak detection capability is provided, but false positive detections occur and detection accuracy is low
Solution Approach 1:
The detection system segments the analysis by creating multiple hypothesis categories (leak spot hypotheses, animal hypotheses, shadow hypotheses, precipitation hypotheses) to differentiate between various types of detected objects. This segmentation allows the system to distinguish true leak detections from false positives caused by other objects or environmental factors.
Solution Approach 2:
The system dynamically updates leak spot hypotheses by continuously comparing new images with existing hypotheses. When a detected spot matches an existing hypothesis, the hypothesis is updated with new information; when no match is found, a new hypothesis is created. This dynamic approach improves detection accuracy over time.
2Productivity
If constant monitoring is implemented, then leak detection speed is improved, but system complexity increases
Solution Approach 1:
The system captures images at regular intervals when the vehicle is stationary, providing continuous monitoring capability without requiring constant active processing. This periodic imaging approach enables fast leak detection while managing system complexity by activating the camera only when needed.
Solution Approach 2:
The processing unit automatically analyzes captured images, compares them with existing hypotheses, and updates or creates new hypotheses without human intervention. This self-service automation enables constant monitoring with rapid leak identification while reducing the operational complexity of the system.
Data Source
AI summary
A commercial vehicle with at least one camera configured to detect leaks is disclosed. The at least one camera is arranged and aligned to capture a region of interest beneath the commercial vehicle, wherein a processing unit is connected to the camera and is configured to read an image from the at least one camera at regular intervals when the commercial vehicle is stationary and to detect differences between the images and to classify them as hypotheses, including leak spot hypotheses, animal hypotheses, shadow hypotheses and precipitation hypotheses. and when a leak spot hypothesis is verified, to determine its location in relation to predetermined regions beneath the commercial vehicle in order to establish a defect hypothesis related to the cause of the leak.