Camera Fault Detection via Image Property Comparison
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Solution Overview
Problem
Environmental disturbances such as dust, moisture, vibration, or mechanical impacts can impair camera functionality by altering light incidence on the image sensor, causing focus or field of view changes, and leading to distorted images, which are difficult to detect and require timely maintenance, often performed at fixed intervals, resulting in potential data loss or increased costs.
Innovation Solution
A system that includes a fault detection module capable of analyzing camera images for properties like cross covariance, frequency spectrum, edge presence, and edge orientation to automatically detect changes in lens, protective cover, image sensor, focus, or field of view, sending alerts for maintenance when significant differences are detected, allowing for timely intervention and reducing maintenance costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If maintenance is performed at fixed intervals, then maintenance scheduling is simple, but data loss may occur and costs increase due to unnecessary or delayed maintenance
Solution Approach 1:
The system continuously monitors camera images and provides feedback about lens, protective cover, or image sensor conditions by comparing properties between reference and current images. This feedback mechanism enables condition-based maintenance scheduling that adapts to actual camera degradation, replacing fixed-interval maintenance with a dynamic approach that triggers maintenance only when conditions deteriorate beyond thresholds.
Solution Approach 2:
The system performs preliminary analysis by capturing reference images under known good conditions and storing their properties for later comparison. This preliminary action establishes a baseline that enables detection of degradation before it causes data loss or functional failure, allowing proactive maintenance scheduling.
2Reliability
If maintenance is performed frequently to ensure reliability, then camera functionality is maintained, but maintenance costs and time increase
Solution Approach 1:
The continuous monitoring and comparison system provides real-time feedback on camera component conditions. By analyzing changes in image properties and triggering maintenance only when degradation exceeds predefined thresholds, the system prevents both premature maintenance (saving time) and delayed maintenance (preserving reliability).
Solution Approach 2:
The maintenance scheduling transitions from a static fixed-interval approach to a dynamic condition-based approach. The system adapts maintenance timing based on actual camera degradation rates, environmental factors, and operational conditions, optimizing the balance between reliability and maintenance time investment.
3Productivity
If environmental disturbances are not detected timely, then camera operations continue uninterrupted, but data loss occurs and maintenance costs increase
Solution Approach 1:
The system continuously compares current image properties against reference properties to detect environmental disturbances such as dust, moisture, vibration, or mechanical impacts. This feedback mechanism identifies degradation trends early, enabling timely maintenance intervention that prevents data loss while minimizing operational disruption.
Solution Approach 2:
By establishing reference images under known good conditions and continuously comparing them with current images, the system performs preliminary detection of environmental disturbances before they cause data loss. This allows maintenance to be scheduled at the optimal moment, maintaining productivity while ensuring data integrity.
Data Source
AI summary
Generally discussed herein are techniques, software, apparatuses, and systems configured for detecting an anomaly in a camera. In one or more embodiments a method can include: (1) determining a first property of a reference image, (2) determining a second property of a second image captured after the first image, wherein the second property is the same property as the first property, (3) comparing the first property to the second property, (4) determining a lens condition, a protective cover condition, an image sensor condition, a focus, or a field of view of the camera has changed since the first time in response to determining the first property is substantially different from the second property, or (5) sending an alert indicating that the lens condition, the protective cover condition, the image sensor condition, the focus, or the field of view of the camera has changed.