TOF Matrix Sensor Self-Damage Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for detecting signal interference or sabotage on imaging optical sensors, such as TOF matrix sensors, are costly and reliant on additional sensors, with methods often dependent on brightness information that is sensitive to ambient light and reflection, lacking robustness and efficiency in maintenance.
Innovation Solution
A fully automatic system using a TOF matrix sensor with a signal evaluation unit that evaluates distance signals from multiple receiver elements to detect damage or covering by comparing distance values over time with reference values, providing reliable and cost-effective status detection without additional components, enabling remote maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional sensors (motion sensors, glass break sensors, pressure sensors) are installed to detect sensor malfunctions, then detection capability is improved, but installation and maintenance costs increase significantly
Solution Approach 1:
The TOF matrix sensor detects its own malfunctions by analyzing changes in its own measurement signals. The signal evaluation unit monitors the sensor's own distance measurements and identifies patterns indicating contamination or damage, eliminating the need for separate detection sensors and reducing system complexity while maintaining reliability
Solution Approach 2:
The system continuously monitors the sensor's measurement signals and provides feedback about the sensor's condition. By comparing current distance measurements with expected patterns, the system detects malfunctions and triggers appropriate responses, creating a self-monitoring feedback loop that improves reliability without additional hardware
2Difficulty of detecting and measuring
If brightness information (intensity data) is used for sabotage detection, then detection is possible, but the system becomes highly dependent on ambient light conditions and surface reflectivity, reducing robustness
Solution Approach 1:
The system changes the parameter used for detection from brightness/intensity to distance measurement. By using time-of-flight distance data instead of optical intensity, the system becomes independent of ambient light conditions and surface reflectivity properties, significantly improving robustness while maintaining detection capability
Solution Approach 2:
The system substitutes optical intensity measurement with time-of-flight distance measurement. This replacement of one measurement principle with another eliminates the sensitivity to light conditions and reflectivity, as distance measurements based on light travel time are fundamentally independent of these optical properties
3Reliability
If fixed maintenance and cleaning cycles are implemented, then sensor reliability is maintained, but costs increase compared to condition-based maintenance
Solution Approach 1:
The system performs preliminary detection of sensor contamination or damage by continuously monitoring measurement signals for patterns indicating malfunctions. This early detection allows maintenance to be scheduled based on actual sensor condition rather than fixed cycles, enabling condition-based maintenance that is both reliable and cost-efficient
Solution Approach 2:
The continuous monitoring of sensor condition through signal analysis provides real-time feedback about sensor health. This feedback enables dynamic maintenance scheduling based on actual sensor state, replacing fixed maintenance cycles with condition-based maintenance that optimizes both reliability and cost efficiency
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects and classifies signal interference, reducing maintenance costs and improving reliability by using distance data independent of brightness fluctuations, allowing for timely and efficient maintenance actions.
Implementation Method 1
distance-measuring sensors which perform a distance measurement based on the time-of-flight measurement of light
Data Source
Figure 1~3
Figure 4
Figure 5~6
AI summary
The optical sensor has a transmission element and a receiving matrix (3) made of multiple receiving elements (4). A signal evaluation unit is provided for interpretation and evaluation of sensor signals as distance values for each receiver element and an interface for release of evaluation result. The signal evaluation unit is designed to conduct recognition of damages and coverings of the sensor by evaluation of the distance signals of multiple receiving elements according to their distance values and their temporal change.