Camera-Assisted Crane Safety Zone Detection
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Solution Overview
Problem
Existing safety systems for cranes face challenges in detecting obstacles in three-dimensional spaces due to the complexity of crane movements and the need for robust, shock-resistant sensors that can cover all possible trajectories, which is time-consuming and costly to implement and maintain.
Innovation Solution
A safety system utilizing a computing system communicatively coupled with at least two cameras to analyze images and define a three-dimensional safety zone around the load, identifying potential hazards and executing remedial actions such as alarms or movement adjustments to avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors are installed to cover all possible crane trajectories, then obstacle detection reliability is improved, but device complexity and installation cost increase
Solution Approach 1:
The patent applies universality by using general-purpose cameras instead of specialized sensors for each trajectory. The camera system is multi-functional, capable of detecting obstacles across all crane movement paths through image processing and coordinate transformation, replacing numerous specialized sensors with a single versatile detection system.
Solution Approach 2:
The patent replaces mechanical sensor installations with an optical-electronic system. Instead of physically installing sensors along crane trajectories, the system uses cameras to capture images and computational algorithms to detect obstacles, substituting mechanical deployment with optical detection and digital processing.
2Reliability
If robust shock-resistant sensors are used to withstand crane movements, then measurement reliability is improved, but device complexity and maintenance requirements increase
Solution Approach 1:
The patent replaces mechanical shock-resistant sensors with an optical-camera system that is inherently more resistant to vibration and shock. The camera-based approach eliminates the need for mechanically robust sensors, as the detection is performed optically with minimal mechanical components that could fail under crane operational stresses.
Solution Approach 2:
The system performs self-calibration and automatic coordinate transformation between camera and crane coordinate systems through image processing algorithms. This self-service capability reduces the need for manual calibration and maintenance interventions, allowing the system to adapt to crane movements automatically without requiring specialized maintenance procedures.
3Measurement precision
If extensive sensor installation is performed to cover three-dimensional safety zones, then obstacle detection precision is improved, but installation time and cost increase
Solution Approach 1:
The patent replaces extensive mechanical sensor installation with a single or few camera installations coupled with computational processing. The precision three-dimensional obstacle detection is achieved through image processing algorithms and coordinate transformations rather than through dense physical sensor arrays, dramatically reducing installation time while maintaining detection precision.
Data Source
AI summary
Aspects of this disclosure relate to a system that uses images of a load handled by a crane as captured by cameras to monitor the load. The images may include different sets of outer perimeters of the load. The system may identify the outer perimeters and then define a safety zone that extends beyond these outer perimeters. In response to identifying an object within the safety zone, the system may execute a remedial action.