Optoelectronic Safety Sensor Diagnostic Unit for False Shutdown Classification
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Solution Overview
Problem
Current safety sensors in machine safety applications face challenges in reliably distinguishing between hazardous and non-hazardous interventions, leading to frequent false shutdowns, which are difficult to analyze and resolve due to lack of data processing capabilities and user expertise, resulting in machine downtimes and reduced productivity.
Innovation Solution
A distance-measuring optoelectronic safety sensor with a diagnostic unit integrated within the sensor or safety controller that automatically records, classifies, and analyzes shutdown events, providing clear, processed information to users, reducing the need for expert analysis and enabling quick identification of causes and corrective measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If safety sensors trigger emergency stop on detected object intrusion, then safety is improved, but false shutdowns increase due to inability to distinguish hazardous from non-hazardous interventions
Solution Approach 1:
The patent replaces manual analysis of shutdown events with an automated diagnostic system that uses optical sensors and electronic processing to classify interventions. The diagnostic unit automatically evaluates sensor data, determines whether intrusions are hazardous or non-hazardous, and generates diagnostic outputs without requiring manual intervention, thereby reducing false shutdowns while maintaining safety.
Solution Approach 2:
The patent introduces a diagnostic unit as an intermediary between the safety sensor and the machine control system. This diagnostic unit processes sensor data, classifies intrusions, and provides differentiated diagnostic outputs that enable operators to distinguish between genuine safety threats and false alarms, thereby maintaining safety while reducing unnecessary shutdowns.
2Loss of information
If manual analysis of shutdown events is performed, then diagnostic information can be obtained, but time consumption and expertise requirements increase
Solution Approach 1:
The patent implements a self-service diagnostic system where the safety sensor includes an integrated diagnostic unit that automatically analyzes shutdown events, classifies intrusions, and generates diagnostic outputs. This eliminates the need for operators to manually analyze sensor data, significantly reducing time consumption and expertise requirements while preserving complete diagnostic information.
Solution Approach 2:
The patent replaces manual diagnostic analysis with an automated electronic diagnostic system that processes sensor data, applies classification algorithms, and generates diagnostic outputs automatically. This substitution of manual processes with automated electronic analysis reduces both time consumption and the need for specialized expertise while maintaining comprehensive diagnostic capabilities.
3Loss of information
If diagnostic data is stored for analysis, then shutdown causes can be identified, but data processing complexity and storage requirements increase
Solution Approach 1:
The patent extracts and stores only the essential diagnostic information needed for classification, such as intrusion characteristics, sensor signal patterns, and temporal features. By selectively storing only relevant data rather than all raw sensor data, the system reduces storage requirements and processing complexity while maintaining sufficient information for accurate diagnostic analysis.
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
This solution enables direct recording, analysis, and evaluation of shutdown events, reducing the time and expertise required for troubleshooting, enhancing system availability and safety by providing actionable insights for reducing false shutdowns and improving machine uptime.
Implementation Method 1
the distance of the object from the safety laser scanner is inferred from the light travel time using the speed of light
Implementation Method 2
A light beam generated by a laser periodically scans a surveillance area with the help of a deflection unit. The light is remitted to objects in the surveillance area and evaluated in the scanner.
Data Source
Figure 1
AI summary
A distance-measuring optoelectronic safety sensor (10) for monitoring a monitoring area (18) is specified, wherein the safety sensor (10) has a light receiver (24) for generating a received signal when light is received (20) from the monitoring area (18) and an evaluation unit (30) which is designed to detect objects in the monitoring area (18) using the received signal and to determine their position including their distance to the safety sensor (10) and to recognize an impermissible object intrusion into a protected area within the monitoring area (18) as a shutdown event and to output a safety signal on the basis of this.A memory (34) is provided for storing a history with object intervention information of the shutdown events and a diagnostic unit (36) is provided which is designed to classify shutdown events stored in the memory (34) on the basis of the object intervention information and to output the object intervention information processed in this way, including class information.