Acoustic Trip Detection in Electrical Enclosures With Noise Classification
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Solution Overview
Problem
Existing methods for detecting the tripping of disconnection units in electrical installations are costly and not feasible for large installations, especially when existing units cannot be replaced, and there is a need for a more efficient way to identify electrical faults without relying on expensive radio communication systems.
Innovation Solution
A method and device that acoustically detect the tripping of disconnection units by generating decision-making categories through a learning phase using machine learning systems, specifically neural networks, to distinguish between disconnection and switching noise signals, allowing for continuous noise signal acquisition and alarm signaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radio communication systems are used to detect tripping of disconnection units, then detection capability is improved, but implementation cost increases significantly
Solution Approach 1:
The patent replaces electronic radio communication systems with an acoustic detection system using microphones and signal processing. The tripping event generates a characteristic acoustic signature that can be detected and analyzed to determine when a disconnection unit has tripped, eliminating the need for expensive radio communication hardware while maintaining detection capability.
Solution Approach 2:
The patent creates an acoustic copy or signature of the tripping event that can be detected and analyzed. By capturing and analyzing the acoustic characteristics of the tripping mechanism, the system can identify tripping events without requiring the original unit to have radio communication capabilities, thus reducing implementation costs.
2Reliability
If acoustic detection is used to distinguish disconnection from switching noise, then false alarms are reduced, but signal processing complexity increases
Solution Approach 1:
The patent performs preliminary action by capturing and analyzing acoustic signatures during a learning phase before normal operation. The system learns the characteristic acoustic patterns of both switching operations and tripping events in advance, creating a reference database that enables accurate real-time differentiation without requiring complex processing during actual detection.
Solution Approach 2:
The patent implements feedback mechanisms where the detected acoustic signals are continuously analyzed and compared against learned patterns. The system provides feedback by adjusting its detection thresholds and patterns based on learned data, improving its ability to distinguish between switching noise and actual tripping events while reducing false alarms.
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
Enables cost-effective and efficient detection of electrical faults by differentiating between disconnection and switching noise, reducing false alarms and enabling timely intervention without the need for expensive radio communication systems.
Implementation Method 1
acquiring a unit noise signal generated by at least one of said disconnection units for disconnecting the electric current or at least one switching unit for switching the electric current
Data Source
AI summary
A method for detecting a tripping of a disconnection unit in an electrical enclosure, the electrical enclosure including at least one disconnection unit for disconnecting electric current and at least one switching unit for switching the electric current, the method including a learning phase configured to generate decision-making categories associated with an acoustic signature of the tripping of the at least one disconnection unit, and a phase of detecting the tripping of the disconnection unit, including:acquiring a unit noise signal generated by at least one of the disconnection units for disconnecting the electric current or at least one switching unit for switching the electric current, andcomparing the unit noise signal with the decision-making categories in order to detect whether the unit noise signal corresponds to the tripping of the disconnection unit.