Method for determining a state of a heating system
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Solution Overview
Problem
Current heating system monitoring lacks precision in detecting anomalies, leading to undetected issues and incorrect diagnoses, which can result in unnecessary maintenance interventions and reduced efficiency.
Innovation Solution
A method involving repeated temperature and vibration measurements in a water heating system, analyzed by a processing unit to identify anomalies, determine the probable causes of malfunctions, and provide precise diagnostics, allowing for remote identification and scheduling of necessary physical interventions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If temperature detection based monitoring is used, then remote monitoring capability is provided, but measurement precision and anomaly detection accuracy deteriorate
Solution Approach 1:
The patent combines multiple measurement parameters (temperature, vibration, acoustic emissions, current) into a unified monitoring system. By merging these different sensing modalities, the system achieves both remote monitoring capability and high measurement precision, as each parameter complements the others to provide more accurate anomaly detection than any single parameter could achieve alone.
Solution Approach 2:
The patent transitions from single-parameter temperature monitoring to multi-dimensional monitoring by adding vibration, acoustic emissions, and electrical current measurements. This dimensional expansion allows the system to detect anomalies more precisely while maintaining remote monitoring capabilities, as defects manifest differently across multiple measurement dimensions.
2Measurement precision
If multiple measurement parameters are collected, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent employs a processing unit that performs multiple functions: acquiring data from various sensors, storing measurements, determining temporal evolution of parameters, and generating anomaly alerts. This multi-functional approach consolidates what would otherwise require separate systems, improving measurement precision while controlling device complexity through functional integration.
Solution Approach 2:
The processing unit acts as an intermediary between multiple sensors and the monitoring system. It centralizes data acquisition, synchronization, and analysis functions, thereby managing the complexity introduced by multiple measurement parameters while enabling precise anomaly detection through coordinated processing of all sensor inputs.
3Reliability
If real-time multi-parameter monitoring is implemented, then reliability of fault detection improves, but loss of time for data processing increases
Solution Approach 1:
The processing unit continuously determines the temporal evolution of measurement parameters in real-time, maintaining updated information about system behavior patterns. This preliminary processing ensures that when anomalies occur, the system can immediately compare current readings against established temporal patterns, improving fault detection reliability without significant time loss.
Solution Approach 2:
The system implements continuous feedback by repeatedly measuring parameters, determining their temporal evolution, and generating alerts when anomalies are detected. This closed-loop feedback mechanism maintains high reliability by constantly monitoring system state while managing processing time through efficient comparison of current measurements against historical patterns stored in memory.
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 approach enables early detection of system failures, reduces the number of maintenance visits, and ensures that maintenance personnel are adequately prepared with the correct tools and parts, improving the overall efficiency and effectiveness of heating system maintenance.
Implementation Method 1
measure a water temperature at at least one location and repeatedly in the heating system
Implementation Method 2
repeatedly measure vibrations of at least one part of the heating system
Data Source
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AI summary
The disclosure relates to a method for determining the state of a heating system (101) for the provision of an anomaly identification, said method comprising: /a/ measuring a temperature at at least one location and repeatedly in the heating system; /b/ repeatedly measuring vibrations of at least one part of the heating system; /c/ sending data corresponding to said measurements to a processing unit (110); /d/ determining at least the time evolution of the temperature and vibrations by the processing unit; /e/ providing an anomaly identification based on the result of the determination step.