Method for detecting deficiencies of a heating device
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Solution Overview
Problem
Current methods for detecting deficiencies in heating devices are complex, specific to each case, and often unreliable due to insufficient data, making it difficult to quickly identify operating failures and plan maintenance operations effectively.
Innovation Solution
A method involving temperature measurement over time, detection of upward and downward temperature setpoint variations, calculation of a heating rate based on restart duration and temperature differences, and triggering an alarm for deficient device states, allowing for early detection and identification of maintenance needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex pattern recognition and learning methods are used for fault detection, then measurement precision may be improved, but device complexity increases and reliability decreases due to insufficient data
Solution Approach 1:
The patent extracts only the essential parameters needed for fault detection (temperature setpoint variations and heating rates) from the complex system, eliminating the need for comprehensive pattern recognition and learning algorithms. This focuses the diagnosis on critical thermal behavior indicators rather than attempting to analyze all possible system parameters.
Solution Approach 2:
Instead of using complex AI methods to interpret system behavior, the patent inverts the approach by using simple physical principles (thermal response characteristics) to directly detect faults. The method relies on the fundamental relationship between temperature changes and heating device performance, rather than trying to teach a system to recognize fault patterns.
2Measurement precision
If theoretical temperature comparison methods are used requiring external data, then measurement precision improves, but device complexity increases due to need for web servers and building identification algorithms
Solution Approach 1:
The patent extracts only the essential information needed for fault detection from the system - specifically the temperature setpoint variations and actual temperature response. This eliminates the need for external web servers, building identification algorithms, and other complex infrastructure, focusing solely on the thermal behavior data that directly indicates device health.
3Loss of time
If automated diagnostics are implemented, then loss of time for maintenance planning is reduced, but device complexity increases
Solution Approach 1:
The heating device performs self-diagnosis by automatically monitoring its own temperature response to setpoint variations and calculating heating rates. This self-service approach provides automated fault detection without requiring complex external diagnostic systems, reducing both time loss and system complexity.
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 provides a simple and universal solution for monitoring heating device performance, enabling rapid detection of operating failures and optimizing maintenance operations by objectively assessing device states and triggering alarms for deficient conditions.
Implementation Method 1
Measurement by a probe of the temperature of said medium over time over a given time interval
Data Source
Figure 1a
Figure 1b
Figure 1c
AI summary
The invention relates to a method for detecting deficiencies in a heating device (10) in operation in a given environment, comprising the implementation of steps of: (a) Measurement by a probe (20) of the temperature of said medium over time (Tint(t)) over a given time interval; (b) Detection of an instant of upward variation (Temps_Init) of a temperature set point over time (Tset(t)); (c) Determination of a duration, from said moment of upward variation (Temps_Init), of relaunch (Duration_Relance) necessary for said measured temperature (Tint(t)) to catch up with the temperature set point over time ( Tcons(t)) to within a predetermined success threshold, or the data processing means (30) detect a moment of downward variation of the temperature setpoint over time (Tcons(t)); (d) Calculation of a heating rate (Allure) as a function of said relaunch duration (Duration_Relance) and minimum and maximum temperatures (T_min, T_max) measured over said relaunch duration (Duration_Relance); (e) determination of a deficient state of the device (10) as a function of at least said heating rate (Allure); (f) Triggering an alarm if the device (10) is determined to have a faulty condition.