Gas Meter Detailed Sampling for Remote Appliance Failure Diagnosis
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Solution Overview
Problem
Conventional gas appliance failure diagnosis systems cannot accurately identify the specific failure part of a gas appliance, requiring manual inference by repair technicians based on limited information, leading to inefficient repair processes.
Innovation Solution
A gas appliance failure diagnosis system that includes a gas meter capable of measuring flow rates in both normal and detailed modes, coupled with a center device that analyzes the collected data to generate failure diagnosis information, allowing remote identification of the failure part.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed measurement mode is used continuously to obtain accurate flow rate data, then measurement precision is improved, but energy consumption increases
Solution Approach 1:
The system dynamically switches between normal measurement mode and detailed measurement mode based on operational conditions. The flow rate meter adjusts its sampling frequency and measurement detail level according to whether the gas appliance is in steady state or experiencing transient conditions, thereby achieving high measurement precision when needed while minimizing energy consumption during normal operation.
Solution Approach 2:
The measurement parameters (sampling period, measurement detail) are changed based on the operational state of the gas appliance. During steady-state operation, normal measurement mode with longer sampling periods is used to conserve energy. When abnormalities or transient conditions are detected, the system switches to detailed measurement mode with shorter sampling periods to capture accurate flow rate data for failure diagnosis.
2Measurement precision
If detailed measurement mode is used to obtain accurate flow rate data, then measurement precision is improved, but data processing complexity increases
Solution Approach 1:
The patent extracts only the necessary detailed measurement data for failure diagnosis purposes. The center device selectively requests and processes detailed flow rate data only when failure diagnosis is needed, rather than continuously processing all measurement data. This reduces data processing complexity while maintaining measurement precision when required.
Solution Approach 2:
The center device acts as an intermediary between the flow rate meter and the failure diagnosis system. It receives measurement data from the gas meter, filters and processes only the relevant information needed for failure diagnosis, and transmits necessary data to the diagnosis system. This intermediary role simplifies the overall data processing complexity by eliminating the need for the gas meter itself to perform complex analysis.
3Productivity
If manual inference by repair technicians is used, then device complexity is reduced, but productivity decreases
Solution Approach 1:
The diagnosis system enables self-service failure identification by automatically analyzing flow rate data to determine the cause of gas appliance failures. The system compares measured flow rate patterns against known failure patterns and automatically identifies the failure cause, eliminating the need for repair technicians to perform manual inference. This significantly improves repair productivity while the system complexity is managed through automated algorithms rather than human expertise.
Data Source
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Figure 3A~3C
AI summary
A gas meter (10) includes a normal measurement mode in which the flow rate is measured in a predetermined sampling period and a detailed measurement mode in which the flow rate is measured in a sampling period shorter than the predetermined sampling period in the normal measurement mode. A center device (40) gives an instruction to the gas meter (10) to measure the flow rate in the detailed measurement mode. The center device (40) further collects flow rate data measured in the detailed measurement mode from the gas meter (10), and generates, based on the collected flow rate data, failure diagnosis information for diagnosing a failure in a gas appliance. With this configuration, the failure part in the gas appliance can be remotely identified, which accelerates the repair work.