Data Processing Device for Electrical Apparatus Status Inference
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Solution Overview
Problem
Existing methods for inferring the operational status of electrical apparatuses, such as those with inverters, face accuracy issues due to the need for extensive teacher data covering fluctuation patterns in current and power consumption, which can be labor-intensive and costly to prepare.
Innovation Solution
A data processing device and method that acquires measurement data, extracts reference components by distinguishing between fluctuation and non-fluctuation periods, and uses feature values to infer operational statuses, allowing for more accurate inference with reduced teacher data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive teacher data covering fluctuation patterns is prepared to improve inference accuracy, then measurement precision is improved, but device complexity and loss of time increase due to labor-intensive data preparation
Solution Approach 1:
The patent extracts only the necessary reference components (non-fluctuation parts) from measurement data, separating them from fluctuation components. This extraction approach reduces the amount of teacher data needed while maintaining inference accuracy, directly resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent segments measurement data into fluctuation periods and non-fluctuation periods, and further divides reference components into current reference components and power reference components. This segmentation allows selective processing of only relevant data portions, reducing overall data preparation complexity while preserving essential information for accurate inference
2Measurement precision
If extensive teacher data covering fluctuation patterns is prepared to improve inference accuracy, then measurement precision is improved, but loss of time increases due to labor-intensive data preparation
Solution Approach 1:
The patent extracts only the necessary reference components (non-fluctuation parts) from measurement data, separating them from fluctuation components. This extraction approach reduces the amount of teacher data needed while maintaining inference accuracy, directly resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent segments measurement data into fluctuation periods and non-fluctuation periods, and further divides reference components into current reference components and power reference components. This segmentation allows selective processing of only relevant data portions, reducing overall data preparation complexity while preserving essential information for accurate inference
3Measurement precision
If measurement data is processed to cover sufficient fluctuation variation, then measurement precision is improved, but device complexity increases due to processing requirements
Solution Approach 1:
The patent extracts only the necessary reference components (non-fluctuation parts) from measurement data, separating them from fluctuation components. This extraction approach reduces the amount of teacher data needed while maintaining inference accuracy, directly resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The patent segments measurement data into fluctuation periods and non-fluctuation periods, and further divides reference components into current reference components and power reference components. This segmentation allows selective processing of only relevant data portions, reducing overall data preparation complexity while preserving essential information for accurate inference
Data Source
AI summary
As means for solving the above-described problem, there is provided a data processing device (1) including a measurement data acquisition unit (10) that acquires measurement data indicating a temporal change in at least one of current consumption and power consumption of an electrical apparatus, a reference component extraction unit (20) that extracts a reference component of the current consumption and a reference component of the power consumption from the measurement data, and a feature value acquisition unit (30) that acquires a feature value of each reference component.