Cooling Performance Sign Detection Using Operating-State Filtering
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Solution Overview
Problem
Existing oil cooling apparatuses face challenges in accurately detecting cooling performance deterioration, particularly when load is low, due to factors like clogging or oil quality deterioration, which are difficult to discern from normal operation.
Innovation Solution
A sign detection system that includes a pre-processing unit to extract features from operation data and a sign detection unit using a model trained on these features to diagnose cooling performance, excluding operation status data indicating standby periods to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If cooling performance diagnosis is performed using all operation data including standby periods, then more data is available for analysis, but detection accuracy decreases due to false positives from standby conditions
Solution Approach 1:
The patent extracts and removes standby period data from the operation data before performing cooling performance diagnosis. The diagnosis target is set to exclude periods where the cooling target apparatus is in standby state, thereby eliminating the source of false positives while retaining useful operational data for accurate diagnosis.
2Reliability
If cooling performance deterioration is detected at low load conditions, then early signs of deterioration can be identified, but detection accuracy decreases because temperature differences are not remarkable
Solution Approach 1:
The patent performs preliminary classification of operation data into operational periods and standby periods before diagnosis. By pre-identifying and excluding standby periods from the diagnosis target, the system prepares clean data that enables reliable detection of cooling performance deterioration signs even when temperature differences are subtle.
3Reliability
If general check mechanism stops apparatus operation when oil temperature increases, then safety is maintained, but productivity decreases due to unnecessary shutdowns from false alarms
Solution Approach 1:
The patent implements a feedback mechanism where the diagnosis result (indicating cooling performance deterioration) feeds back to control the shutdown decision. The check mechanism now shuts down the apparatus only when the diagnosis unit confirms actual cooling performance deterioration, rather than responding to all temperature increases, thereby eliminating false alarms while maintaining safety.
Data Source
AI summary
In order to achieve high accuracy of detecting a sign of cooling performance deterioration, a sign detection system includes: a pre-processing unit acquiring operation data of a time series about a cooling target apparatus and extracting features from the operation data, the cooling target apparatus including a temperature rise source and a cooling unit cooling the temperature rise source, and a sign detection unit diagnosing cooling performance of the cooling unit, based on an output obtained by inputting the features extracted from the operation data for diagnosis to a sign detection model, the sign detection model being constructed using training data generated based on the features extracted from the operation data for training and a label indicating a state of the cooling performance. The sign detection model is constructed using the training data generated based on the features extracted from the operation data including the operation statuses corresponding to the being operating and the being on standby. When diagnosing the cooling performance, the sign detection unit inputs the features extracted from the operation data including only the operation statuses corresponding to the being operating, to the sign detection model.