State estimation device, drive system, refrigeration system, fan system, state estimation method, and state estimation program
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Solution Overview
Problem
State estimation devices face challenges in accurately estimating the state of a device due to unintended variations (noise) in feature quantities, leading to potential erroneous estimations, particularly in diagnosing device abnormalities.
Innovation Solution
A state estimation device that includes a control unit to perform a calculation process for deriving feature quantities, an estimation process for estimating the device's state, and a restriction process to prevent erroneous estimation by satisfying predetermined conditions, releasing the restriction only when stable conditions are met, such as changes in motor rotation, fluid pressure or temperature, or control mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the estimation process is continuously performed based on feature quantity, then the state of the device can be monitored in real-time, but erroneous estimation occurs when noise or unintended variation is present in the feature quantity
Solution Approach 1:
The control unit performs preliminary actions by determining whether restriction conditions are satisfied before executing the estimation process. When the restriction condition is satisfied (indicating unstable feature quantity due to noise), the control unit restricts the estimation process in advance, preventing erroneous estimation before it occurs. This preliminary restriction ensures that estimation is only performed when the feature quantity is reliable.
Solution Approach 2:
The restriction condition acts as an intermediary mechanism between the feature quantity and the estimation process. The control unit evaluates the restriction condition (which monitors the stability of the feature quantity) as a mediator to determine whether the estimation process should proceed. This intermediary layer filters out erroneous estimations caused by noisy feature quantities while allowing valid estimations to pass through.
2Reliability
If the estimation process is restricted to prevent erroneous estimation, then estimation accuracy is improved, but the response time for detecting actual abnormalities increases
Solution Approach 1:
The restriction condition is designed to be dynamic rather than static. The control unit continuously monitors whether the restriction condition is satisfied, allowing the estimation process to be dynamically enabled or disabled based on the current state of the feature quantity. When the feature quantity becomes stable (restriction condition not satisfied), the estimation process is automatically released, ensuring timely detection of abnormalities without permanent delay.
Solution Approach 2:
The system implements feedback by continuously evaluating the restriction condition based on the feature quantity's stability. The control unit uses this feedback to adjust the estimation process in real-time - restricting it when noise is detected and releasing it when stability is confirmed. This feedback mechanism ensures that the estimation process responds appropriately to changing conditions, minimizing time loss while maintaining accuracy.
3Productivity
If the feature quantity is calculated from physical quantity within a predetermined period, then the state estimation can be performed, but unintended variation (noise) occurs in the feature quantity
Solution Approach 1:
The control unit performs preliminary evaluation of the restriction condition before using the calculated feature quantity for estimation. By checking whether the restriction condition is satisfied (indicating presence of noise) in advance, the system prevents erroneous estimation from occurring, thus maintaining reliability without sacrificing the speed of the estimation process itself.
Solution Approach 2:
The restriction condition serves as an intermediary that separates the feature quantity calculation from the estimation process. The control unit uses this intermediary to determine whether the calculated feature quantity is reliable enough for estimation. This mediator allows the system to maintain high productivity by quickly calculating feature quantities while ensuring reliability by filtering out noisy calculations through the restriction condition evaluation.
Data Source
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AI summary
In a calculation process, a control unit (31) calculates a feature quantity from a physical quantity obtained from a device (70) within a predetermined period. In an estimation process, the control unit (31) estimates the state of the device (70), based on the feature quantity calculated by the calculation process. In a restriction process, the control unit (31) restricts the estimation process when an estimation restriction condition is satisfied, maintains restriction of the estimation process until a standby release condition is satisfied when a restriction release condition is satisfied, and releases the restriction of the estimation process after the standby release condition is satisfied. The estimation restriction condition is a condition in which there is a possibility of occurrence of erroneous estimation in the estimation process. The restriction release condition is a condition in which the erroneous estimation in the estimation process is suppressed.