Rotary Valve State Monitoring with Position and History Inference
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Solution Overview
Problem
Existing valve monitoring techniques fail to accurately account for specific use conditions of each valve, leading to inadequate anomaly detection and state prediction, and inefficient management of valve systems.
Innovation Solution
A valve state grasping system that includes a sensor unit attached to the valve, a server with a database for storing position and history information, and a terminal device for displaying inference information, allowing for accurate monitoring and management of valve systems by considering specific use conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If general valve monitoring techniques are used, then the monitoring system is simple to implement, but the anomaly detection accuracy is insufficient because specific use conditions are not considered
Solution Approach 1:
The monitoring system is segmented into multiple functional modules: sensor unit for data collection, communication unit for data transmission, and server for data processing and analysis. Each module performs a specific function, allowing the system to achieve high detection accuracy through specialized processing while maintaining implementation simplicity through modular design.
Solution Approach 2:
A server acts as an intermediary between the sensor units and the user interface. The server receives data from multiple sensors, processes it centrally, and generates comprehensive analysis results. This intermediary approach allows complex processing to be centralized while keeping individual sensor units simple.
2Reliability
If position information and history information are accumulated for each valve, then state inference accuracy improves, but data management complexity increases
Solution Approach 1:
The server performs multiple functions: storing position information, accumulating history information, processing sensor data, generating anomaly detections, and providing user interfaces. This multi-functional approach consolidates data management complexity into a single platform while improving state inference accuracy through comprehensive data accumulation.
Solution Approach 2:
The system continuously accumulates history information and position data for each valve over time, enabling progressive improvement of state inference accuracy. The continuous data collection and processing allow the system to learn from past operations and improve reliability without increasing operational complexity.
3Loss of time
If comprehensive valve monitoring with position and history information is implemented, then maintenance prediction accuracy improves, but system cost increases
Solution Approach 1:
The monitoring system enables self-service maintenance planning by automatically analyzing valve state data, detecting anomalies, and predicting maintenance needs. The system serves itself by using accumulated history information to generate maintenance predictions without requiring external expert intervention, improving timing accuracy while optimizing resource consumption.
Solution Approach 2:
The system performs preliminary analysis of valve conditions by continuously monitoring position information and history data, detecting potential issues before they become critical failures. This preliminary action allows maintenance to be scheduled proactively based on actual valve state rather than reactive responses to failures.
Data Source
AI summary
A valve state grasping system, a display device and a rotary valve, a valve state grasping program, a recording medium, and a valve state grasping method that enable efficient valve system monitoring and accumulation of information. The system includes a valve V, a sensor unit, a server including a database, a terminal device including a display unit, and a system control unit. The database includes a position information unit, a history information unit, and an inference information unit. The position information unit includes unique information and pipe attachment information, and the history information unit includes at least measurement information and diagnosis information. The system control unit accumulates information of the position information unit and information of the history information unit in association with each other and outputs predetermined inference information from the inference information unit based on information of the position information unit and information of the history information unit.