Pipeline Throughput Estimation Under Fluctuating Operating Conditions
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Solution Overview
Problem
Existing management systems struggle to accurately estimate the maximum processing amount in pipelines that process fluid, particularly in chemical plants, due to fluctuations caused by factors such as retention in tanks, pressure balance changes, and supply variations, which affect processing performance.
Innovation Solution
A management system that utilizes sensors to obtain measurement values, applies a physical model based on device properties, and employs a genetic algorithm to estimate the maximum processing amount, pressure balance, and detect anomalies, optimizing operating conditions through a server and user terminals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a physical model is used to estimate processing amount in drainage facilities, then the control of drainpipe network is optimized, but the estimation accuracy deteriorates when applied to chemical plant pipelines due to multiple fluctuating factors
Solution Approach 1:
The patent applies dynamics by making the physical model adaptable to changing operating conditions. The system dynamically adjusts the physical model parameters based on real-time sensor measurements from the chemical plant pipeline, allowing the estimation to remain accurate despite fluctuations in retention amounts, pressure balance, and supply conditions. This transforms a static estimation approach into a dynamic one that evolves with operating conditions.
Solution Approach 2:
The patent implements parameter changes by modifying the physical model parameters according to actual operating conditions in the chemical plant. By changing parameters such as retention time, pressure differential, and flow characteristics based on measured values, the system maintains accurate processing amount estimation across varying operational states, resolving the contradiction between model simplicity and estimation accuracy.
2Measurement precision
If multiple factors influencing processing amount are considered, then the maximum processing amount can be accurately grasped, but the system complexity increases
Solution Approach 1:
The patent applies universality by creating a multi-functional system that simultaneously handles multiple influencing factors through a unified physical model framework. The system processes retention data, pressure measurements, flow rate information, and supply conditions all within a single integrated estimation mechanism, avoiding the need for separate systems for each factor and thus managing complexity while maintaining comprehensive measurement precision.
Solution Approach 2:
The patent uses an intermediary approach by introducing a computational processing layer that mediates between multiple sensor inputs and the final processing amount estimation. This intermediary computational model integrates various影响因素 (influencing factors) through standardized calculations, reducing the direct complexity of handling multiple factors while preserving measurement accuracy through systematic data synthesis.
Data Source
AI summary
A management system for managing an operating condition for a pipeline that processes fluid, the management system including a processor configured to: obtain measurement values from sensors provided in devices that constitute the pipeline; and estimate a maximum processing amount of the fluid in the entire pipeline in operation by inputting the measurement values obtained from the sensors into a physical model that is built based on physical properties of the devices.