Distillation Column Concentration Estimation With Sensor Fault Detection
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Solution Overview
Problem
Existing methods for detecting failures in concentration sensors within distillation columns are limited by their reliance on steady-state conditions, are computationally heavy, and require additional pipes that deteriorate insulation, making real-time estimation of chemical component concentrations along the column challenging.
Innovation Solution
A method using a convection-diffusion model with an adjustment parameter to estimate concentrations, where the parameter's erratic behavior indicates sensor failure, allowing for real-time detection without additional pipes, by weighting diffusion and propagation effects in packed distillation columns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If concentration analyzers are installed to measure concentrations at multiple locations, then measurement reliability is improved, but additional pipes and drilling are required which deteriorate insulation and increase device complexity
Solution Approach 1:
The existing temperature and pressure sensors in the distillation column are made to serve dual purposes: their original functions plus concentration estimation. The convection-diffusion model uses these multi-functional sensors to estimate concentrations without requiring dedicated concentration analyzers, thereby avoiding additional pipes and insulation deterioration.
Solution Approach 2:
The system uses its own existing sensor network (temperature and pressure sensors) to perform concentration measurement indirectly through the convection-diffusion model. This self-service approach eliminates the need for external concentration analyzers and their associated piping infrastructure.
2Measurement precision
If corrective approaches linking form factor to operating conditions are used, then concentration estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The form factor is pre-calculated and stored in lookup tables before real-time operation. During actual concentration estimation, the system only needs to perform simple table lookups based on current operating conditions rather than performing complex real-time calculations, thus maintaining accuracy while reducing computational burden.
Solution Approach 2:
The form factor is made dynamic by linking it to operating conditions (temperature, pressure, flow rates). Instead of using a constant form factor, the system adapts the form factor based on current operational state, improving accuracy across varying conditions while using pre-computed tables to manage complexity.
3Reliability
If data reconciliation techniques are used for failure detection, then sensor reliability is improved, but the methods are limited to steady-state conditions and require well-identified operating conditions
Solution Approach 1:
The approach changes from using multiple sensor measurements for reconciliation to using a single adjustable parameter (the form factor) that adapts to different operating conditions. This parameter change enables the system to detect sensor failures during transient states and varying operating conditions where traditional data reconciliation methods fail.
Solution Approach 2:
The system performs preliminary calculation and storage of form factor values for various operating conditions before actual operation. This pre-computation enables rapid failure detection during transient states without requiring complex real-time calculations or assumptions about steady-state conditions.
4Ease of manufacture
If black box models are used for concentration estimation, then ease of implementation is improved, but realism, focus, and efficiency remain questionable for complex industrial units
Solution Approach 1:
The approach replaces black box empirical models with a physics-based convection-diffusion model that incorporates fundamental mass transfer principles. This substitution improves model realism and efficiency by using established physical laws while maintaining practical implementability through the use of existing sensor data and pre-computed form factors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables reliable real-time estimation of chemical component concentrations and effective detection of sensor failures, improving operational efficiency and reducing maintenance costs by avoiding the need for additional pipes and enhancing insulation integrity.
Implementation Method 1
a convection-diffusion model with an adjustment parameter to estimate concentrations, where the parameter's erratic behavior indicates sensor failure
Implementation Method 2
weighting diffusion and propagation effects in packed distillation columns
Data Source
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Figure 6~7
AI summary
The invention concerns a method for determining the concentrations of chemical components of a product, in particular air, in a distillation column, said method involving implementing a model for estimating the concentration of the components from measurements carried out by one or a plurality of sensors (41-45, 51-55), said model using an adjustment parameter making it possible to take into consideration operating variations of the column, the method comprising a step which involves detecting the values (200) of said adjustment parameter that are outside a nominal variation range of said parameter in order to diagnose a fault D in one or a plurality of said sensors.