CT-Based DPF Density Mapping for Contamination Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for evaluating the density of particulate matter in diesel particulate filters (DPFs) are inadequate, leading to reduced effectiveness in removing particulate matter from exhaust streams due to contamination and clogging, which is not efficiently assessed using current technologies.
Innovation Solution
A computed tomography (CT) scanning method that generates images of DPF samples, segments them into regions, determines density by correlating grayscale values with reference values, and identifies contamination levels by analyzing mean atomic numbers, allowing for precise evaluation of particulate matter density and contamination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT scanning is used to evaluate particulate matter density in DPFs, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces a reference stack with known density values as an intermediary between the CT scanner and the DPF sample. This reference stack serves as a calibration medium that translates complex CT grayscale values into meaningful density measurements, simplifying the overall measurement system while maintaining high precision.
Solution Approach 2:
The patent transforms the measurement parameter from direct density measurement to grayscale value correlation. By scanning at multiple energy levels and calculating attenuation coefficient deltas, the system changes the measurement parameters to enable more accurate density determination through reference comparison rather than direct measurement.
2Measurement precision
If multiple energy levels are used for CT scanning to determine mean atomic number, then contamination identification accuracy is improved, but use of energy increases
Solution Approach 1:
The patent performs CT scanning at multiple energy levels (excessive action) to obtain attenuation coefficients at different energies. This partial redundancy in energy levels allows for calculation of mean atomic numbers and contaminant identification, with the additional energy expenditure justified by the significant improvement in contamination detection accuracy.
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
This method provides accurate and detailed assessments of particulate matter density and contamination in DPFs, enabling better maintenance and performance optimization of exhaust aftertreatment systems by identifying specific regions of interest and contamination levels within the filters.
Implementation Method 1
A computed tomography (CT) scanning method that generates images of DPF samples
Implementation Method 2
determining density by correlating grayscale values with reference values
Data Source
AI summary
A computer system is structured to determine a density of particulate matter in a diesel particulate filter (DPF) sample. The computer system includes a processing circuit having a processor and a memory. The processing circuit is structured to generate a computed tomography (CT) scan-based image of the DPF sample; and, segment the CT scan-based image of the DPF sample into a plurality of regions. For at least one region from the plurality of regions, the processing circuit is structured to determine a density of a portion of the DPF sample corresponding to the at least one region of the CT scan-based image of the DPF sample and cause an electronic display of a user device to display the CT scan-based image including the at least one region and an indication of the density for the at least one region.