Dynamic 3D Visualization Scaling for Pipeline Inspection Data
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Solution Overview
Problem
The visualization of large data sets from pipeline inspections is hindered by the sheer volume of data generated, which is bandwidth and storage intensive, making it difficult to access and manage, especially in remote locations with limited bandwidth.
Innovation Solution
A system that includes a mapping sled generating data, a data server for storage, and a visualization server that processes and generalizes the data into dynamic three-dimensional visualization, reducing storage requirements without sacrificing accuracy, particularly highlighting potential problem areas in pipelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed three-dimensional data is stored at full resolution, then measurement precision is improved, but storage requirements and bandwidth consumption increase significantly
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the resolution level of stored visualization data based on the scale of display. Full-resolution data is preserved for detailed analysis while lower-resolution versions are used for overview displays, thereby reducing storage requirements while maintaining measurement precision when needed
Solution Approach 2:
The patent segments the data storage system into multiple resolution levels (full-resolution, reduced-resolution, and summary levels). This segmentation allows the system to store and retrieve only the necessary data quality for each specific viewing context, reducing overall storage requirements while maintaining accuracy for problem location identification
2Measurement precision
If full-resolution visualization data is transmitted to remote devices, then measurement precision is improved, but bandwidth consumption increases significantly
Solution Approach 1:
The system dynamically changes the resolution parameter of transmitted data based on the display scale and device capabilities. When inspectors view data on mobile devices with limited bandwidth, the system transmits lower-resolution versions that consume less bandwidth while still maintaining sufficient accuracy for identifying problem locations
Solution Approach 2:
The patent transmits only the necessary level of data detail for each specific viewing context. Instead of always transmitting full-resolution data, the system transmits partial data (reduced-resolution versions) when full detail is not needed, thereby reducing bandwidth consumption while maintaining measurement precision for problem detection
3Reliability
If comprehensive pipeline inspection data is stored, then reliability is improved, but storage requirements increase significantly
Solution Approach 1:
The patent applies local quality by storing full-resolution data only for specific segments of the pipeline that contain identified problems or anomalies, while storing reduced-resolution data for normal pipeline sections. This approach maintains inspection reliability for problem areas while reducing overall storage requirements
Data Source
AI summary
Visualization of three-dimensional data without loss of desired characteristics is enabled by receiving three-dimensional data pertaining to a physical object in the world, the physical object represented by a series of segments, the three-dimensional data including a predetermined number of measurements of the series of segments, storing the three-dimensional data in data storage and generating an average measurement value for each of the series of segments. The process further involves generating a first generalization of the three-dimensional data by selecting, for each of the series of segments, a desired number of measurements, fewer than the predetermined number of measurements, that represent the largest deviations from the respective average measurement, storing the selected measurements as the first generalization of the three-dimensional data in the data storage, and upon request, providing access to the first generalization of the three-dimensional data.