Earthquake Search Engine Using Approximate Nearest Neighbor Matching
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Solution Overview
Problem
Current earthquake monitoring technologies are unable to rapidly determine source parameters, such as focal mechanism, in real-time, which is crucial for early warning systems and timely reporting, often requiring hours or days of computational efforts and expertise.
Innovation Solution
A method and system utilizing an approximate nearest neighbor search with waveform matching in both historical and theoretical seismogram databases to quickly identify similar seismograms and determine earthquake parameters, employing a Multiple Randomized K-Dimensional Tree (MRKD-Tree) structure for efficient data indexing and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If waveform modeling and inversions are performed to derive earthquake focal mechanism, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent pre-calculates and stores theoretical seismograms for various earthquake source parameters in a database before actual earthquake analysis is needed. This preliminary preparation allows rapid matching with observed seismograms during real earthquake events, eliminating the need for time-consuming waveform modeling and inversions while maintaining determination accuracy
Solution Approach 2:
The patent creates a comprehensive database of theoretical seismograms that replicate various possible earthquake waveforms under different source parameters. By copying pre-computed theoretical waveforms into the database, the system enables rapid comparison and matching with observed seismograms, achieving fast focal mechanism determination without repeated computational modeling
2Measurement precision
If expert analysis is required to ensure estimation accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent implements an automated matching system that independently compares observed seismograms with pre-stored theoretical seismograms using objective similarity criteria. The system automatically determines earthquake parameters without requiring expert intervention, thereby maintaining measurement precision while significantly reducing operational complexity and enabling real-time analysis
Solution Approach 2:
The patent replaces the manual expert analysis process with an automated computational system that uses algorithmic waveform matching and similarity assessment. This substitution eliminates the need for human expertise in the analysis chain while maintaining or improving consistency and speed of parameter determination
3Measurement precision
If comprehensive waveform analysis is performed, then measurement precision is improved, but productivity decreases
Solution Approach 1:
The patent pre-computes and stores theoretical seismograms for a comprehensive range of source parameters before earthquake events occur. This advance preparation enables rapid matching with observed waveforms during actual events, achieving both high measurement precision and fast reporting speed by avoiding real-time computational modeling
Solution Approach 2:
The patent uses a database of theoretical seismograms that covers a broader range of source parameters than any single earthquake event requires. This excessive preparation ensures that the observed seismogram can be rapidly matched against relevant theoretical waveforms, achieving fast and accurate determination without performing unnecessary comprehensive analysis
Data Source
AI summary
Methods for rapidly determining earthquake parameters of an earthquake include inputting a seismogram of the earthquake, searching concurrently in pre-established historical seismogram database and theoretical seismogram database by use of an approximate nearest neighbor search method, to find a set of seismograms similar to the input seismogram according to a preset similarity condition, and determining from the set of similar seismograms one or more seismograms matched with the input seismogram, and determining the earthquake parameters from the matched seismograms. With the present invention, it is possible to search in millions of seismograms and determine parameters for an earthquake in a few second, and thus realize rapid and even real-time estimation of earthquake parameters.