Virtual Solid Data Object for Anomaly Detection via Kinematic Perturbation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Analyzing large data sets is challenging due to their complexity, making it difficult for humans to engage directly with them effectively, as existing methods struggle to provide immediate and intuitive analysis of multiple parameters and values.
Innovation Solution
A system that transforms raw data into a virtual representation of a solid physical object with non-infinitesimal dimensions and defined material properties, allowing for analysis using structural engineering tools like finite element modeling, enabling immediate identification of outliers and anomalies through kinematic perturbations and vibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If large data sets are analyzed using traditional methods, then data processing can be performed, but human engagement and intuitive analysis become difficult due to complexity
Solution Approach 1:
The patent creates a physical replica or model of the data set that can be manipulated tangibly. This physical copy allows humans to interact with data structures through hands-on manipulation, transforming abstract complex data into concrete, perceivable forms that maintain the original data relationships while enabling intuitive exploration and analysis
Solution Approach 2:
The patent transitions data from abstract numerical dimensions to physical spatial dimensions. By representing data in three-dimensional physical space with tangible objects, the system adds a new dimension of human interaction, allowing users to perceive and manipulate data structures through spatial reasoning and physical manipulation rather than purely cognitive processing
2Adaptability or versatility
If data is transformed into virtual objects with non-infinitesimal dimensions, then structural engineering tools can be applied, but the complexity of the visualization system increases
Solution Approach 1:
The patent creates a universal physical data representation system that can accommodate multiple types of data sets and support various analytical operations. The standardized physical object framework allows different structural engineering tools, analytical methods, and manipulation techniques to be applied across diverse data types, providing multi-functional capability while maintaining a consistent underlying system architecture
3Measurement precision
If kinematic perturbations and vibrations are applied to the object, then anomaly detection is enhanced, but the manipulation system becomes more complex
Solution Approach 1:
The patent applies mechanical vibration and kinematic perturbation to physical data objects to reveal anomalies through resonant responses. By introducing controlled vibrations and observing how different parts of the physical data structure respond, the system enhances anomaly detection capability, allowing defects or unusual patterns to manifest as detectable vibrational characteristics that differ from normal data structures
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
Facilitates rapid and intuitive analysis of large data sets, enhancing anomaly detection and decision-making by converting complex data into a visual representation that can be manipulated and understood using familiar structural engineering tools, reducing the cognitive burden and increasing speed of data analysis.
Implementation Method 1
A vibration is applied to the structure at a selected frequency, and the vibrating structure is reviewed to identify anomalies within the data set
Implementation Method 2
A vibration is applied to the structure at a selected frequency, and the vibrating structure is reviewed to identify anomalies within the data set
Data Source
AI summary
Systems and methods are provided for analyzing large data sets. A source interface receives a data set representing at least two independent variables and at least one dependent variable. A modeling component defines a three-dimensional structure representing the data set and instantiates the structure as an object. The object is defined to have non-infinitesimal dimensions in all directions and defined material properties with at least one of a dimension of the object and a material property of the object being a function of the dependent variable. A structural engineering component manipulates the object to facilitate review of the data set represented by the object via one of a kinematic perturbation and application of a structural engineering tool to the object or directly applying mathematical methods to achieve similar results once the cognitive challenge is met by structurally organizing the data.