Anomaly Root Cause Localization Through Data Item Fluctuation Analysis

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Solution Overview

Problem

Existing methods for locating anomaly root causes in data systems are inaccurate and require manual intervention, leading to inefficiencies and increased labor, as they fail to account for the complexity of data items and their correlations, resulting in a broadened range of identified anomalies.

Innovation Solution

A method and device for anomaly root cause localization that involves obtaining anomaly indicators, disassembling derived indicators to data items, determining anomaly data items through data fluctuation information, and tracing back to anomaly fields using Pearson correlation and machine learning models to narrow the root cause range.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual participation is used to locate anomaly indicators, then the accuracy of identifying root causes is improved, but the time consumption and labor requirements increase significantly

Engineering Contradiction:

Improveaccuracy of locating root causeVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system automatically performs anomaly detection, data item set generation, and root cause localization without requiring manual intervention. The algorithm independently analyzes data fluctuation information, determines anomaly data items, and traces back to root causes, enabling the system to serve itself in the anomaly localization process.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical analysis with an automated algorithmic system. The system uses computational methods to analyze data fluctuation information, calculate anomaly degrees, and identify root causes, substituting human operators with an automated computing system that processes information faster and more consistently.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Ease of operation

If existing methods are used to locate anomaly indicators, then the process is simplified, but the accuracy of locating the root cause deteriorates due to inability to account for data item correlations

Engineering Contradiction:

Improvesimplicity of processVSAvoidaccuracy of locating root cause

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent segments the anomaly localization process into distinct stages: obtaining anomaly indicators, generating data item sets, determining anomaly data items through fluctuation analysis, and tracing back to root causes. This segmentation allows each step to be handled systematically while maintaining overall process simplicity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces data item sets as an intermediary structure between anomaly indicators and root causes. By analyzing data fluctuation information within these structured sets and calculating anomaly degrees, the system bridges the gap between simple indicator monitoring and complex root cause identification, maintaining simplicity while improving accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Reliability

If the range of identified anomalies is broadened to account for data item correlations, then the completeness of root cause identification is improved, but the complexity of the system increases

Engineering Contradiction:

Improvecompleteness of root cause identificationVSAvoidsystem complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments the complex analysis into manageable components: data item sets group related data items, data fluctuation information captures correlation patterns, and anomaly degree calculations assess individual contributions. This segmentation handles complexity systematically while ensuring complete root cause identification.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the parameter of analysis from simple anomaly detection to multi-dimensional fluctuation analysis. By examining data fluctuation information, correlation patterns, and anomaly degrees as separate calculable parameters, the system comprehensively identifies root causes while managing complexity through parameterized analysis.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12566659B2Methods, devices, and electronic devices for locating anomaly root causes

Publication Date: 2026.03.03 CHENGDU AIRCRAFT INDUSTRY GROUP

AI summary

The present disclosure discloses a method, a device, and an electronic device for locating an anomaly root cause. The method for locating the anomaly root cause includes obtaining an anomaly indicator of a target system, obtaining a data item set based on the anomaly indicator, determining an anomaly data item based on data fluctuation information of each data item of the data item set, obtaining an anomaly field corresponding to the anomaly data item based on the anomaly data item, and locating an anomaly root cause of the target system based on the anomaly field.