Industrial Vibration Anomaly Analysis Across Multi-Machine Facilities
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Solution Overview
Problem
Existing systems are unable to simultaneously analyze vibration data from numerous sensors across industrial machines at a facility scale, leading to inefficiencies in identifying and tracking anomalies and reporting sub-optimal performance, due to noise, time series discrepancies, and other data integrity issues.
Innovation Solution
A system that collects, transforms, and analyzes vibration data from multiple industrial machines, identifies anomalies, and reports machines deviating from optimal performance by using a distributed computing framework to standardize and process data, including data cleaning, imputation, and penalty matrix generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional threshold-based vibration monitoring systems are used, then simple anomaly detection is achieved, but the systems are incapable of simultaneously analyzing vibration data from hundreds of sensors across multiple industrial machines at facility scale
Solution Approach 1:
The patent segments the facility into multiple zones, each with its own anomaly detection system. Each zone independently processes vibration data from sensors within that zone, enabling parallel processing across the facility while maintaining manageable system complexity through distributed architecture
Solution Approach 2:
The patent transitions from traditional single-machine analysis to multi-dimensional facility-wide analysis by organizing sensors into zones and implementing hierarchical processing. This dimensional expansion allows simultaneous analysis of hundreds of sensors through structured parallel processing rather than centralized sequential analysis
2Reliability
If vibration data from multiple sensors is collected without normalization, then comprehensive monitoring coverage is achieved, but data integrity is compromised due to noise, time series discrepancies, and uncontrolled variations
Solution Approach 1:
The patent applies parameter changes by normalizing vibration data through standardized processing procedures. This includes adjusting time series data to common intervals, applying noise filtering parameters, and establishing consistent measurement baselines across all sensors, thereby improving data integrity while maintaining manageable processing complexity through systematic approaches
3Ease of operation
If simple threshold-based anomaly detection is used, then implementation is straightforward, but the systems are incapable of identifying and tracking vibration anomalies across the facility
Solution Approach 1:
The patent implements feedback mechanisms where anomaly detection results from each zone are aggregated and fed back to a central reporting system. This allows the system to maintain simple local detection operations while accumulating comprehensive facility-wide anomaly information through iterative feedback loops, enabling both ease of operation and complete tracking
Data Source
AI summary
Methods, systems, and devices for analyzing vibration data and for identifying and tracking vibration anomalies in industrial machines are described. In various embodiments, the system described herein collects, transforms, and analyzes sensor data from one or more machines, such as industrial machines. The system may identify one or more sensors that are experiencing vibrational anomalies. In various embodiments, the system: collects and analyzes vibration data for a set of one or more vibration-related sensors of one or more industrial machines; determines an occurrence of one or more anomalies based on the vibration data as compared to a threshold; tracks anomalies in collected vibration data for the one or more industrial machines of the facility; generates a report of vibration data for the one or more vibration-related sensors of the facility; and reports industrial machines in the facility that may deviate from a target performance.