Alarm Correlation Analysis for Root Cause Signal Identification
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Solution Overview
Problem
In industrial process plants, the overwhelming number of alarms and data signals can lead to confusion, causing important alarms to be overlooked, especially during unusual events, as users struggle to identify the root cause amidst a flood of information.
Innovation Solution
An apparatus and method for alarm information determination that uses correlation scores to identify relevant data signals and alarms associated with an event of interest, allowing users to quickly determine the root cause of issues by outputting the most correlated data and alarms, enabling efficient remedial action.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If numerous alarm systems and field devices are deployed to monitor process plants, then monitoring coverage and safety are improved, but alarm data volume and operator confusion increase
Solution Approach 1:
The patent extracts and isolates the most relevant alarm data from the overwhelming flood of alarm signals by applying correlation analysis. The system identifies and extracts only those alarms that are actually related to the root cause of unusual events, separating signal from noise. This allows the system to maintain comprehensive monitoring coverage while presenting only the critical subset of alarm data to operators.
Solution Approach 2:
The patent introduces an intermediary processing layer between the alarm generation systems and the operator interface. This intermediary system computes correlation scores and filters alarm data, acting as a mediator that translates raw alarm floods into meaningful, prioritized information. The correlation analysis mechanism serves as the intermediary that connects comprehensive monitoring with selective presentation.
2Loss of information
If all alarm data and data signals are presented to operators, then complete information availability is improved, but identification time and operator cognitive load increase
Solution Approach 1:
The patent performs preliminary correlation analysis and alarm filtering before presenting data to operators. By pre-computing correlation scores and pre-identifying relevant alarms in advance, the system prepares the information in a ready-to-use format. This preliminary processing eliminates the need for operators to manually sift through data during critical situations, significantly reducing identification time while maintaining information availability.
Solution Approach 2:
The patent applies different quality levels of information processing to different subsets of alarm data. Rather than treating all alarms uniformly, the system applies correlation-based filtering and prioritization selectively to identify which alarms require immediate attention. This local quality approach ensures that critical information is prominently presented while less relevant data is appropriately de-emphasized.
3Measurement precision
If correlation analysis is performed on all alarm data, then accuracy in identifying root cause is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the alarm data processing into distinct stages: initial correlation score computation, threshold-based filtering, and hierarchical prioritization. By dividing the complex analysis into manageable segments, the system achieves high root cause identification accuracy without overwhelming computational requirements. Each segment processes a subset of data with appropriate complexity, avoiding the need to analyze all alarm data simultaneously.
Solution Approach 2:
The patent changes the parameter of correlation threshold to dynamically control the balance between accuracy and computational complexity. By adjusting the correlation score threshold, the system can adaptively filter alarm data at different stages of analysis. This parameter change allows the system to maintain high accuracy when needed while reducing computational load during normal operations by raising the threshold for detailed analysis.
Data Source
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AI summary
The present invention relates to an apparatus (10) for alarm information determination. It is described to provide (110) a processing unit with historical process control data from an input unit, wherein the process control data comprises a plurality of data signals, a plurality of alarm data and data relating to an event of interest. The processing unit determining (120) a plurality of correlation scores for the plurality of data signals paired with the plurality of alarm data, wherein a correlation score is determined for a data signal paired with an alarm data and wherein a high score indicates a higher degree of correlation than a low score. The processing unit identifies (130) at least one first alarm data from the plurality of alarm data, the identification comprising utilization of the data relating to the event of interest. At least one first data signal is identified (140) from the plurality of data signals, the identification comprising the processing unit utilizing the correlation scores for the identified at least first one alarm data paired with the plurality of data signals. An output unit outputs (150) the at least one first data signal.