Alarm Management Using Petri Nets to Filter Redundant Alarms
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Solution Overview
Problem
The increasing number of alarms in industrial environments due to advanced monitoring systems leads to 'alarm floods,' overwhelming operators and potentially causing off-specification products and hazardous events, as existing solutions fail to effectively reduce redundant and redundant alarms in real-time.
Innovation Solution
The use of temporal and non-temporal Petri nets to model alarm relationships, identify domination and mutual dependency between alarms, and apply construction rules to filter out redundant alarms, reducing the number of alarms presented to operators and facilitating safer and more efficient operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the number of sensors and monitoring variables is increased to improve process monitoring capability, then the completeness of process monitoring is improved, but alarm floods occur that overwhelm operators and reduce operational safety
Solution Approach 1:
The patent extracts and removes redundant alarms from the alarm sequence by identifying systematic causality relationships. Domination relationships identify alarms that are implied by other alarms, while mutual dependency relationships identify alarms that provide equivalent information. These redundant alarms are extracted and filtered out, leaving only essential alarms for operator presentation.
Solution Approach 2:
The patent introduces Petri nets as an intermediary formalism to model and analyze alarm relationships. The alarm sequence is transformed into a Petri net representation, which enables systematic identification of domination and mutual dependency relationships. This intermediary model facilitates the detection and removal of redundant alarms while preserving essential alarm information.
2Reliability
If comprehensive alarm monitoring is implemented to improve safety, then the detection capability is improved, but the complexity of alarm management increases and operators cannot respond quickly enough
Solution Approach 1:
The system performs self-service by automatically analyzing alarm sequences and identifying redundancy relationships without requiring manual expert intervention for each alarm configuration. The Petri net-based approach enables automated detection of domination and mutual dependency relationships, allowing the system to self-optimize alarm presentation while maintaining comprehensive monitoring coverage.
Solution Approach 2:
The patent changes the representation parameters of alarm data by transforming raw alarm sequences into Petri net models. This parameter transformation enables systematic analysis of alarm relationships and automatic identification of redundancy. The constructed rules based on Petri net analysis dynamically adjust which alarms are presented to operators, reducing the effective number of alarms while maintaining safety.
3Loss of information
If all alarms are presented to operators to ensure complete information, then information completeness is improved, but operator response time decreases and hazardous events may occur
Solution Approach 1:
The patent performs preliminary analysis of alarm sequences to identify and mark redundant alarms before presenting them to operators. By pre-processing alarm data through Petri net modeling and constructing rules that identify domination and mutual dependency relationships, the system prepares a filtered alarm set in advance, enabling operators to respond quickly to essential alarms without being overwhelmed by redundant information.
Solution Approach 2:
The patent applies partial action by selectively presenting only non-redundant alarms to operators rather than all generated alarms. The systematic identification of domination relationships allows the system to omit certain alarms that are implied by other presented alarms, while mutual dependency analysis ensures equivalent information is not lost. This partial presentation of alarms reduces operator workload while maintaining essential information completeness.
Data Source
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AI summary
A Petri net that corresponds to the mathematical model is determined and the Petri net includes the domination relationships and mutual dependency relationships between individual alarms. The Petri net is analyzed to determine a set of construction rules. The construction rules define an approach to reduce the number of alarms presented to an operator or a computer program.