Method and apparatus for suppression of spikes detected by a proximity sensor
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Solution Overview
Problem
Rotating machinery monitoring systems often generate false alarms due to non-vibration induced random events, leading to unnecessary shutdowns and increased maintenance costs.
Innovation Solution
A digital proximity system that detects non-periodic spikes and suppresses them based on predefined criteria, such as spike magnitude and duration, to prevent false alarms and allow non-vibration induced events to resolve without triggering a shutdown.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the proximity sensor monitors vibration continuously, then the reliability of detecting true vibration-induced failures is improved, but false alarms from non-vibration induced random events increase
Solution Approach 1:
The system dynamically adjusts the alarm threshold based on learned normal vibration patterns. By continuously adapting the threshold to match the specific operational characteristics of the machinery, the system maintains high sensitivity to true failures while filtering out false alarms from random non-vibration events.
Solution Approach 2:
The system implements feedback mechanisms where alarm history and vibration patterns are continuously analyzed. When false alarms are detected, the system learns from these events and adjusts its detection parameters accordingly, improving future detection accuracy while reducing spurious alarm generation.
2Measurement precision
If the alarm threshold is set low to detect early failures, then the sensitivity of the monitoring system is improved, but the frequency of false alarms increases
Solution Approach 1:
Rather than using a fixed low threshold that triggers false alarms, the system dynamically determines thresholds based on learned normal operation patterns. This allows the system to maintain high sensitivity for detecting early failures while adapting to normal operational variations that would otherwise trigger false alarms.
Solution Approach 2:
The system changes the detection parameter from a fixed threshold to a dynamic, adaptive threshold that evolves based on operational data. This parameter transformation enables the system to maintain high detection sensitivity while automatically adjusting to filter out false alarm conditions.
3Reliability
If the system shuts down machinery immediately upon detecting a spike, then the protection against catastrophic failure is improved, but unnecessary shutdowns due to random events increase
Solution Approach 1:
The system performs preliminary analysis of detected spikes to determine their nature before triggering a shutdown. By pre-analyzing vibration patterns and comparing them against learned normal behavior, the system can distinguish between true failure conditions requiring shutdown and random events that should be ignored, thus protecting machinery while maintaining productivity.
Solution Approach 2:
The system uses feedback from alarm history and vibration pattern analysis to make informed shutdown decisions. When a spike is detected, the system references past performance data to determine whether the spike represents a true failure condition or a random event, thereby avoiding unnecessary shutdowns while maintaining machine protection.
4Reliability
If scheduled maintenance is performed frequently to prevent failure, then the reliability of the machinery is improved, but the downtime and maintenance costs increase
Solution Approach 1:
The system performs preliminary detection and analysis of potential failure conditions in real-time, allowing maintenance to be scheduled only when actually needed. By continuously monitoring vibration patterns and detecting early signs of failure, the system enables condition-based maintenance that replaces frequent scheduled maintenance, thereby improving reliability while reducing unnecessary downtime.
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
Reduces the likelihood of false alarms, allowing machinery to continue operating while ensuring that actual vibration-induced shutdown conditions are properly identified and addressed, thereby minimizing downtime and maintenance costs.
Implementation Method 1
an output signal generated by a proximity sensor in the proximity system and monitoring at least a magnitude of the output signal; determining whether a spike having a magnitude exceeding a prescribed threshold value has occurred in the received output signal
Data Source
AI summary
A method for suppressing a non-periodic random event in a proximity system includes: receiving an output signal generated by a proximity sensor in the proximity system and monitoring at least a magnitude of the output signal; determining whether a spike having a magnitude exceeding a prescribed threshold value has occurred in the output signal; when a spike in the output signal is detected, setting an output of the proximity system to a prescribed level for a prescribed duration of time; when the prescribed duration of time has elapsed, determining whether the output signal meets one or more prescribed criteria indicative of a shutdown condition; when it is determined that the output signal meets the prescribed criteria, setting the output of the proximity system to a level exceeding an alarm threshold; and when it is determined that the output signal fails to meet at least one of the prescribed criteria, releasing suppression of the output of the proximity system.