Motor Vibration State Gating for Accurate Multi-Motor Alarms
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Solution Overview
Problem
Existing vibration monitoring systems struggle to accurately determine the operational state of motors in multi-motor machines, leading to false alarms and inefficient maintenance scheduling.
Innovation Solution
A vibrational sensing system (VSS) that uses an accelerometer and a data processor to determine the operational state of motors, gate learning of long-term vibrational data, and calculate alarm thresholds, thereby reducing false alarms and improving maintenance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vibration monitoring systems continuously collect data from all motors in multi-motor machines, then comprehensive monitoring coverage is achieved, but false alarms increase due to inability to distinguish operational states
Solution Approach 1:
The patent segments the vibration monitoring approach by motor operational state. Instead of treating all motors uniformly, the system divides monitoring into distinct operational modes (on-state and off-state) and applies different data collection and analysis strategies to each segment. This allows accurate discrimination between motors that are actually running versus those that are idle, eliminating false alarms while maintaining comprehensive coverage.
Solution Approach 2:
The system dynamically adjusts its monitoring behavior based on detected operational states. The monitoring parameters, data collection frequency, and analysis methods are dynamically modified according to whether motors are in on-state or off-state. This dynamic adaptation enables the system to optimize alarm accuracy by applying appropriate monitoring intensity to each operational condition.
2Measurement precision
If vibration data is collected during both on-state and off-state, then complete vibration profile is captured, but non-operational data contaminates baselines and creates false alarms
Solution Approach 1:
The patent extracts and separates operational vibration data from non-operational vibration data. By identifying and isolating data collected during motor on-state, the system creates pure operational baselines free from contamination by off-state vibrations. This extraction process ensures that baseline calculations and alarm thresholds are derived solely from relevant operational conditions, eliminating false alarms caused by mixing data from different states.
3Productivity
If multiple motors with uncorrelated on/off cycling are monitored simultaneously, then complete machine coverage is achieved, but disturbance rejection becomes difficult
Solution Approach 1:
The system performs preliminary identification and classification of each motor's operational state before conducting vibration analysis. By pre-establishing which motors are in on-state versus off-state, the system can selectively apply monitoring and analysis techniques appropriate to each state. This preliminary action enables effective disturbance rejection by preventing cross-contamination of vibration data from motors in different operational states, even when they cycle uncorrelated.
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
The VSS effectively determines the operational state of motors, reduces false alarms, and enables proactive maintenance by recognizing early signs of wear and failure, thus extending machine life and preventing unexpected downtime.
Implementation Method 1
an accelerometer and a data processor, which determines an 'operational state' of a mechanical drive unit
Data Source
AI summary
Apparatus and associated methods relate to a vibrational sensing system (VSS) including an accelerometer and a data processor, which determines an “operational state” of a mechanical drive unit, the processor further employing the “operational state” to gate learning of long-term vibrational data to exclude collection of non-operational data, the long-term data collected to calculate alarm thresholds. For example, vibrations from a target motor are sensed by a coupled accelerometer. Vibrational data from the accelerometer is fed into a data processor which determines the operational state of the motor. The operational state (e.g., on/off indication) may gate data collection such that data is only acquired during on-time, which may advantageously create accurate baselines from which alarm thresholds may be generated, and nuisance alarms may be avoided.