Rotating Member Fault Detection Using Angular Vibration Trends
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Solution Overview
Problem
Existing fault detection systems for mechanical systems with rotating members do not effectively account for linear combinations of frequencies and overall trends in energy and harmonics, leading to inadequate detection of potential failures.
Innovation Solution
A method involving vibration and angular sensors to process temporal signals, transform them into angular and frequency domains, identify trend frequency channels, and compare these with linear combinations of known fault frequencies to detect potential faults using a fault presence indicator.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional vibration monitoring indicators are used, then the system can detect faults, but the detection reliability is insufficient due to not accounting for linear combinations of frequencies and overall trends
Solution Approach 1:
The patent transforms the vibration analysis from traditional time-domain or simple frequency-domain indicators to a more sophisticated parameter set that includes linear combinations of fault frequencies and their temporal trends. This parameter transformation enables more reliable fault detection by capturing the evolving characteristics of fault signatures.
Solution Approach 2:
The patent introduces a new dimension of analysis by considering not only the presence of fault frequencies but also their temporal evolution trends. This adds a time-dimension to frequency analysis, allowing the system to distinguish between transient disturbances and developing faults based on whether frequency components are increasing or decreasing over time.
2Reliability
If simple vibration amplitude thresholds are used, then the system is easy to operate, but early fault detection capability is insufficient
Solution Approach 1:
The patent performs preliminary transformation of vibration signals into the frequency domain and identifies trend characteristics before making fault detection decisions. By pre-processing the signals to extract frequency trends, the system enables early fault detection while maintaining a manageable level of complexity through systematic signal processing steps.
Solution Approach 2:
The patent introduces frequency trend analysis as an intermediary between raw vibration signals and fault detection decisions. This intermediary layer transforms complex time-domain signals into interpretable frequency trend indicators, bridging the gap between raw data and diagnostic conclusions.
3Measurement precision
If comprehensive frequency analysis is performed, then fault detection accuracy improves, but processing time increases
Solution Approach 1:
The patent extracts only the relevant frequency components and their trends from the complete vibration spectrum, rather than analyzing all frequencies equally. By focusing computational resources on identifying and tracking specific fault-related frequency combinations and their temporal evolution, the system achieves high detection accuracy with reduced processing time.
Data Source
AI summary
A method and a device for detecting a fault in a mechanical system comprising a rotating member and a vibration sensor transmitting a temporal vibration signal. The method comprises processing the temporal vibration signals transmitted over a predetermined period in order to transform the temporal vibration signals firstly into angular vibration signals, then into frequency vibration signals. Next, series of amplitudes are generated, each series being associated with a specific frequency channel and comprising the amplitudes of the frequency vibration signals for this frequency channel. The frequency channels displaying an increasing trend consistent with the fault of interest are then identified. The frequency channels that display an increasing trend are then compared with characteristic frequencies of a known fault of interest in order to check for the possible presence of such a fault in the mechanical system.