Rotating Machine Condition Analysis With Revolution-Synchronous Decimation
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Solution Overview
Problem
Existing machine condition monitoring systems face challenges in accurately analyzing the condition of machines with rotating parts, particularly due to high noise levels and varying rotational speeds, which can lead to inadequate detection of deteriorating conditions and sudden failures.
Innovation Solution
A system comprising a Shock Pulse Measurement sensor, an analogue-to-digital converter, decimators, and an enhancer that processes vibration signals to maintain a constant sample rate per revolution, amplifying repetitive signal components and reducing stochastic noise, enabling early detection of incipient damage in rotating parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vibration signals are sampled at high frequency to capture detailed mechanical vibrations, then measurement precision is improved, but data processing complexity and noise levels increase
Solution Approach 1:
The patent segments the vibration signal processing into distinct stages: analog filtering stage, analog-to-digital conversion stage, digital filtering stage, and analysis stage. Each stage processes only the necessary frequency range or signal component, reducing the overall computational complexity while maintaining measurement precision for defect detection.
Solution Approach 2:
The patent extracts and processes only the relevant signal components for bearing defect detection. By using band-pass filters to isolate specific frequency ranges associated with bearing defects, the system removes unnecessary high-frequency noise and low-frequency vibrations, reducing data processing complexity while preserving measurement precision for the critical defect signals.
2Device complexity
If the sampling rate is reduced to decrease data processing load, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent applies preliminary analog filtering before analog-to-digital conversion to pre-process the vibration signal and remove out-of-band frequencies. This preliminary action reduces the bandwidth of the signal that needs to be digitized and processed digitally, allowing for lower sampling rates while maintaining measurement precision for the frequency ranges most relevant to bearing defect detection.
Solution Approach 2:
The patent changes the sampling rate parameter dynamically based on the detected rotational speed of the bearing. When the bearing rotates faster, the sampling rate is increased to capture the higher frequency vibrations; when the bearing rotates slower, the sampling rate is reduced. This adaptive parameter adjustment maintains measurement precision across varying operating conditions while optimizing data processing load.
3Measurement precision
If noise filtering is applied to reduce noise levels, then measurement precision is improved, but loss of information occurs in the vibration signal
Solution Approach 1:
The patent applies different filtering characteristics to different frequency ranges of the vibration signal. Band-pass filters are designed with passbands centered on the characteristic frequencies of bearing defects (ball pass frequency, cage frequency, etc.), allowing strong noise reduction in non-critical frequency ranges while preserving the local signal quality in the critical defect-related frequency bands, thus improving signal-to-noise ratio without losing important diagnostic information.
4Reliability
If complex signal processing algorithms are used to enhance defect detection, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent employs periodic signal processing techniques that exploit the periodic nature of bearing defect signals. By synchronizing the analysis with the rotational period of the bearing and accumulating signal energy over multiple revolutions, the system enhances periodic defect signatures while suppressing random noise. This approach improves defect detection reliability using relatively simple processing operations repeated periodically rather than complex continuous algorithms.
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 system effectively enhances repetitive signal patterns and reduces noise, allowing for early detection of machine damage and improved condition monitoring, even in noisy environments and varying rotational speeds.
Implementation Method 1
a first sensor adapted to generate an analogue electric measurement signal (SEA) dependent on mechanical vibrations emanating from rotation of said part
Implementation Method 2
an analogue-to-digital converter (44) for sampling said analogue measurement signal at a sampling frequency (fS) so as to generate a digital measurement data signal (SMD)
Implementation Method 3
a first decimator for performing a decimation of the digital measurement data signal (SMD, SENV) so as to achieve a first digital signal (SMD, SENV) having a first reduced sampling frequency (fSR1)
Implementation Method 4
an enhancer having an input for receiving said second digital signal (SRED2); said enhancer being adapted to receive a first plurality (ILENGTH) of sample values, wherein said second digital signal (SRED2) represents mechanical vibrations emanating from rotation of said part for a duration of time; said enhancer being adapted to perform a correlation so as to produce an output signal sequence (O) wherein repetitive signals amplitude components are amplified in relation to stochastic signal components
Data Source
AI summary
A method analyzing a machine having a rotating shaft includes generating an electric measurement signal dependent on mechanical vibrations from the shaft rotation; sampling the measurement signal to generate a digital measurement data signal; performing a decimation of the digital measurement data signal to achieve a digital signal having a reduced sampling frequency, where the decimation includes controlling the reduced sampling frequency such that the number of sample values per revolution of the shaft is kept at a substantially constant value, and receiving the digital signal at an enhancer input performing a correlation in the enhancer so as to produce an output signal sequence where repetitive signals amplitude components are amplified in relation to stochastic signal components, and performing a condition analysis for analyzing the condition of the machine dependent on the digital signal having a reduced sampling frequency.