Tachometer Signal Generation from Vibration Data Using FFT Filtering
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Solution Overview
Problem
Existing tachometer signal-based condition monitoring systems for rotating equipment face challenges in situations where tachometer sensors are impractical or difficult to use, leading to inaccurate fault detection due to spectral smearing and increased costs, weight, and installation complexity.
Innovation Solution
A method and system that generate a tachometer signal from vibration sensor data using band pass filtering, Fast Fourier Transform (FFT), and low pass filtering to reduce jitter, allowing for accurate fault detection and monitoring without the need for traditional tachometer sensors, utilizing techniques like forward/backward Infinite Impulse Response (IIR) filters and low pass FFT processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional tachometer sensors are used for condition monitoring, then measurement precision is improved, but device complexity, cost, and installation difficulty increase
Solution Approach 1:
The patent creates a virtual tachometer signal by processing vibration data through FFT analysis, effectively copying the function of a physical tachometer sensor without requiring actual sensor installation on the rotating component. The vibration-based tachometer signal is generated by identifying the fundamental frequency component in the vibration spectrum and using it as a reference for rotational speed measurement.
Solution Approach 2:
The patent replaces the mechanical/electrical tachometer sensor system with a signal processing approach that uses vibration analysis. Instead of using physical sensors to detect rotational position or speed, the system uses FFT-based spectral analysis of vibration data to extract rotational information, substituting mechanical measurement with computational analysis.
2Reliability
If tachometer sensors are installed on rotating components, then fault detection accuracy is improved, but weight and installation complexity increase
Solution Approach 1:
The patent makes the vibration sensor serve multiple functions: it simultaneously captures both the vibration data needed for fault detection and the rotational information needed for tachometer signal generation. This multi-functionality eliminates the need for separate tachometer sensors, reducing overall system weight while maintaining both fault detection accuracy and rotational speed measurement capability.
3Productivity
If vibration data is processed without filtering, then processing speed is improved, but measurement precision deteriorates due to spectral smearing
Solution Approach 1:
The patent applies band-pass filtering around the fundamental frequency before performing FFT analysis. This preliminary filtering action removes out-of-band noise and vibrations that would cause spectral smearing, ensuring that the subsequent spectral analysis produces accurate fault frequency measurements without requiring excessive computational resources for post-processing.
4Measurement precision
If high sample rates are used for vibration monitoring, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent extracts only the relevant frequency components from the vibration spectrum by applying band-pass filters centered on the fundamental frequency and its harmonics. This extraction approach allows the system to use standard sampling rates while maintaining measurement precision for fault detection, as only the frequency bands containing actual fault information are processed in detail, reducing overall computational energy requirements.
Data Source
AI summary
A system and method for generating a tachometer signal from a vibration sensor is disclosed in which an approximately idealized band pass filter is used along with a fast Fourier transform (FFT) to create a sufficient analytic signal to derive the tachometer signal for a shaft or other rotating component. In addition, jitter in the generated tachometer signal, or any tachometer signal, can be reduced by using an approximately idealized low pass filter and then transforming the filtered signal using a real FFT. These processes can be performed using a smart vibration sensor, which facilitates improved vibration analysis on rotating equipment where in the past the addition of a tachometer would be prohibitive due to cost, weight, certification requirements, or physical impracticality.