Vibration Signal Processing via Lissajous Angle Spectrum Analysis
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Solution Overview
Problem
Existing methods for abnormality diagnosis in rotary devices, such as JP-A-2000-258305, require skilled techniques for setting reference Lissajous waveform figures and threshold values, making it difficult to determine the state of the object accurately.
Innovation Solution
A signal processing method that includes acquiring measurement data from multiple sensors, generating Lissajous figures, transforming coordinates into polar coordinates, and calculating maximum peak intensities in frequency spectra to analyze the state of an object.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reference Lissajous waveform figures and threshold values are set using skilled techniques, then abnormality diagnosis can be performed, but the process becomes complex and difficult to operate
Solution Approach 1:
The system automatically determines abnormality by comparing actual Lissajous waveform figures with reference figures stored in a database, eliminating the need for operators to manually set threshold values. The determination unit autonomously performs the diagnosis by retrieving appropriate reference figures based on device information and comparing waveforms, making the system self-sufficient and easy to operate.
Solution Approach 2:
Reference Lissajous waveform figures for various abnormality conditions are pre-calculated and stored in a database before actual diagnosis operations. This preliminary preparation allows the system to quickly retrieve and compare against stored reference patterns during operation, eliminating the need for real-time threshold setting by skilled operators.
2Adaptability or versatility
If multiple reference Lissajous waveform figures are set for different abnormality causes, then comprehensive diagnosis is possible, but the device complexity increases
Solution Approach 1:
A single determination unit handles all abnormality diagnoses by retrieving appropriate reference Lissajous waveform figures from a database based on device information. This universal approach allows comprehensive diagnosis coverage without increasing device complexity, as the system uses one multi-functional component rather than multiple specialized ones.
Solution Approach 2:
A database serves as an intermediary between the sensor unit and determination unit, storing pre-calculated reference Lissajous waveform figures. This intermediary component allows the system to maintain comprehensive diagnostic capabilities while keeping the core processing logic simple and unified in the determination unit.
3Measurement precision
If Lissajous waveform figures are used for state determination, then vibration analysis is achieved, but noise and fluctuations make accurate determination difficult
Solution Approach 1:
The system creates reference Lissajous waveform figures that represent ideal or known-good vibration patterns, storing these reference copies in a database. By comparing actual waveform copies against these reference copies, the system can accurately determine device state despite noise and fluctuations in the measured data.
Data Source
AI summary
A signal processing method includes: acquiring first measurement data based on a signal output from a first sensor configured to detect a physical quantity of a first axis generated by a vibration of an object and second measurement data based on a signal output from a second sensor configured to detect a physical quantity of a second axis generated by the vibration of the object; generating a Lissajous figure based on the first measurement data and the second measurement data; transforming coordinates of each point in the Lissajous figure into polar coordinates and generating time series data of a first angle which is an angle formed between the first axis and a straight line, the straight line being obtained by projecting a straight line passing through an origin and each point in the Lissajous figure onto a plane including the first axis and the second axis; and executing frequency analysis on the time series data of the first angle and calculating a first maximum peak intensity which is a maximum peak intensity in a first frequency spectrum obtained by the frequency analysis.