Electric Motor Diagnosis Device for Bearing Degradation Detection
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Solution Overview
Problem
Conventional abnormality diagnosis methods for induction motors face difficulties in detecting sideband frequencies near the power source frequency due to increased spectrum intensity from load torque variations, making it hard to diagnose motor abnormalities accurately.
Innovation Solution
An electric motor diagnosis device that includes an electric current input unit, FFT analysis unit, peak detection unit, averaging unit, sideband frequency extraction unit, and rotational frequency band determination unit to calculate and compare peak differences between power source and rotational frequency bands, allowing for the detection of sideband frequencies and bearing degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If load torque variations occur in an induction motor, then spectrum intensity increases on both sides of the power source frequency, but this makes it difficult to detect sideband frequencies
Solution Approach 1:
The patent segments the frequency spectrum analysis into distinct components: power source frequency analysis and sideband frequency analysis. By separating these analyses and applying different processing methods to each, the system can accurately detect sideband frequencies even when spectrum intensity increases due to load torque variations.
Solution Approach 2:
The patent introduces an intermediary processing step between raw spectrum analysis and sideband detection. This intermediary involves calculating the difference between the actual spectrum and a reference spectrum, which acts as a mediator to highlight sideband frequencies while suppressing the effects of load torque variations.
2Measurement precision
If conventional frequency analysis is performed on motor current, then sideband frequencies can be detected under stable conditions, but the method fails when load torque varies
Solution Approach 1:
The patent implements a dynamic reference spectrum that adapts to varying load conditions. Instead of using a fixed reference, the system continuously updates the reference spectrum based on current operating conditions, allowing accurate sideband detection across different load scenarios.
Solution Approach 2:
The patent changes the analysis parameters dynamically based on operating conditions. By adjusting the reference spectrum and analysis thresholds according to load variations, the system maintains high detection precision across diverse operating conditions.
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
Enables accurate diagnosis of motor abnormalities and bearing degradation by reliably detecting sideband frequencies even with varying load torque, improving diagnostic precision and reducing noise interference.
Implementation Method 1
an FFT analysis unit configured to analyze a power spectrum of the electric current from the electric current input unit
Data Source
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Figure 5
AI summary
[Problem to be Solved] Provided is an electric motor diagnosis device capable of diagnosing the presence or absence of abnormality of an electric motor by means of detecting sideband frequencies appearing in peak states on both sides in vicinity to a power source frequency, even in the motor whose load torque varies. [Means for Solving the Problem] In the device, an electric current of an electric motor 5 is detected by an electric current detector 4, and inputted from an electric current input unit 10; a smoothing process is carried out on a plurality of charges of analytical results of power spectra obtained by a logic calculation unit 11 by performing frequency analysis on an electric current waveform when the electric current is stable; from analytical results of power spectra on which the smoothing process is carried out, sideband frequencies are detected, and also the presence or absence of abnormality of the motor 5 is determined by calculating a difference value between a power spectrum's peak of a power source frequency of the motor 5 and a power spectrum's peak in a rotational frequency band thereof; and a warning is outputted from a warning output unit 12 when determining abnormality being caused.