Partial Discharge Detection Using Real-Time Spectrum Analysis
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Solution Overview
Problem
Conventional partial discharge detection systems in electrical drive systems, particularly in aircraft electric and hybrid-electric propulsion systems, face challenges due to the interference from Pulse Width Modulated (PWM) waveforms, leading to inconsistent and unreliable detection of partial discharge signals, especially at high altitudes, resulting in premature insulation failure.
Innovation Solution
A system and method utilizing a real-time spectrum analyzer that transforms signals from the time domain to the frequency domain using Fast Fourier Transform (FFT) and applies signal discrimination based on frequency domain profiles to differentiate partial discharge signals from switching noise, enabling effective online detection without the need for filters or voltage signal triggering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional time domain analysis with high frequency filters synchronized with voltage signal triggering is used, then the detection system can operate with standard equipment, but the low frequency bands of PD signals are lost or strongly attenuated, reducing measurement precision
Solution Approach 1:
Instead of filtering out high frequency content as conventional systems do, this patent inverts the approach by using real-time spectrum analysis to capture and analyze the full frequency spectrum including high frequency components. The system transforms time domain signals to frequency domain using FFT, allowing PD signals to be identified through their spectral characteristics rather than being filtered away.
Solution Approach 2:
The patent transitions from one-dimensional time domain analysis to two-dimensional frequency domain analysis by applying Fast Fourier Transform. This dimensional change allows PD signals to be distinguished from PWM noise through spectral fingerprinting, where PD signals exhibit characteristic frequency distributions that differ from switching noise.
2Reliability
If high frequency filters synchronized with voltage signal triggering are applied, then the system can reduce noise interference, but PD signals do not correlate with the synchronized voltage signal, making time domain recognition difficult
Solution Approach 1:
The patent moves the detection problem from time domain to frequency domain using FFT transformation. In the frequency domain, PD signals can be discriminated from PWM noise through spectral analysis without requiring synchronization with voltage triggering, as PD signals exhibit distinct frequency characteristics that are independent of the PWM switching cycle.
Solution Approach 2:
The patent introduces real-time spectrum analysis as an intermediary between signal acquisition and PD detection. This intermediary process transforms raw time domain signals into frequency domain representations, allowing PD signals to be identified through their spectral fingerprints rather than direct time domain correlation with voltage signals.
3Measurement precision
If conventional PD monitoring equipment is used, then the system structure remains simple, but PD signals cannot be detected satisfactorily, especially sporadic PD signals under PWM conditions
Solution Approach 1:
The patent implements dynamic real-time spectrum analysis that continuously updates the frequency domain representation of signals. This dynamic approach allows sporadic PD signals to be captured and identified as they occur, rather than requiring steady-state conditions or averaging over multiple cycles, thereby improving detection of intermittent discharge events.
Solution Approach 2:
By transforming the detection problem from time domain to frequency domain through real-time FFT, the system gains the ability to identify sporadic PD signals through their spectral characteristics. PD signals exhibit consistent frequency domain patterns even when sporadic in time domain, enabling reliable detection of intermittent discharge events.
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
This approach provides reliable and accurate online partial discharge detection, improving the health monitoring and diagnosis of insulation systems, allowing for proactive maintenance without system interruption and reducing the risk of premature failure.
Implementation Method 1
A system and method utilizing a real-time spectrum analyzer that transforms signals from the time domain to the frequency domain using Fast Fourier Transform (FFT)
Data Source
AI summary
Aspects of the present disclosure are directed to systems and methods for detecting Partial Discharge (PD) associated with wide bandgap semiconductor-based electrical drive systems in real time. In one aspect, signals, including noise associated with drive switching and other background noises are detected using a sensing device. The signals are received by a real-time spectrum analyzer. The spectrum analyzer transforms the signals into the frequency domain and determines or registers the frequency domain profiles of the signals. The spectrum analyzer performs signal discrimination between at least one other signal included within the signals and switching noise based on their frequency domain profiles. Based on the discrimination analysis, the presence of a partial discharge signal may be detected. A physics-based signal discrimination approach can also be used for signal discrimination, for example utilizing pressure-dependency of characteristics of a PD signal.