Semiconductor Switching Noise Spectrum Analysis With Phase Synthesis
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Solution Overview
Problem
Existing noise analysis techniques struggle to accurately and efficiently analyze noise in power conversion circuits with changing on and off period lengths, leading to reduced accuracy and increased computation time.
Innovation Solution
A noise analysis apparatus and method that calculates a sum spectrum of noise by acquiring information on multiple switching occurrences, generating phase difference information, and performing a phase transform to reflect time differences in switching occurrences, thereby accurately reflecting changing on and off period lengths without significantly increasing computation time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If transient waveforms for multiple switching periods are used as noise source data to reflect changing on and off period lengths, then noise analysis accuracy is improved, but the time width subject to Fourier transform increases and computation time increases
Solution Approach 1:
The patent segments the switching periods into individual transient waveform data for each switching event. Instead of performing Fourier transform on the entire multi-period waveform, it processes each switching period separately, extracts amplitude and phase information, and then synthesizes the sum spectrum. This segmentation reduces the computational burden of Fourier transform while maintaining accuracy through proper phase transformation.
Solution Approach 2:
The patent performs preliminary processing by extracting amplitude and phase information from each individual transient waveform before synthesis. By pre-calculating these parameters for each switching event and storing them, the system avoids the need for a lengthy Fourier transform of the complete multi-period signal, thus reducing computation time while preserving the phase relationships necessary for accurate noise analysis.
2Adaptability or versatility
If transient waveforms for multiple switching periods are used as noise source data, then the behavior of changing on and off period lengths is reflected, but the number of time steps increases and Fourier transform becomes more complex
Solution Approach 1:
The patent divides the multi-period waveform into separate single-period transient waveforms, each processed independently. This segmentation allows the system to handle variable on and off period lengths in each switching event without increasing the complexity of the Fourier transform operation, as each transformation is performed on a single period with consistent timing characteristics.
Solution Approach 2:
The patent transforms the problem from the time domain to the frequency domain by extracting amplitude and phase parameters for each switching event. This parameter transformation allows the system to accommodate varying on and off period lengths through phase adjustments rather than requiring complex Fourier transforms of variable-length signals, thus maintaining computational simplicity while achieving adaptability.
3Productivity
If a transient waveform for one switching period is used as noise source data, then computation time is reduced, but the behavior of changing on and off period lengths cannot be reflected in the noise source
Solution Approach 1:
The patent merges multiple single-period transient waveforms by synthesizing their individual Fourier transform results. Each waveform is transformed separately to maintain computational efficiency, then the results are combined through addition while applying appropriate phase transformations. This merging process preserves the variable on and off period length information from each switching event while maintaining the computational speed benefits of processing individual periods separately.
Solution Approach 2:
The patent introduces phase transformation as an intermediary step between individual Fourier transforms and the final sum spectrum. This intermediary process allows the system to combine results from multiple single-period transforms while accurately representing the time relationships and varying period lengths, thus bridging the gap between computational efficiency and analytical accuracy.
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 rapid and accurate derivation of simulated noise results, even when semiconductor devices have changing on and off period lengths, by minimizing the time width subject to Fourier transform and efficiently handling multiple switching events.
Implementation Method 1
generates a plurality of pieces of phase difference information respectively corresponding to the plurality of occurrence times acquired by the first acquisition unit for subjecting a noise spectrum in the switching of the semiconductor device to a phase transform
Data Source
AI summary
A time range setting unit acquires a plurality of occurrence times at which switching of a semiconductor device occurs a plurality of times, respectively. A phase transform units generates a plurality of pieces of phase difference information for subjecting a noise spectrum in the switching of the semiconductor device to a phase transform to reflect a time difference between the plurality of occurrence times. An addition unit adds together a plurality of noise spectra that are obtained through a phase transform of the noise spectrum in the switching of the semiconductor device by the plurality of pieces of phase difference information, respectively, to calculate a result of calculating a sum spectrum generated by the switching of the semiconductor device.