AC Signal Abnormality Detection via Sinusoidal Parameter Transformation
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Solution Overview
Problem
Existing methods for detecting abnormalities in alternating current (AC) signals are not accurate, particularly in distinguishing between ideal and distorted waveforms, leading to difficulties in identifying issues like stepped zero crossing, zero crossing distortion, transient overvoltage, and frequency variations.
Innovation Solution
An abnormality detection method that calculates the value of sin2ωt+cos2ωt for an AC signal and determines abnormalities based on a threshold range, using a high-speed sampling apparatus with an FPGA for real-time processing and alarm signaling, allowing for precise identification of signal distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a low pass filter is used to smooth the input waveform for abnormality detection, then the detection process becomes simpler, but the accuracy of detecting signal distortions deteriorates
Solution Approach 1:
The patent transforms the AC signal parameters by calculating sin²(ωt) and cos²(ωt) values from the detected signal, then sums these transformed parameters. For ideal sine waves, this transformation produces a constant value, while distorted waves produce varying values. This parameter transformation approach enables accurate abnormality detection without requiring complex filtering operations, thus resolving the contradiction between detection simplicity and accuracy.
2Ease of manufacture
If traditional waveform analysis methods are used, then the detection method is easier to implement, but the ability to distinguish between ideal and distorted waveforms deteriorates
Solution Approach 1:
The patent applies mathematical transformation to the detected AC signal parameters, converting the waveform analysis problem into a parameter comparison problem. By calculating sin²(ωt) + cos²(ωt) and comparing against a threshold, the system achieves high discrimination accuracy between ideal and distorted waveforms while maintaining implementation simplicity through straightforward arithmetic operations.
Solution Approach 2:
The patent replaces complex waveform visualization and manual analysis with automated mathematical transformation and digital threshold comparison. The FPGA performs real-time calculation of sin²(ωt) + cos²(ωt) values and automatically compares them against predefined thresholds, substituting mechanical/visual analysis with electronic computation to achieve both ease of implementation and high precision.
3Speed
If real-time processing is implemented using FPGA, then the response time to detect abnormalities improves, but the device complexity increases
Solution Approach 1:
The patent replaces software-based or manual waveform analysis with hardware-based FPGA implementation. The FPGA directly computes sin²(ωt) + cos²(ωt) values and performs threshold comparisons in real-time, achieving high-speed abnormality detection. While FPGA adds some complexity, it eliminates the need for complex external processing systems, and the mathematical approach keeps the logic simple and efficient.
Solution Approach 2:
The patent implements a universal detection algorithm in the FPGA that can identify multiple types of waveform abnormalities (distortion, frequency variations, transient overvoltage) using a single mathematical transformation approach. This multi-functional capability is achieved through one unified calculation method, avoiding the need for separate detection circuits for each abnormality type, thus managing device complexity while maintaining high detection speed.
Data Source
AI summary
An abnormality detection method according to one aspect of the present disclosure is a method of detecting an abnormality in an AC signal to be input from an AC power supply. The method includes, where an ideal AC signal is represented as V0 sin ωt (V0: amplitude, co: angular frequency, t: time), calculating an arithmetic value including a value represented by sin2ωt+cos2ωt and determining that the AC signal is abnormal when the arithmetic value is out of a threshold range.