Amplitude Phase Fault Detection in Measurement Signals
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Solution Overview
Problem
Current methods fail to accurately determine the proportion of individual interference influences on error variables in digitally modulated single-carrier transmission signals due to the complexity of causal technical relationships, making it impossible to subdivide error variables into specific groups of interference-related influences.
Innovation Solution
A method and device that record and sort in-phase components of noisy measurement signals, calculate error variables for deterministic and stochastic amplitude and phase disturbances by forming sums and differences, and scale these variables to determine specific error magnitudes and ratios, allowing for the characterization of individual interference types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple different faults are present simultaneously in a measurement signal, then the total fault size can be measured, but it becomes impossible to determine the proportion of each individual fault due to complex causal relationships
Solution Approach 1:
The patent segments the total error into distinct components by separating in-phase components (I) from quadrature components (Q). The in-phase components capture deterministic amplitude disturbances and in-phase noise, while quadrature components capture quadrature errors and orthogonal interference. This segmentation allows individual fault proportions to be determined independently through separate calculation paths for I and Q components.
Solution Approach 2:
The patent introduces intermediate error variables as mediators to bridge the gap between total error measurement and individual fault characterization. These intermediate variables (such as error variables characterizing deterministic amplitude disturbance, stochastic amplitude and phase disturbance, and deterministic phase disturbance) serve as computational intermediaries that decompose the total error into attributable components through structured mathematical relationships.
2Loss of information
If the total fault size is measured in a noisy measurement signal, then an overall error variable is obtained, but the subdivision of error variables into proportions attributable to individual interference groups is not known
Solution Approach 1:
The patent applies segmentation by dividing the error analysis into distinct phases: first determining intermediate error variables from in-phase components, then separately determining additional error variables from quadrature components. This phased segmentation preserves information about individual interference types by processing different signal components through dedicated calculation paths rather than treating the total error as a single undifferentiated quantity.
Solution Approach 2:
The patent transitions from one-dimensional total error measurement to multi-dimensional error characterization by introducing separate error variables for different interference types (deterministic amplitude, stochastic amplitude and phase, deterministic phase). This dimensional expansion allows the system to capture error contributions from multiple interference groups simultaneously, each represented in its own computational dimension.
3Measurement precision
If intermediate error variables are determined first and then additional error variables are calculated from them, then individual fault proportions can be identified, but the calculation process becomes complex
Solution Approach 1:
The patent applies preliminary action by first determining intermediate error variables from in-phase components before proceeding to calculate additional error variables from quadrature components. This preliminary determination establishes a foundation of known error characteristics that simplifies subsequent calculations, as the additional error variables can be derived systematically from the already-determined intermediate variables rather than requiring simultaneous solution of all error components.
Solution Approach 2:
The calculation process is segmented into distinct computational stages: Stage 1 determines intermediate error variables using only in-phase components, Stage 2 determines additional error variables using quadrature components and the intermediate variables from Stage 1. This segmentation of the calculation process reduces complexity by breaking down a potentially intractable simultaneous calculation into sequential, manageable steps with clear dependencies.
Data Source
Figure 1A~1F
Figure 2~3
Figure 4A
AI summary
The method involves detecting in-phase-portions of interferences contained in a disturbed measuring signal. The detected in-phase-portions are sorted into two classes of in-phase-portions corresponding to its size. Squared in-phase-portions are summed to a total, and associated squared amplitudes of an undisturbed measuring signal are summed to another total. A flaw size characterizing an amplitude interference is determined from the totals. Another flaw size characterizing a deterministic amplitude interference is determined. Independent claims are also included for the following: (1) a method for determining a flaw size characterizing a deterministic phase interference of a measuring signal (2) a device for determining a flaw size characterizing a deterministic phase interference of a measuring signal.