Sensor Signal Linearization via Variable Interval Interpolation
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Solution Overview
Problem
Sensors often produce output signals with nonlinearities, making it challenging to capture physical parameters like temperature, pressure, or position accurately, as seen in magnetic field sensors where nonlinear distortions occur beyond a certain range, leading to measurement errors.
Innovation Solution
The approach involves using linearization points to divide the value range into intervals of varying lengths, allowing for flexible resolution by multiplying an initial interval length by a non-integer factor, enabling linear interpolation and reducing memory requirements by using fewer linearization points in more linear sections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform linearization points are used to divide the measurement region, then sufficient linearization can be achieved in nonlinear sections, but memory requirements increase and device complexity increases
Solution Approach 1:
The patent applies local quality by using different interval lengths for different sections of the measurement range. Specifically, the measurement range is divided into a first section and a second section, with the first section having a larger number of linearization points for high-precision requirements, and the second section having fewer linearization points. This allows each section to have optimized linearization quality according to its specific needs, reducing overall memory requirements while maintaining accuracy where critical.
Solution Approach 2:
The patent segments the measurement range into multiple sections with different linearization point densities. By dividing the overall measurement range into distinct sections (first section and second section), each with tailored linearization point distribution, the system achieves efficient memory utilization. The segmentation allows critical regions to receive higher linearization resolution while non-critical regions use coarser resolution.
2Measurement precision
If more linearization points are used to improve linearization in nonlinear sections, then measurement accuracy improves, but device complexity and memory usage increase
Solution Approach 1:
The patent implements local quality by assigning different levels of linearization processing to different measurement sections. The first section, which likely corresponds to more nonlinear or critical measurement regions, receives denser linearization point distribution for higher accuracy. The second section uses sparser linearization points, reducing processing complexity where high precision is less critical. This localized approach optimizes the balance between accuracy and complexity.
3Device complexity
If uniform interval lengths are used for linearization points, then device complexity is reduced, but measurement precision decreases in nonlinear sections
Solution Approach 1:
The patent directly applies local quality by using different interval lengths for different sections. The first section employs smaller interval lengths with more linearization points to capture nonlinear characteristics accurately, while the second section uses larger interval lengths. This heterogeneous interval structure maintains device relative simplicity while significantly improving measurement precision in nonlinear regions compared to uniform interval approaches.
Data Source
AI summary
An apparatus for linearizing an input signal includes a memory, in which an output value is stored for each of a plurality of linearization points. The linearization points divide a value range into a plurality of intervals. Each interval is delimited by a first linearization point with an assigned first output value and a second linearization point with an assigned second output value. The apparatus includes a computer device configured to determine the interval in which an input signal value of the input signal is located and to calculate a linearized output signal value for the input signal value by way of a linear interpolation using the input signal value, the first output value of this interval, and the second output value of this interval. At least two of the intervals have different interval lengths, which are formed by multiplication of an output interval length by an integer factor.