Optical Fiber Sensor Signal Normalization for Installation Variance
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Solution Overview
Problem
The acquired sensor signals in optical fiber sensors vary significantly depending on the installation state of the optical fiber, leading to difficulties in achieving accurate measurements.
Innovation Solution
A sensor signal processing apparatus and method that includes variation calculation means to receive sensor signals based on scattered light and calculate variations from a reference value, and normalization processing means to normalize these variations within a predetermined time, thereby calculating a normalized variation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the optical fiber sensor is used to detect vibrations and environmental changes, then the measurement capability is extended to new parameters, but the sensor signal varies significantly depending on installation state, reducing measurement accuracy
Solution Approach 1:
The patent transforms the raw sensor signal into a normalized variation signal by changing the parameter representation. Instead of using absolute light intensity values which are affected by installation state, the system calculates variations from reference values and normalizes them, thereby eliminating the influence of installation conditions while preserving the ability to detect environmental changes and vibrations
Solution Approach 2:
The patent introduces an intermediary processing stage between signal acquisition and measurement output. The normalization processing acts as a mediator that translates the installation-dependent raw signal into installation-independent normalized variation data, enabling accurate measurements across different installation scenarios
2Device complexity
If the sensor signal is used directly for measurement, then the system structure remains simple, but the fluctuation caused by varying installation states leads to inaccurate measurements
Solution Approach 1:
The patent performs preliminary normalization processing on the sensor signal before it is used for measurement. By pre-calculating the normalized variation from the raw signal, the system eliminates installation-state fluctuations in advance, ensuring that subsequent measurements are accurate without requiring complex real-time correction mechanisms
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 enables accurate measurement in optical fiber sensors regardless of the installation situation of the optical fiber, by standardizing the sensor signal variations and suppressing fluctuations caused by varying installation states.
Implementation Method 1
a sensor signal based on scattered light of a light pulse propagating through an optical fiber
Implementation Method 2
an optical fiber sensor that detects a mechanical vibration added to the optical fiber
Implementation Method 3
backscattered light called Brillouin scattered light is measured. The Brillouin scattered light has a property of causing a frequency shift when a distortion or the like is added to the optical fiber
Implementation Method 4
measuring an intensity change of backscattered light that returns in the optical fiber in a reverse direction
Data Source
AI summary
In optical fiber sensors, sensor signals obtained differ according to the circumstances of installation, in locations being observed, of optical fibers serving as sensors, and it is difficult to perform accurate measurements; therefore, a sensor signal processing apparatus according to the present invention includes variation calculation means for receiving a sensor signal based on scattered light of a light pulse propagating through an optical fiber, and calculating a variation of the sensor signal from a reference value; and normalization processing means for normalizing the variation within a predetermined time, and calculating a normalized variation.