Optical fiber state evaluating method based on combination of improved membership function and neural network
A membership function and neural network technology, applied in the field of optical fiber line status evaluation and analysis, can solve the problems of unable to find potential faults of optical fiber lines, unable to evaluate and analyze the status of optical fiber lines, etc., to achieve good fitting accuracy and meet the requirements of reliability , the effect of fast convergence speed
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[0021] Specific implementation mode 1. Combination Figure 1 to Figure 3 Illustrate this embodiment, based on the improved membership function combined with the neural network optical fiber state evaluation method, the method is implemented by the following steps:
[0022] Step 1. Data preprocessing:
[0023] Since the optical fiber vibration parameters and temperature parameters are time series data collected at every certain time interval, when the optical fiber vibration amplitude and temperature change sharply, the impact on the status of the optical fiber line is obvious, so all the extreme values of the vibration parameters S and temperature parameters T are selected. As the original sample of factors affecting the fiber state, respectively, S=(S 1 ,S 2 ,...,S m ), T=(T 1 , T 2 ,...,T m ); by better observing its change characteristics, the extreme value sequence is first-order difference: S(m)=S(m+1)-S(m), T(m)=T(m+1)-T(m ), where m is the ordinal number of t...
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