Application of the Spectrum Peak Positioning Technology Based on

BP Neural Network in Demodulation of Cavity Length of EFPI Fiber Optical Sensor

Open Access JCC

Optical fiber transmission

Laser light

source Isolator

Interference

analyzer

Coupler

DMFLock-in amplifier

EFPI sensor

Signal

processing unit

Signal source

Figure 1. The basic principle of EFPI fiber optical sensor

system diagram.

tributed and multiple parameter sensing. Especially EFPI

fiber optical sensor can work in the inflammable, explo-

sive, hig h te mperat ur e and high pressure envi ronments.

3. The Demodulation of EFPI Sensor Cavity

Length by Using the Spectrum Peak

Positioning Technology

3.1. The Basic Principle of the EFPI Sensor

Cavity Length Demodulation

F-P cavity length as shown in Figure 2 is between two

optical polishing surface distances. In order to achieve

the measurement of wide dynamic range and high resolu-

tion, accurate information of the cavity length is obtained

from optical interference signal, which is returned from

the EFPI fiber optical sensor through effective signal de-

modulation. Through tracking changes of wavelengths of

spectral peak in particular interfered order Cavity length

demodulation of EFPI fiber optical sensor which is based

on the spectral peak location will obtain the information

of cavity length. The demodulation method has many

kinds, such as: unimodal measurement, bimodal measure-

ment, BP neural network measurement etc [3]. Though

unimodal measurement resolution is very high, the range

of measurement is finite; bimodal measuring method can

realize the measurement of large dynamic range. How-

ever, the resolution is too low. This paper presents that

using BP neural network locates the spectral interference

spectrum, so that the reso lution of cav ity length wit h wide

dynamic range and high resolution can be achieved. Spec-

tral interferenc e signal s collected by the syste m are treated

to get the change information of long cavity through the

analysis of interference spectrum changes.

3.2. Spectral Peak Location Technology Based

on BP Neural Network

3.2.1. BP Neural Network

BP neural network is a multilayer feed forward network

[4], it mainly consists of three parts: input layer, output

Figure 2. The structure diagram of EFPI fiber optical sen-

sor.

layer and hidden layer. Function f are often used as the

transfer function of neurons to realize arbitrary nonlinear

mapping:

( )

1

1cx

fx e−

=+,

(1) [6]

c is the neurons input. Its basic principle is to minimize

the squared error between the expected value and the

output value by adjusting the weights of the network. BP

neural network is divided into forward propagation and

back propagation. In the training process of forward

propagation, each layer of neurons will only change with

a layer of neurons. When the output layer does not reach

the expected value, the actual error is calculated out and

then the error signal fed back to the original. Repeatedly

revising each layer neuron weights makes the error of

prediction to the minimum.

In the whole network, input layer [5] contains N neu-

ron 1

p, 2

p, 3

p,..., n

p, each neuron has a correspond-

ing weight. As shown in Figure 3, 1

p, 2

p,

,..., n

p

corresponding respectively to weights

,

,

,...,

. An offset

is in the hidden layer, all the neurons

and the corresponding weights do multiplication and ac-

cumul a t ion as network input s ignal

:

112 2totaln n

pG pGpG

λ

= +++

(2)

If the overall input signal is total

λ

, then

(3)

The input signal of each layer respectively enter the

transfer function f, output signal of neurons

can fi-

nally be obtained through operation processing,

Kf

ω

= (4)

3.2.2. The Tracing of Spectral Peak by Using BP

Neural Network

The essence of application of BP neural network spec-

trum peak tracing is to make the correct judgment for

spectral peak of the normalized interference spectrum.

The nonlinear functional approximation of BP neural

network can effectively identify discrete changes of F-P

cavity length in phase space, so that the wavelength val-