The Architecture Design Of Submarine Magnetic Detection Optical Fiber Network Based On EPON Technology

Covering about 70% of the earth,the ocean,which contains lots of sources of mineral,fishery,and hydrology,plays a significant role in economy,national defense and ecological environment.However,it is difficult to develop the marine owing to the sheer complexity of marine environment.Additionally,the ocean is easily invaded by some military equipment with high concealment,such as submarines and frogmen.Therefore,it is urgent to find some suitable detecting means of marine to develop its economy and ensure its safety.With the rapid development of the noise reduction technology,the acoustic detection has quite a few limitations in marine detection,which becomes hard to meet the needs.Additionally,the single-point detection is difficult to satisfy because of the detection accuracy,the detection range,etc.Considering that the magnetic detection technology has the characteristics of high resolution and good stability,it is maturely applied in the resource exploration,anti-invasion and other fields.When it comes to the sensor networking,we found that the Ethernet Passive Optical Network(EPON)has the characteristics of low cost and long transmission distance,and it is widely applied in access network system.Therefore,we adopted magnetic anomaly detection technology and EPON to build a network of submarine optical fiber magnetic detection.In this paper,we first investigated some famous submarine detection networks both at home and abroad,and then chose the specific target based on the current conditions and studied the magnetic anomaly of the specific target through theoretical analysis and software simulation.In the next section,we discussed the principle and the key technologies of EPON,and studied the topology protection based on the architecture and EPON technology.At last,according to the actual demands and the current conditions,we drew the final plan and built a model of detection network,and conducted some experiments,and then we studied the performance of our network based on the results and obtained data.The results showed that the model could achieve detection function,and had good detection performance,in line with the expected target.