Precision positioning vibration fiber manufacturer-INNO

Fiber optic needs to be able to accurately locate the point of occurrence in any measurement. If the error is large, there is no need to use fiber optic sensors to measure physical parameters. FJINNO is a manufacturer of precision positioning vibration fiber optic.

Когда optical fibers are affected by external factors such as temperature, давление, вибрация, и т. д., интенсивность, фаза, частота, состояние поляризации, и другие параметры проходящего света в волокне соответственно изменятся. By measuring these parameters of the transmitted light, соответствующие физические величины могут быть получены. Эта технология называется технологией оптоволоконного зондирования..
Compared to traditional electric quantity sensors, fiber optic sensors have the advantages of high sensitivity, анти-электромагнитные помехи, маленький размер, бюджетный, and can be used for long-distance distributed measurement. Поэтому, с конца 1970-х годов, fiber optic sensing technology has been widely developed, с распределенное оптоволокно sensing technologies based on Rayleigh scattering, Бриллюэновское рассеяние, Комбинационное рассеяние, и т. д.. Среди них, polarized light time-domain reflection technology (ПОДР) is a relatively common distributed fiber optic sensing technology.

Fiber optic vibration precise positioning host

1. Maintain consistent sensitivity of detection signals
2. Capable of real-time and complete extraction of signal features
By adopting a multi node hardware computing framework and utilizing FPGA and DSP for real-time acquisition and processing of detection signals, it is possible to quickly complete the calculation of large amounts of multi-channel data, extract data features in a timely manner, and provide sufficient signal features for intrusion behavior recognition and judgment.
3. Has strong pattern recognition ability
The use of neural network technology, combined with the frequency domain and time domain characteristics of signals, greatly improves the intelligent recognition ability of vibration signals. Through the adaptive learning function of neural networks, learning can be tailored to the environment of each defense zone, avoiding interference from environmental factors in intrusion behavior judgment, and improving the system’s ability to detect false alarms in various environments.
4. Adopting anti dismantling design for defense zone equipment
By adopting more professional technology, the equipment can effectively detect external damage to the equipment, whether in deployed or disarmed states, ensuring that the equipment is always in normal operation.
5. UV resistant design
Design UV protection for outdoor equipment to effectively prevent aging and damage caused by factors such as UV radiation, ensuring that the equipment can work in the outdoor environment for a long time.