The integration of distributed optical fiber temperature sensor with supervisory control and data acquisition （SCADA） system is proposed and implemented. In the implementation of the integration, both the compatibil...The integration of distributed optical fiber temperature sensor with supervisory control and data acquisition （SCADA） system is proposed and implemented. In the implementation of the integration, both the compatibility with traditional system and the characteristics of distributed optical fiber temperature sensor is considered before Modbus TCP/IP protocol is chosen. The protocol is implemented with open source component Indy. The Modbus TCP/IP protocol used in the system is proved to be fast and robust.展开更多
A landslide monitoring application is presented by using a high-resolution distributed fiber optic stress sensor. The sensor is used to monitor the intra-stress distribution and variations in landslide bodies, and can...A landslide monitoring application is presented by using a high-resolution distributed fiber optic stress sensor. The sensor is used to monitor the intra-stress distribution and variations in landslide bodies, and can be used for the early warning of the occurrence of the landslides. The principle of distributed fiber optic stress sensing and the intra-stress monitoring method for landslides are described in detail. By measuring the distributed polarization mode coupling in the polarization-maintaining fiber, the distributed fiber stress sensor with stress measuring range 0 to 15 MPa, spatial resolution 10 cm and measuring range 0.5 km, is designed. The warning system is also investigated experimentally in the field trial.展开更多
Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors i...Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors in signal acquisition conditions,such as manufacturing process,deployment,and environments,current AI schemes for signal recognition of DSS frequently encounter poor generalization performance.In this paper,an adaptive decentralized artificial intelligence(ADAI)method for signal recognition of DSS is proposed,to improve the entire generalization performance.By fine-tuning pre-trained model with the unlabeled data in each domain,the ADAI scheme can train a series of adaptive AI models for all target domains,significantly reducing the false alarm rate(FAR)and missing alarm rate(MAR)induced by domain differences.The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme,showcasing a FAR of merely 4.3%and 0%,along with a MAR of only 1.4%and 2.7%within two specific target domains.The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.展开更多
基金supported by the National Natural Science Foundation of China under Grant No. 60608009Science Foundation of Zhejiang Province under Grant No. Y107091 and ScienceTechnology Department of Zhejiang Province under Grant No. 2008C21172.
文摘The integration of distributed optical fiber temperature sensor with supervisory control and data acquisition （SCADA） system is proposed and implemented. In the implementation of the integration, both the compatibility with traditional system and the characteristics of distributed optical fiber temperature sensor is considered before Modbus TCP/IP protocol is chosen. The protocol is implemented with open source component Indy. The Modbus TCP/IP protocol used in the system is proved to be fast and robust.
基金supported by the National Natural Science Foundation of China under Grant No. 60377021partially supported by Program for New Century Excellent Talents in University under Grant. No. NCET-07-0152Sichuan Scientific Funds for Young Researchers under Grant No. 08ZQ026-012.
文摘A landslide monitoring application is presented by using a high-resolution distributed fiber optic stress sensor. The sensor is used to monitor the intra-stress distribution and variations in landslide bodies, and can be used for the early warning of the occurrence of the landslides. The principle of distributed fiber optic stress sensing and the intra-stress monitoring method for landslides are described in detail. By measuring the distributed polarization mode coupling in the polarization-maintaining fiber, the distributed fiber stress sensor with stress measuring range 0 to 15 MPa, spatial resolution 10 cm and measuring range 0.5 km, is designed. The warning system is also investigated experimentally in the field trial.
基金financial supports from the National Natural Science Foundation of China(NSFC)(No.61922033&U22A20206)Zhejiang Provincial Market Supervision Bureau Young Eagle Plan project under Grant CY2022228.
文摘Artificial intelligence(AI)plays a critical role in signal recognition of distributed sensor systems(DSS),boosting its applications in multiple monitoring fields.Due to the domain differences between massive sensors in signal acquisition conditions,such as manufacturing process,deployment,and environments,current AI schemes for signal recognition of DSS frequently encounter poor generalization performance.In this paper,an adaptive decentralized artificial intelligence(ADAI)method for signal recognition of DSS is proposed,to improve the entire generalization performance.By fine-tuning pre-trained model with the unlabeled data in each domain,the ADAI scheme can train a series of adaptive AI models for all target domains,significantly reducing the false alarm rate(FAR)and missing alarm rate(MAR)induced by domain differences.The field tests about intrusion signal recognition with distributed optical fiber sensors system demonstrate the efficacy of the ADAI scheme,showcasing a FAR of merely 4.3%and 0%,along with a MAR of only 1.4%and 2.7%within two specific target domains.The ADAI scheme is expected to offer a practical paradigm for signal recognition of DSS in multiple application fields.
