Advanced Learning Algorithms for the Proactive Infrasonic Pipeline Evaluation Network (PIGPEN) Pipeline Encroachment Warning System
| 项目名称： | Advanced Learning Algorithms for the Proactive Infrasonic Pipeline Evaluation Network (PIGPEN) Pipeline Encroachment Warning System |
| 摘要： | This research will advance development of self-training algorithms supporting seismic sensor systems that provide real-time warning of unauthorized right-of-way encroachment and excavation activity near a pipeline. he outcome will enable the sensor system to optimize its intruder detection algorithms based on learned characteristics of its local environment. Field tests are expected to demonstrate better than 97% alarm reliability with few false alarms. Physical Sciences Inc. (PSI), with American Innovations Ltd. (AI) and NYSEARCH, are addressing the technology gap of Early Warning Damage Prevention Monitoring Systems, specifically Advanced Development of Algorithms for Detecting Digging Threats and Avoiding False Alarms. This research will implement and evaluate self-training algorithms in the Proactive Infrasonic Gas Pipeline Evaluation Network (PIGPEN) autonomous distributed seismic sensor system. PIGPEN provides real-time warning of unauthorized right-of-way encroachment and excavation activity near a pipeline. Early warning enables a response to the potential intrusion in time to prevent pipeline damage, and thus preclude the additional cost and risk of repairs. The ideal PIGPEN alarm system would activate an intruder notification with 100% reliability and no false alarms. The project will enhance reliability by enabling PIGPEN to learn the characteristics of its local environment and optimize its intruder detection algorithms based on learned experience. Field tests are expected to demonstrate better than 97% alarm reliability with few false alarms. |
| 状态： | Active |
| 资金： | 267000.00 |
| 资助组织： | Pipeline and Hazardous Materials Safety Administration |
| 项目负责人： | Merritt, James |
| 执行机构： | Physical Sciences Incorporated |
| 开始时间： | 20100930 |
| 实际结束时间： | 20120331 |
| 主题领域： | Data and Information Technology；Maintenance and Preservation；Pipelines |
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