Crack Monitoring of Lock Infrastructure Using Strain Sensors

Abstract

Inland navigation systems facilitate barge traffic, the most efficient tonnage per fuel method of transportation. Miter gates allow barges to bypass navigational dams. The Dalles downstream miter gate has experienced numerous instances of cracking, threatening its continued operation and shipping on the Columbia River. The earliest instance of cracking led to the installation of a sensor system to ensure continued operation. The most recent serious cracking has resulted in serious efforts to track the cracking by moving some existing sensors and leveraging on-site underwater ROV cameras. A simple method is proposed to choose strain gage locations sensitive to cracks. A corresponding structural health monitoring algorithm to monitor the crack with strain gage data would benefit from supervised learning techniques. Thus, the existing strain gage system is leveraged to validate the finite element model, which in turn enables supervised learning techniques. It is found to be necessary to update the finite element model for acceptable validation.