Automated Health Monitoring of Rail Cars and Railroad Bridges Using Embedded Sensors

Abstract

Current maintenance operations and integrity checks on a wide array of structures require personnel entry into normally-inaccessible or hazardous areas to perform necessary nondestructive inspections. To gain access for these inspections, structure must be removed, sealant must be removed, disassembly processes must be completed, or personnel must be transported to remote locations. The use of in-situ sensors, coupled with remote interrogation, can be employed to overcome a myriad of inspection impediments stemming from accessibility limitations, complex geometries, the location and depth of hidden damage, and the isolated location of the structure. Furthermore, prevention of unexpected flaw growth and structural failure could be improved if on-board health monitoring systems were used to more regularly assess structural integrity. Reliable Structural Health Monitoring (SHM) systems can automatically process data, assess structural condition, and signal the need for specific maintenance actions. A research program has been completed to develop and validate Comparative Vacuum Monitoring (CVM) Sensors for surface crack detection. The test specimens included those designed to simulate crack origination sites on aircraft and bridge structures. The test matrix studied the affects of surface coating, skin thickness, and material type on the performance of the CVM sensors. Statistical methods using one-sided tolerance intervals were employed to derive Probability of Detection (POD) levels for each of the test scenarios. The result is a series of flaw detection curves that can be used to propose CVM sensors for crack detection. Complimentary, multi-year field tests were also conducted to study the deployment and long-term operation of CVM sensors on aircraft and bridges. This paper presents the quantitative crack detection capabilities of the CVM sensor, its performance in actual operating environments, and the prospects for structural health monitoring applications on a wide array of civil structures.