SBIR-STTR Award

Broken Rail Detection from Flashing Rear End Device
Award last edited on: 3/14/2019

Sponsored Program
SBIR
Awarding Agency
DOT
Total Award Amount
$299,999
Award Phase
2
Solicitation Topic Code
171FR2
Principal Investigator
Bo Ling

Company Information

Migma Systems Inc

1600 Providence Highway Suite 211
Walpole, MA 02081
   (508) 660-0328
   contact@migmasys.com
   www.migmasys.com
Location: Single
Congr. District: 08
County: Norfolk

Phase I

Contract Number: DTRT5717C10146
Start Date: 00/00/00    Completed: 00/00/00
Phase I year
2017
Phase I Amount
$150,000
In Phase I, Migma Systems propose to develop a robust system for detection of railway track surface cracks. Automated railway inspection is critical for ensuring the safety of public transportation. Rails often break under trains and broken tracks can lead to train derailment. In Phase I, we will make a prototype sensor with low power microprocessor, IR camera, GPS and temperature/humidity sensor. It will be integrated with an existing FRED. Algorithms will be developed to detect track surface cracks through geometric thermal signature. This system also has the self-calibration capability. It does not require external illumination and is suitable for Class 9 train travelling at a speed of 200 mph. In Phase I, we will work with MBTA and install our sensor on FRED of the train for data collection. The collected data will be used for the development of algorithms of track surface crack detection and false alarm mitigation. A data structure will also be formed, which can be used to send event data to the train operators, which including sensor health status. For proof-of-concept, the outcome of Phase I development will be a demo system made of hardware of sensor and software detecting track cracks.

Phase II

Contract Number: 6913G618C100012
Start Date: 00/00/00    Completed: 00/00/00
Phase II year
2018
Phase II Amount
$149,999
In Phase I, we developed a practical sensor platform suitable for mounting on the back of train. A large amount of IR images associated with rail tracks were collected on an MBTA train. Algorithms were developed to identify both right and left tracks from a moving train. To help detect track cracks, we developed new algorithms for IR image enhancement and track crack identification. Algorithms were also developed to detect the rail cracks in real time. In Phase II, we will further develop new software algorithms solving some issues observed in Phase I. A smaller sensor platform will be developed for data collection on MBTA train, which incorporates a higher resolution IR camera and smaller gyro stabilizer. Using this new sensor platform, we will collect more data of both regular rail tracks and track cracks. We will then develop software algorithms for image quality improvement under various operating conditions, thermal signature variations, and discrimination between true track cracks and background clutters. In Phase II, we will work with engineers in both Vehicle Department and Track Department of MBTA. To support our Phase II effort, MBTA has provided an endorsement letter. Feedback from MBTA will be incorporated into the final system.