CAV2013-Systems and Structures TG Overview.pptx

Systems and Structures Health
Management Technical Group
Dr. Karl Reichard
Dr. Cliff Lissenden
Applied Research Laboratory
Phone: (814) 863-7681
Email: [email protected]
Engineering Science & Mechanics
Phone: (814) 863-5754
Email: [email protected]
Steve Conlon
Jeff Banks
Joe Rose
Scott Pflumm
Marty Trethewey
Mitch Lebold
Jason Hines
Chris Rogan
Systems and Structures Health Management Technical Group
Steve Hambric
Joe Cusumano
Jeff Mayer
Bernie Tittman
1
Mission
Develop new methodologies and technologies to manage the life cycle of
systems and structures. This includes the full range of
•  Material state awareness,
•  Health and usage monitoring,
•  Condition based maintenance,
•  Autonomic and conventional operations and logistics,
•  Prognostics and useful life prediction calculation.
The underlying goal of the group is to maximize safety, minimize life cycle
cost and increase capability. Key areas of investigation include
•  Sensor systems,
•  Signal processing,
•  Pattern recognition,
•  Reasoning techniques,
•  Material and system modeling and simulation, and
•  Modeling of damage progression to failure.
Systems and Structures Health Management Technical Group
2
Technical Group
Presentations
•  Structural Health Monitoring of Joints in Composites, Aaron Lesky,
Kyle Salitrik, Cliff J Lissenden, Josesph L Rose, Farhad Mohammadi
•  SBCT Embedded Data Collection and Analysis System (SEDCAS),
Jeffery Banks, Mark Brought, Eddie Crow
•  Development of an Optical Fiber Pressure Sensor for Nuclear Power
Plant Monitoring Applications, Mark Turner, Karl Reichard
–  Included in Annual Review
•  Vibration-Based Sensor Design To Detect Lubrication Levels
Contained Within Differential Gear Housings, Stephen Wells, Karl
Reichard
–  Student poster, also included in Annual Review
•  Nonlinear Ultrasonics, Cliff Lissenden
–  Included in Annual Review
Systems and Structures Health Management Technical Group
3
SBCT Embedded Data
Collection and Analysis
System (SEDCAS)
Mark Brought
Project Lead
[email protected]
(814) 865-2687
Jeff Banks
Project Lead
[email protected]
(814) 863-3859
Ed Crow
Project Support
[email protected]
(814) 863-9887
SEDCAS Goals & Tasks Goals: •  On-­‐pla4orm monitoring and data collec=on and off-­‐pla4orm analysis to inform maintenance and repair needs •  This is an end to end pilot implementa=on of CBM+ system and its capabili=es •  Supports ILSC goals and objec=ves Denotes SEDCAS Focus Tasks: •  Conduct a degrader analysis •  Build a vehicle fleet data collec=on system •  Test within the 56th SBCT PAARNG •  Provide on-­‐pla4orm and off-­‐pla4orm data analysis techniques •  Show how vehicle data is turned into automated and ac=onable maintenance and logis=cs informa=on. Stryker Degrader Analysis •  The top degrader components and subsystems for the Stryker pla4orm were selected based on analysis of three data sources including: –  Results of the maintainer interviews –  Analysis of the parts replacement data from the DMIS database and the AMSAA sample data collec=on effort –  OEM ques=onnaire. •  The primary emphasis of the analysis was to correlate the three data sources. The star=ng point was the maintainer interview informa=on, which was compared to the part replacement data to corroborate the interview results. SEDCAS: Opera=onal View Stryker and HEMTT Pla6orms + Unit LocaCon Usage Data, Fault Codes, and Parametric Data from each Vehicle + GOTS Technologies MSD v3 with FIPS 140-­‐2 on each vehicle Vehicle Data Received by CAISI Access Point/Bridge On-­‐Pla6orm Sensors and Data GOTS Technologies Data Repository InformaCon Warehouse ABCD Data Server FIPS 140-­‐2 wireless from each vehicles to access bridge. + Exis=ng OEM Data: •  Usage Data •  Fault Codes •  Sensor Data Automated Wireless Data Transmission from PAANG to the Data Warehouse Three Data Transmission Methods to the Data Warehouse: 1.  GOTS: CAISI 2.  COTS: Cellular Network 3.  GOTS: VSAT (Poten=al Connec=on) SBCT Unit Management Portal User Interfaces + + Fuel Sensor (CAN) Electrical Power ‘Smart’ Sensor (CAN) Data warehouse server will host interface and data with web access Digital Sensors and Adaptors Electrical Power Monitoring Sensor • 
Measures and reports electric current, voltage and temperature for the alternator and bacery strings (24 volt) on vehicles. • 
Integrated fault predic=ve algorithms enable health monitoring for alternator and baceries. • 
Outputs message on SAE J1939 bus (PGN65300 – PGN65317) with a one second update rate. Universal Fuel to CAN Adaptor • 
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The fuel gauge intermicently sources current, once every 12 seconds. The sensor sinks current propor=onal to the fuel level on the sensing element. The UFC adaptor design accommodates other fuel sender / gauge styles widely used across other military pla4orms such as current loop, Pulse Width Modulated signal (PWM) and poten=al (voltage) type. The adaptor outputs message on SAE J1939, (PGN65276 and SPN 96) at a one second update rate with field upgradeable firmware. Differen=al Oil Level Sensor •  We gathered vibra=on and vehicle speed data from both a Stryker differen=al and a HEMTT differen=al. •  Conducted data analysis to evaluate the correla=on between the vibra=on measured by the transducer and the differen=al lubrica=on level. •  Based on the analysis, we were able to create an algorithm that uses vibra=on data from the differen=al to determine the lubrica=on level Vehicle Iden=fica=on and Tracking •  In order to minimize data input errors on forms: –  At-­‐Pla4orm Diagnos=c Systems (IETM, etc.) and Off-­‐Pla4orm Enterprise Systems (GCSS-­‐Army, etc..) • 
Development and integra=on of an Electronic Data Plate –  Technology for extrac=ng required form fields via devices on the vehicle data bus. –  Easily programed by the MSD to store and when needed broadcast these parameters. MSD v3 Integra=on The MSD v3 laptop computer was configured as a digital source collec=on device with the implementa=on of the Noregon DLA+ bus adaptor and the Noregon JPRO Military solware that enables the ability to collect data from the J1939 and J1708 data buses. The MSD v3 provides the 802.11 wireless and the Windows 7 opera=ng system provides the FIPS 140-­‐2 wireless communica=ons. Added this J1939 bus to each Stryker vehicle to support the digital sensors. Automated Informa=on Warehouse Global Fleet Readiness View Vehicle Loca=ons and High Level Readiness View Vehicle Health and Fuel Informa=on Individual Vehicle Fuel Level History Individual Vehicle Distance Traveled History Data Individual Vehicle Engine Coolant Temperature History Prototype Interface •  This is a prototype interface that we have developed for fault detec=on and isola=on to enable the correct maintenance ac=vity for the correct component. Summary Conclusions and Recommenda=ons: Component: Diesel Engine
Dominant Failure Mode: Low Engine Oil Level •  A general low engine oil condi=on is detectable with the exis=ng embedded diagnos=cs using the oil temperature switch and oil pressure switch and their accompanying fault codes. •  A more direct diagnos=c capability as well as a predic=ve capability would require the addi=on of an oil level sensor. Components: Differen=als and the Transfer Case Dominant Failure Mode: Low Lubrica=on Oil Level •  A low lubrica=on oil condi=on for the differen=als and the transfer case is not detectable with the exis=ng embedded diagnos=cs and there are no exis=ng sensors installed on the vehicle for monitoring the health of the differen=als or transfer case. •  A diagnos=c capability as well as a predic=ve capability would require the addi=on of a single vibraCon sensor (accelerometer) applied to each differen=al and transfer case. Components: Alternator, Baceries and Voltage Regulator Dominant Failure Mode: Charging Issues •  This failure mode cannot be completely detected by the exis=ng vehicle embedded capability. •  The alternator and voltage regulator would require the addi=on of a current sensor with a current and voltage trending algorithm for a diagnos=c capability and a predic=ve capability for the alternator could be implemented with current signature analysis techniques. •  For the baceries, it is recommended that the exis=ng U.S. Army at-­‐pla6orm ba\ery diagnosCc tools be fully u=lized by the maintainers before an embedded solu=on is implemented on the pla4orms. Summary Conclusions and Recommenda=ons: Components: Height Control Manifold in the HMS Dominant Failure Mode: Nitrogen Gas Leaks. •  The exis=ng embedded diagnos=cs has a par=al capability to detect this failure mode. •  In order to provide a comprehensive leak detec=on capability as well as a predic=ve indica=on it is recommended that a pressure sensor be installed on both the low and high pressure sides of the system in addi=on to or as a replacement for the exis=ng pressure switches. Components: Hydraulic System Dominant Failure Mode: Loss of Hydraulic Fluid. •  The loss of fluid is a direct consequence of hydraulic fluid leaks that can be generally detected with the exis=ng reservoir level switch but the specific source of the leaking fluid failure mode cannot be determined (i.e. isolated) with the exis=ng vehicle sensors. •  The implementa=on of an embedded fault isola=on or predic=ve capability for hydraulic fluid leaks is not recommended for this applica=on due to low effec=veness of the current technology.