Prognostic Monitoring and Condition Reporting for Remote Multi-Mission Vehicle (RMMV) Subsystems
Navy SBIR 2015.1 - Topic N151-056
NAVSEA - Mr. Dean Putnam - [email protected]
Opens: January 15, 2015 - Closes: February 25, 2015 6:00am ET
N151-056 TITLE: Prognostic Monitoring and Condition Reporting for Remote Multi-Mission Vehicle (RMMV) Subsystems
TECHNOLOGY AREAS: Sensors, Electronics, Battlespace
ACQUISITION PROGRAM: PMS 403, Remote Minehunting System (RMS) Program Office
The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items. Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 5.4.c.(8) of the solicitation. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
OBJECTIVE: Develop a system for the Remote Multi-Mission Vehicle (RMMV) to monitor and record diagnostic data on the health of vehicle subsystem components for real-time mission decisions and post-mission analysis and targeted maintenance.
DESCRIPTION: The Navy needs a system consisting of sensors that monitors and records the health of RMMV subsystem components for post-mission analysis and that, additionally, analyzes the state of key components and reports critical information back to the operator in real-time to support decisions on mission continuation. Such a system will reduce the labor required in support of the RMMV by reducing unnecessary preventive maintenance and by identifying corrective maintenance in a timely manner, thereby increasing availability.
Unmanned sea vehicles operate in a constantly changing and corrosive environment which can contribute to accelerated failures of key components. Maintenance, preparation, launch and recovery of such vehicles is time-consuming and costly. Because these vehicles are unmanned, maintenance or faults typically cannot be fixed until they are recovered. Therefore, it is desirable to maximize the reliability and availability of these assets when they are on a mission. The ability to predict the remaining useful life of critical system components will allow targeted maintenance to be scheduled and performed, thus increasing vehicle availability and decreasing operating costs. In some instances, mission success may require these systems to continue executing with degraded performance due to a known fault. Developing methodologies for managing these failures and making educated decisions to optimize performance would increase the probability of continued operation. Additionally, maintenance would be planned and any required parts can be procured prior to vehicle recovery, reducing the mean time to repair.
The RMMV, an unmanned, remotely operated, diesel-powered semi-submersible vehicle, is deployed from Littoral Combat Ships to perform minehunting missions. The RMMV is capable of real-time communication back to its host platform (ref 1), and, conversely, an operator on the host platform can communicate commands back to the RMMV. Vehicle subsystems include self-contained control, propulsion, power, and navigation features (ref 1). The Navy has procured ten RMMVs of the current design, and there are plans to competitively award and fund the development and procurement of a next generation RMMV.
In general, the state-of-the-art of component condition health monitoring sensors and routine data recording is fairly mature (ref 2, 3); however, the process of automated gathering, analysis, and reporting of event data provides significant opportunity for innovation (ref 2). Condition Based Maintenance (CBM) approaches have been used for industrial machine applications (ref 2) and in the aerospace industry (ref 4), but are seldom used for unmanned maritime vehicles.
This topic has two requirements. In both cases, the effort will require working closely with the contractor that builds and provides the RMMV to the Navy to develop a plan for prognostic monitoring and condition reporting. Both also require that the data gathering and reporting technology integrate as much as possible with the RMMV software and communication capabilities. The government encourages offerors to make as much use as possible of previously developed technology, including sensors. Key innovations are likely to occur in the data analysis and operator alert functions. The government also encourages designs that minimize demands on size, weight, and power (SWaP) requirements. Instead of just sensing failures, prognostics allow the prediction of failures based on actual performance data collected and allow the Navy to take action before the failure and potential loss of an RMMV.
First, the transition target of the prognostic monitoring and condition reporting technology will be the next generation RMMV. The most cost-effective and efficient design and implementation of such a system should occur during the design and development of the vehicle itself, rather than as a retrofit, once the vehicle is developed. A subtask of the work will include a review of existing O-level maintenance for the current set of RMMVs and identification of maintenance actions that apply to a specific subsystem monitoring metric for recording prognosis data.
As RMMVs return to depots for refurbishment and restoration, the technology can be introduced to increase performance or reliability. A demonstration of the technology would not be for all vehicle subsystems, due to the challenges and costs of retrofitting. A portion of the monitoring system would be demonstrated, based on the most cost-effective choice. For example, the demonstration could apply to the control surface hydraulic actuators. The current RMMV has a position sensor located at the control surface actuator. This data along with commanded position are recorded to a log and can be accessed. The demonstration would be two-fold. The first would be to record the data for post-mission analysis. The second would be real-time analysis of the data and providing an alert to the operator on discrepancies between actual and commanded control surface position (e.g., position errors and response time). A yellow alert would signal degradation of performance to support an operators� decision to adjust commands to the vehicle with a view toward completing the mission at less than optimal performance. A red alert would support an operator�s decision on whether or not to abort the mission. Inquiries have not turned up any commercially available sensors that diagnose and predict actuator health, so offerors may also assess the feasibility of developing such a sensor to provide additional data. For the current RMMV, data is available for items such as vehicle hydraulic pressure and vehicle spatial awareness (speed, depth, etc.). The demonstration for the current RMMV would not necessarily incorporate this data.
PHASE I: The company will define and develop a concept for prognostic monitoring and condition reporting for RMMV subsystems that meets the objectives as stated in the topic description. The company will show the feasibility of the concept in meeting Navy needs and will establish that the concept can be developed into a useful product for the Navy both for the current RMMV and for the planned upgrade. The company will review current O-level maintenance activities and determine the types that can be addressed via prognostic monitoring and condition monitoring and will provide supporting evidence to substantiate. The company will develop a plan for prognostic monitoring and condition reporting in conjunction with the next generation RMMV Low Rate Initial Production (LRIP) prime contractor. Material testing and analytical modeling, in a laboratory and/or on an actual unmanned vehicle, will establish feasibility.
PHASE II: Based on the results of Phase I, the company will develop a limited prototype for evaluation on the current RMMV, and develop and validate a full system design for the next increment of RMMVs. The demonstration of the limited prototype will be planned for the current RMMV control surface hydraulic actuators through a stand-alone implementation. The prototype will be evaluated to determine its capability in meeting the performance goals and Navy requirements for the prognostic monitoring and condition reporting system. Performance will be demonstrated through prototype evaluation and modeling or analytical methods. The validation of the full system design for the next increment of RMMV will be achieved through modeling and analytic methods, incorporating, where possible, the results of testing on equivalent subsystem components. In both cases, the company will use the results to refine the prototype into al design that will meet Navy requirements. The company will prepare a Phase III development plan to transition the technology to Navy use.
PHASE III: The company will support the Navy in transitioning the technologies into the applicable RMMVs. The company will support the Navy for test and validation to certify and qualify the system for Navy use. The company must work closely with the company that supplies RMMVs to the Navy.
PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: The potential for commercial application and dual use are extensive. The use of unmanned maritime vehicles is expected to increase in industrial applications, such as oil exploration, oceanographic research, and rescue and recovery operations after disasters such as airplane crashes and other missions that would be hazardous for humans (e.g., nuclear disasters). The objectives that drive the development of the technology for military use are essentially the same for these other application areas.
2. Jardine, A.K.S.; Lin, Banjevic (2006). "A review on machinery diagnostics and prognostics implementing condition-based maintenance". Mechanical Systems and Signal Processing 20 (7): 1483�1510.
3. Ying Peng, Ming Dong, Ming Jian Zuo."Current Status of Machine Prognostics in Condition-Based Maintenance: A Review," The International Journal of Advanced Manufacturing Technology. September, 2010. Volume 50, Issue 1-4, pp 297-313.
4. Millar, Richard C. "Integrated Instrumentation and Sensor Systems Enabling Condition-Based Maintenance of Aerospace Equipment," International Journal of Aerospace Engineering. Volume 2012, Article ID 804747. Downloaded on April 26, 2014. Retrieved from: http://www.hindawi.com/journals/ijae/2012/804747/
KEYWORDS: Unmanned maritime vehicles; system prognostic health monitoring; actuators; condition-based maintenance; system failure management; unmanned vehicle operator decision support
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