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Figueroa, Fernando

Publications and source records attributed to Figueroa, Fernando.

At least 55 records · Page 3

Smart Sensor Node Development, Testing and Implementation for Rocket Propulsion Systems

Successful design and implementation of an Integrated System Health Management (ISHM) approach for rocket propulsion systems requires the capability improve the reliability of complex systems by detecting and diagnosing problems. One of the critical elements in the ISHM is an intelligent sensor node for data acquisition that meets specific requirements for rocket motor testing including accuracy, sample rate and size/weight. Traditional data acquisition systems are calibrated in a controlled environment and guaranteed to perform bounded by their tested conditions. In a real world ISHM system, the data acquisition and signal conditioning needs to function in an uncontrolled environment. Development and testing of this sensor node focuses on a design with the ability to self check in order to extend calibration times, report internal faults and drifts and notify the overall system when the data acquisition is not performing as it should. All of this will be designed within a system that is flexible, requiring little re-design to be deployed on a wide variety of systems. Progress in this design and initial testing of prototype units will be reported.

Mengers, Timothy R.↗

Fiber-Optic Strain Gauge With High Resolution And Update Rate

An improved fiber-optic strain gauge is capable of measuring strains in the approximate range of 0 to 50 microstrains with a resolution of 0.1 microstrain. (To some extent, the resolution of the strain gauge can be tailored and may be extensible to 0.01 microstrain.) The total cost of the hardware components of this strain gauge is less than $100 at 2006 prices. In comparison with prior strain gauges capable of measurement of such low strains, this strain gauge is more accurate, more economical, and more robust, and it operates at a higher update rate. Strain gauges like this one are useful mainly for measuring small strains (including those associated with vibrations) in such structures as rocket test stands, buildings, oilrigs, bridges, and dams. The technology was inspired by the need to measure very small strains on structures supporting liquid oxygen tanks, as a way to measure accurately mass of liquid oxygen during rocket engine testing. This improved fiber-optic strain gauge was developed to overcome some of the deficiencies of both traditional foil strain gauges and prior fiber-optic strain gauges. Traditional foil strain gages do not have adequate signal-to-noise ratios at such small strains. Fiber-optic strain gauges have been shown to be potentially useful for measuring such small strains, but heretofore, the use of fiberoptic strain gauges has been inhibited, variously, by complexity, cost, or low update rate.

Figueroa, Fernando↗

Integrated System Health Management (ISHM): Systematic Capability Implementation

This paper provides a credible approach for implementation of ISHM capability in any system. The requirements and processes to implement ISHM capability are unique in that a credible capability is initially implemented at a low level, and it evolves to achieve higher levels by incremental augmentation. In contrast, typical capabilities, such as thrust of an engine, are implemented once at full Functional Capability Level (FCL), which is not designed to change during the life of the product. The approach will describe core ingredients (e.g. technologies, architectures, etc.) and when and how ISHM capabilities may be implemented. A specific architecture/taxonomy/ontology will be described, as well as a prototype software environment that supports development of ISHM capability. This paper will address implementation of system-wide ISHM as a core capability, and ISHM for specific subsystems as expansions and evolution, but always focusing on achieving an integrated capability.

Figueroa, Fernando↗

ISHM Implementation for Constellation Systems

Integrated System Health Management (ISHM) is a capability that focuses on determining the condition (health) of every element in a complex System (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) "not just data" to control systems for safe and effective operation. This capability is currently done by large teams of people, primarily from ground, but needs to be embedded on-board systems to a higher degree to enable NASA's new Exploration Mission (long term travel and stay in space), while increasing safety and decreasing life cycle costs of systems (vehicles; platforms; bases or outposts; and ground test, launch, and processing operations). This viewgraph presentation reviews the use of ISHM for the Constellation system.

Figueroa, Fernando↗

NASA Stennis Space Center Integrated System Health Management Test Bed and Development Capabilities

Integrated System Health Management (ISHM) is a capability that focuses on determining the condition (health) of every element in a complex System (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK)-not just data-to control systems for safe and effective operation. This capability is currently done by large teams of people, primarily from ground, but needs to be embedded on-board systems to a higher degree to enable NASA's new Exploration Mission (long term travel and stay in space), while increasing safety and decreasing life cycle costs of spacecraft (vehicles; platforms; bases or outposts; and ground test, launch, and processing operations). The topics related to this capability include: 1) ISHM Related News Articles; 2) ISHM Vision For Exploration; 3) Layers Representing How ISHM is Currently Performed; 4) ISHM Testbeds & Prototypes at NASA SSC; 5) ISHM Functional Capability Level (FCL); 6) ISHM Functional Capability Level (FCL) and Technology Readiness Level (TRL); 7) Core Elements: Capabilities Needed; 8) Core Elements; 9) Open Systems Architecture for Condition-Based Maintenance (OSA-CBM); 10) Core Elements: Architecture, taxonomy, and ontology (ATO) for DIaK management; 11) Core Elements: ATO for DIaK Management; 12) ISHM Architecture Physical Implementation; 13) Core Elements: Standards; 14) Systematic Implementation; 15) Sketch of Work Phasing; 16) Interrelationship Between Traditional Avionics Systems, Time Critical ISHM and Advanced ISHM; 17) Testbeds and On-Board ISHM; 18) Testbed Requirements: RETS AND ISS; 19) Sustainable Development and Validation Process; 20) Development of on-board ISHM; 21) Taxonomy/Ontology of Object Oriented Implementation; 22) ISHM Capability on the E1 Test Stand Hydraulic System; 23) Define Relationships to Embed Intelligence; 24) Intelligent Elements Physical and Virtual; 25) ISHM Testbeds and Prototypes at SSC Current Implementations; 26) Trailer-Mounted RETS; 27) Modeling and Simulation; 28) Summary ISHM Testbed Environments; 29) Data Mining - ARC; 30) Transitioning ISHM to Support NASA Missions; 31) Feature Detection Routines; 32) Sample Features Detected in SSC Test Stand Data; and 33) Health Assessment Database (DIaK Repository).

Figueroa, Fernando↗

GUI for Computational Simulation of a Propellant Mixer

Control Panel is a computer program that generates a graphical user interface (GUI) for computational simulation of a rocket-test-stand propellant mixer in which gaseous hydrogen (GH2) is injected into flowing liquid hydrogen (LH2) to obtain a combined flow having desired thermodynamic properties. The GUI is used in conjunction with software that models the mixer as a system having three inputs (the positions of the GH2 and LH2 inlet valves and an outlet valve) and three outputs (the pressure inside the mixer and the outlet flow temperature and flow rate). The user can specify valve characteristics and thermodynamic properties of the input fluids via userfriendly dialog boxes. The user can enter temporally varying input values or temporally varying desired output values. The GUI provides (1) a set-point calculator function for determining fixed valve positions that yield desired output values and (2) simulation functions that predict the response of the mixer to variations in the properties of the LH2 and GH2 and manual- or feedback-control variations in valve positions. The GUI enables scheduling of a sequence of operations that includes switching from manual to feedback control when a certain event occurs.

Figueroa, Fernando↗

Rocket Testing and Integrated System Health Management

Integrated System Health Management (ISHM) describes a set of system capabilities that in aggregate perform: determination of condition for each system element, detection of anomalies, diagnosis of causes for anomalies, and prognostics for future anomalies and system behavior. The ISHM should also provide operators with situational awareness of the system by integrating contextual and timely data, information, and knowledge (DIaK) as needed. ISHM capabilities can be implemented using a variety of technologies and tools. This chapter provides an overview of ISHM contributing technologies and describes in further detail a novel implementation architecture along with associated taxonomy, ontology, and standards. The operational ISHM testbed is based on a subsystem of a rocket engine test stand. Such test stands contain many elements that are common to manufacturing systems, and thereby serve to illustrate the potential benefits and methodologies of the ISHM approach for intelligent manufacturing.

Figueroa, Fernando↗

Physical Intelligent Sensors

This paper proposes the development of intelligent sensors as part of an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA s Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Integrated Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS). The PIS discussed here consists of a thermocouple used to read temperature in an analog form which is then converted into digital values. A microprocessor collects the sensor readings and runs numerous embedded event detection routines on the collected data and if any event is detected, it is reported, stored and sent to a remote system through an Ethernet connection. Hence the output of the PIS is data coupled with confidence factor in the reliability of the data which leads to information on the health of the sensor at all times. All protocols are consistent with IEEE 1451.X standards. This work lays the foundation for the next generation of smart devices that have embedded intelligence for distributed decision making capabilities.

Bandhil, Pavan↗

Intelligent Sensors: Strategies for an Integrated Systems Approach

This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines progress made in the development of intelligent sensors by describing the work done till date on Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Chitikeshi, Sanjeevi↗

Intelligent Sensors: An Integrated Systems Approach

The need for intelligent sensors as a critical component for Integrated System Health Management (ISHM) is fairly well recognized by now. Even the definition of what constitutes an intelligent sensor (or smart sensor) is well documented and stems from an intuitive desire to get the best quality measurement data that forms the basis of any complex health monitoring and/or management system. If the sensors, i.e. the elements closest to the measurand, are unreliable then the whole system works with a tremendous handicap. Hence, there has always been a desire to distribute intelligence down to the sensor level, and give it the ability to assess its own health thereby improving the confidence in the quality of the data at all times. This paper proposes the development of intelligent sensors as an integrated systems approach, i.e. one treats the sensors as a complete system with its own sensing hardware (the traditional sensor), A/D converters, processing and storage capabilities, software drivers, self-assessment algorithms, communication protocols and evolutionary methodologies that allow them to get better with time. Under a project being undertaken at the NASA Stennis Space Center, an integrated framework is being developed for the intelligent monitoring of smart elements. These smart elements can be sensors, actuators or other devices. The immediate application is the monitoring of the rocket test stands, but the technology should be generally applicable to the Intelligent Systems Health Monitoring (ISHM) vision. This paper outlines some fundamental issues in the development of intelligent sensors under the following two categories: Physical Intelligent Sensors (PIS) and Virtual Intelligent Sensors (VIS).

Mahajan, Ajay↗

NSF/ESF Workshop on Smart Structures and Advanced Sensors, Santorini Island, Greece, June 26-28, 2005: Structural Actuation and Adaptation Working Group

This document is a result of discussions that took place during the workshop. It describes current state of research and development (R&D) in the areas of structural actuation and adaptation in the context of smart structures and advanced sensors (SS&AS), and provides an outlook to guide future R&D efforts to develop technologies needed to build SS&AS. The discussions took place among the members of the Structural Actuation and Adaptation Working Group, as well as in general sessions including all four working groups. Participants included members of academia, industry, and government from the US and Europe, and representatives from China, Japan, and Korea.

Figueroa, Fernando↗

V&V of ISHM software for space exploration

NASA has established a far-reaching and long-term program for robotic and manned exploration of the solar system, beginning with missions to the moon and Mars. Integrated System Health Management (ISHM) will be key to improving the reliability, operability and maintainability of many of the systems deployed in this endeavor.

Figueroa, Fernando↗

Qualitative Features Extraction from Sensor Data using Short-time Fourier Transform

The information gathered from sensors is used to determine the health of a sensor. Once a normal mode of operation is established any deviation from the normal behavior indicates a change. This change may be due to a malfunction of the sensor(s) or the system (or process). The step-up and step-down features, as well as sensor disturbances are assumed to be exponential. An RC network is used to model the main process, which is defined by a step-up (charging), drift, and step-down (discharging). The sensor disturbances and spike are added while the system is in drift. The system runs for a period of at least three time-constants of the main process every time a process feature occurs (e.g. step change). The Short-Time Fourier Transform of the Signal is taken using the Hamming window. Three window widths are used. The DC value is removed from the windowed data prior to taking the FFT. The resulting three dimensional spectral plots provide good time frequency resolution. The results indicate distinct shapes corresponding to each process.

Amini, Abolfazl M.↗

Sliding Mode Control of a Thermal Mixing Process

In this paper we consider the robust control of a thermal mixer using multivariable Sliding Mode Control (SMC). The mixer consists of a mixing chamber, hot and cold fluid valves, and an exit valve. The commanded positions of the three valves are the available control inputs, while the controlled variables are total mass flow rate, chamber pressure and the density of the mixture inside the chamber. Unsteady thermodynamics and linear valve models are used in deriving a 5th order nonlinear system with three inputs and three outputs, An SMC controller is designed to achieve robust output tracking in the presence of unknown energy losses between the chamber and the environment. The usefulness of the technique is illustrated with a simulation.

Richter, Hanz↗

An Architecture for Intelligent Systems Based on Smart Sensors

Based on requirements for a next-generation rocket test facility, elements of a prototype Intelligent Rocket Test Facility (IRTF) have been implemented. A key component is distributed smart sensor elements integrated using a knowledgeware environment. One of the specific goals is to imbue sensors with the intelligence needed to perform self diagnosis of health and to participate in a hierarchy of health determination at sensor, process, and system levels. The preliminary results provide the basis for future advanced development and validation using rocket test stand facilities at Stennis Space Center (SSC). We have identified issues important to further development of health-enabled networks, which should be of interest to others working with smart sensors and intelligent health management systems.

Schmalzel, John↗

Fiber-Optic Strain-Gage Tank Level Measurement System for Cryogenic Propellants

Measurement of tank level, particularly for cryogenic propellants, has proven to be a difficult problem. Current methods based on differential pressure, capacitance sensors, temperature sensors, etc.; do not provide sufficiently accurate or robust measurements, especially at run time. These methods are designed to measure tank-level, but when the fluids are in supercritical state, the liquid-gas interface disappears. Furthermore, there is a need for a non-intrusive measurement system; that is, the sensors should not require tank modifications and/or disturb the fluids. This paper describes a simple, but effective method to determine propellant mass by measuring very small deformations of the structure supporting the tank. Results of a laboratory study to validate the method, and experimental data from a deployed system are presented. A comparison with an existing differential pressure sensor shows that the strain gage system provides a much better quality signal across all regimes during an engine test. Experimental results also show that the use of fiber optic strain gages (FOSG) over classic foil strain gages extends the operation time (before the system becomes uncalibrated), and increases accuracy. Finally, a procedure is defined whereby measurements from the FOSG mounted on the tank supporting structure are compensated using measurements of a FOSG mounted on a reference plate and temperature measurements of the structure. Results describing the performance of a deployed system that measures tank level during propulsion tests are included.

Figueroa, Fernando↗

Strain Gage Measurement System to Determine Cryogenic Propellant Tank Level

Measurement of tank level, particularly for cryogenic propellants, has proven to be a difficult proposition. Current methods based on differential pressure, capacitance sensors, temperature sensors, etc.; do not provide sufficiently accurate or robust measurements, especially at run time. This paper describes a simple, but effective method to determine propellant volume by measuring very small deformations of the structure supporting the tank. Results of a laboratory study to validate the method, and experimental data from a deployed system are presented. A comparison with an existing differential pressure sensor shows that the strain gage system provides a very good quality signal even during pressurization.

Figueroa, Fernando↗

A Matlab-Based Graphical User Interface for Simulation and Control Design of a Hydrogen Mixer

A Graphical User Interface (GUI) that facilitates prediction and control design tasks for a propellant mixer is described. The Hydrogen mixer is used in rocket test stand operations at the NASA John C. Stennis Space Center. The mixer injects gaseous hydrogen (GH2) into a stream of liquid hydrogen (LH2) to obtain a combined flow with desired thermodynamic properties. The flows of GH2 and LH2 into the mixer are regulated by two control valves, and a third control valve is installed at the exit of the mixer to regulate the combined flow. The three valves may be simultaneously operated in order to achieve any desired combination of total flow, exit temperature and mixer pressure within the range of operation. The mixer, thus, constitutes a three-input, three-output system. A mathematical model of the mixer has been obtained and validated with experimental data. The GUI presented here uses the model to predict mixer response under diverse conditions.

Richter, Hanz↗