Fernando Figueroa

An architecture for intelligent systems based on smart sensors

Based on requirements for a next-generation rocket test facility, elements of a prototype 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 facilities at Stennis Space Center (SSC) 1. 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.

An ultrasonic ranging system for structural vibration measurements

An ultrasonic ranging system (URS) that can be used to measure vibratory displacements in structures is described. A pair of ultrasonic transducers is used in a transmit-receive mode to acquire the motion of a point on a flexible structure. The structures oscillating motion modulates the phase angle between the transmitted and received acoustic signals. A simple phase detector and low-pass filter combination demodulate the phase signal, thus extracting information about the motion of the point on the structure. The results reported concentrate on some design issues of the URS and its use as a potential displacement measuring device for flexible structures. The URS accurately distinguished four vibration frequencies of a simple cantilevered aluminum beam, with the highest frequency near 50 Hz. >

An automatic self-installation and calibration method for a 3D position sensing system using ultrasonics

Abstract This work addresses 3D position sensing systems that estimate the location of a wave source by triangulating its position based on the time-of-flights (TOFs) to various receivers fixed to an inertial frame of reference. Typical applications of such systems are finding the location of the transmitter that may be fixed to an autonomously guided vehicle (AGV) operating in an enclosed work environment, a robot end-effector, or virtual reality environments. These environments constitute a large working volume, and the receivers have to be fixed in this environment and their locations known exactly. This is a major source of problems in the installation/calibration stage since the receivers are usually distributed in space and finding their exact location entails using a separate 3D calibrating device which may or may not be as accurate as the location system itself. This paper presents a method to use the system itself to set up an inertial frame of reference and find out the locations of the receivers within this frame by simply using an accurate ID positioning system, e.g. an accurate ruler or a simple distance measuring system that uses ultrasonic or infrared sensors. The method entails moving the transmitter to known locations on a single plane, and using the TOFs to estimate the location of the receivers. A typical application would be that an AGV carries a set of receivers to a hazardous environment such as a nuclear power plant, places the receivers arbitrarily, carries out the self-installation/calibration procedure, maps out the environment, and begins to function autonomously, the whole procedure being done without human intervention or supervision.

Intelligent seam tracking using ultrasonic sensors for robotic welding

This paper presents a novel approach for seam tracking using ultrasonics. An ultrasonic seam tracking system has been developed for robotic welding which tracks a seam that curves freely on a two-dimensional surface. The seam is detected by scanning the area ahead of the torch and monitoring the amplitude of the waves received after reflection from the workpiece surface. Scanning is accomplished by using two ultrasonic sensors (a transmitter and a receiver) mounted on a stepper motor such that the transmitter angle is the same as the receiver angle. The motor is mounted on the end-effector just ahead of the welding torch and covers a ninety degree arc in front of the torch. If there is no seam then the receiver receives most of the transmitted waves after reflection, but if there is a seam then most of the transmitted waves are dispersed in directions other than that of the receiver. The system has been tested and is very robust in the harsh environments generated by the arc welding process. The robustness of the system stems from using various schemes such as time windowing, a waveguide, air and metal shields, and an intelligent sensor manager. This ultrasonic system offers some distinct advantages over traditional systems using vision and other sensing techniques. It can be used to weld very shiny surfaces, and is a very economical method in terms of cost as well as computational intensity. The system can be used to detect seams less than 0.5 mm wide and 0.5 mm deep.

A Robust Method to Determine the Coordinates of a Wave Source for 3-D Position Sensing

This work addresses a method for location of a wave source by observing the wave as it reaches various observation points (receivers), or conversely, this is also a method for location of a receiver at an observation point, by probing with waves generated at various sources. The terms observing and probing imply measurement of time-of-flight (TOF) between a source (transmitter) and a receiver. Practical implications of this work include development and improvement of systems that triangulate the position of a point of interest based on TOF measurements to observation points. Typical applications to benefit from this work include 3-D digitization devices based in ultrasonic, laser, or infrared wave energy

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.

Generic model of an autonomous sensor

Abstract This paper presents a novel approach towards the development of a generic model of an autonomous sensor (independent, self-reliant, self-sufficient). A case is made for autonomy as the ability to operate optimally using information available to the sensor without the intervention of other systems. The models taxonomy accommodates behaviors common to most sensors. A taxonomy that includes knowledge and data bases is defined such as to equip the sensor model with decision making and learning capabilities based not only on analytic, or statistical methods, but also based on heuristic knowledge, and on the ability to represent behaviors that are difficult or impossible to represent with analytical or deterministic methods. The objective of the model is to allow the sensor to operate in an “intelligent” manner regardless of the control system in which it may be used. A simulated autonomous thermistor has been instantiated as an example. As defined, autonomous sensors would simplify implementation and operation of complex systems with large numbers of sensors, would improve systems that use multisensor integration and fusion, would maintain sensors at optimum operating conditions, and would aid in automatic task error detection and recovery in complex systems.

Dynamic across time autonomous — Sensing, interpretation, model learning and maintenance theory (DATA -SIMLAMT)

A formal theory for the development of a generic model of an autonomous sensor is proposed and implemented. An autonomous sensor not only interprets the acquired data in accordance with an embedded expert system knowledge base but also uses it to modify and enhance the knowledge base. The main objective of the model is to combine the capabilities of the physical sensor and an expert operator monitoring the sensor in real-time. This gives the sensor the capabilities of not only sensing the measurand, but also interpreting the sensed data at a higher human-like level, maintaining its databases over time to account for bad or incomplete data, and learning about the measurand and sensor behaviors. The sensors data base is defined as the quantitative data it senses as well as the qualitative data it interprets. Its knowledge base is defined as the rules that allow maintenance of the truth and integrity of the system and methodologies for model learning. Relevant aspects of the system are described by properties and their qualitative measure called states. A set of properties and their state values define a concept, and a set of consecutively occurring concepts, over time, describe behaviors that essentially provide a qualitative view of the different possible states of the system. These behaviors and associated concepts, called envisionments, are used to identify the measurand and sensor behaviors in real-time so as to take appropriate countermeasures for those behaviors that cause problems. The identification process is called interpretation and is similar to the pattern recognition problem. Dynamic Across Time Autonomous - Sensing, Interpretation, Model Learning And Maintenance Theory (DATA-SIMLAMT) is a novel theory in the field of robotics and artificial intelligence that attempts to model computer reasoning on human-like reasoning about system behaviors. It finds applications in any field that incorporates the human in the control system. Autonomous sensing is just one application of this theory.

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.

Integrated System Health Management: Pilot Operational Implementation in a Rocket Engine Test Stand

This paper describes a credible implementation of integrated system health management (ISHM) capability, as a pilot operational system. Important core elements that make possible fielding and evolution of ISHM capability have been validated in a rocket engine test stand, encompassing all phases of operation: stand-by, pre-test, test, and post-test. The core elements include an architecture (hardware/software) for ISHM, gateways for streaming real-time data from the data acquisition system into the ISHM system, automated configuration management employing transducer electronic data sheets (TEDS?s) adhering to the IEEE 1451.4 Standard for Smart Sensors and Actuators, broadcasting and capture of sensor measurements and health information adhering to the IEEE 1451.1 Standard for Smart Sensors and Actuators, user interfaces for management of redlines/bluelines, and establishment of a health assessment database system (HADS) and browser for extensive post-test analysis. The ISHM system was installed in the Test Control Room, where test operators were exposed to the capability. All functionalities of the pilot implementation were validated during testing and in post-test data streaming through the ISHM system. The implementation enabled significant improvements in awareness about the status of the test stand, and events and their causes/consequences. The architecture and software elements embody a systems engineering, knowledge-based approach; in conjunction with object-oriented environments. These qualities are permitting systematic augmentation of the capability and scaling to encompass other subsystems.