John L. Schmalzel

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.

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.

The competitive assessment laboratory: introducing engineering design via consumer product benchmarking

In todays quickly changing and increasingly competitive market place, it is imperative that manufacturers keep abreast of the technological advances and design innovations incorporated into competing product lines. The term competitive assessment (or benchmarking) has been coined by manufacturers to describe the process of ethically acquiring, inspecting, analyzing, instrumenting, and testing the product lines of other manufacturers. The Competitive Assessment Laboratory at Rowan University is funded by the National Science Foundation (NSF). In the laboratory, multidisciplinary teams of freshman engineering students from each of the four engineering departments perform each of the above tasks on a consumer product. The laboratory contains a series of consumer appliance test stations featuring PC-based data acquisition systems capable of measuring thermocouple and voltage/current signals. Each station is also equipped with mechanical measurement equipment and portable materials testing equipment. In addition to introducing students to the science and art of design, the Competitive Assessment Laboratory enables the faculty to assess the constantly evolving initial conditions under which the typical engineering student enters his or her course of study.

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.

Sensors: the first stage in the measurement chain

In the first (Fowler and Schmalzel,vol.7,no.1,pp.38-46,Mar. 2004), the context for the tutorial articles was set up by addressing the question of why we measure. Hence many of the common sensor strategies that constitute the first stage in the measurement chain are introduced. While every element of that chain is important, the choice of an appropriate, robust sensor is one of the critical decisions that must be made. This article, the second within the tutorial series, will continue to use examples from test stands for testing rocket engines. Measurements of the weight of liquids, their temperatures, and their flow rates in these rocket engine test stands require sensors and the understanding of how to use them.

Creating an Agile ECE Learning Environment Through Engineering Clinics

To keep up with rapidly advancing technology, numerous innovations to the electrical and computer engineering (ECE) curriculum, learning methods and pedagogy have been envisioned, tested, and implemented. It is safe to say that no single approach will work for all of the diverse ECE technologies and every type of learner. However, a few key innovations appear useful in keeping undergraduate students motivated to learn, resilient to technology evolution, and oriented amid the overload of new information and ECE applications. Engineering clinics, similar to their medical clinic counterparts, provide project-based experiences within the core of an ECE education that enable transformation of the entire curriculum toward an outcomes-oriented, student-centered, total-quality environment. Clinics and project-based learning approaches build skills that give the students confidence and motivation to continuously self-learn and adapt as the technologies around them give way to new, more effective paradigms. Perhaps more importantly, engineering clinic experiences provide numerous opportunities for students to experience the holism of true engineering problem-solving approaches and the ranges of potential technology solutions. This paper reviews the clinic innovations that will enable ECE education to become more effective in the midst of the present plethora of information and technology. Assessment results are provided and are very encouraging. This paper concludes that agile learning environments, created to graduate engineers who can be rapidly productive in the professional and research worlds, are enhanced by clinic and/or project-based learning experiences in the ECE curriculum.

Why do we care about measurement

The IEEE Instrumentation and Measurement (I&M) Society surveyed its membership during the summer of 2003 to clarify IEEE Instrumentation and Measurement Magazines role and purpose. One prominent result was the need for tutorials on I&M. The response to our survey heavily favoured a regular feature in the magazine. Each article focuses on a different concern. Its purpose is to help folks at all levels. Some might be just getting into the discipline and wanting to learn the basics of I&M, general definitions, and common concerns. Moreover, these general areas of knowledge need to be made useful by tying together various I&M elements. Others already working in the field may want introductions to, and possibly more depth in, new and emerging areas. All of the articles are written at a level of a basic undergraduate textbook. To make them as useful as possible, we need your input. That is, we need to know how well the articles meet your needs. These tutorials aim to overcome this myopic view of development and to provide you with a bigger picture - or the systems perspective. Our hope is that understanding the system will thereby help you build more useful instruments. This first tutorial is introductory and provides a basic systems overview.

Integrated System Health Management (ISHM) for Test Stand and J-2X Engine: Core Implementation

ISHM capability enables a system to detect anomalies, determine causes and effects, and predict future anomalies. It provides advice to improve operations based on health status, and includes user interfaces for integrated awareness of the health of the system. NASA Stennis Space Center (SSC), NASA Ames Research Center (ARC), and Pratt & Whitney Rocketdyne (PWR) are currently implementing a core ISHM capability that encompasses the A1 Test Stand and the J-2X Engine. The implementation incorporates all aspects of ISHM; from anomaly detection (e.g. leaks) to root-cause-analysis based on failure modes and effects analysis (FMEA), to a user interface for an integrated visualization of the health of the system (Test Stand and Engine). The implementation provides a low functional capability level (FCL) in that it is populated with few algorithms and approaches for anomaly detection, and root-cause trees from a limited FMEA effort. However, it is a demonstration of a credible ISHM capability, and it is inherently designed for continuous and systematic augmentation of the capability. The paper describes all aspects of the current implementation, and on-going activity leading to a pilot capability that could potentially support the J-2X test program.

A future vision of data acquisition: distributed sensing, processing, and health monitoring

This paper presents a vision for a highly enhanced data acquisition and health monitoring system at NASA SSC rocket engine test facility. This vision includes the use of advanced processing capabilities, in conjunction with highly autonomous distributed sensing and intelligence, to monitor and evaluate the health of data in the context of its associated process. This method is expected to significantly reduce data acquisition costs and improve system reliability and accountability. A universal signal conditioning amplifier (USCA) based system is being evaluated for adaptation to the SSC testing infrastructure. The USCA architecture offers many advantages including flexible and auto-configuring data acquisition with improved calibration and verifiability. Possible enhancements at SSC may include multiplexing the distributed USCAs to reduce per channel costs, and the use of IEEE-485 to Allen-Bradley ControlNet gateways for interfacing with the resident control system.