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This paper presents the method of variable-feedrate intelligent segmentation as an enhanced approach to feedrate optimization in micromilling that overcomes detrimental scale effects in the process and leads to improved stability and decreased machining time. Due to the high tool-size to feature-size ratio present in micromilling, the maximum allowable feedrate is limited by the sampling rate of the real-time trajectory generation and motion control system. The variable-feedrate intelligent segmentation method is proposed to compensate for the feedrate limitation by intelligent selection of the interpolation technique applied to segments along the tool path in order to reduce the trajectory generation computation time and enable increased sampling frequency. The increased sampling frequency allows higher maximum feedrates providing for increased productivity and improved process stability. The performance of the novel intelligent segmentation approach was benchmarked against recent non-rational B-splines (NURBS) feedrate optimization techniques. Results from the numerical evaluation of the intelligent segmentation technique have demonstrated significant reductions in machining time, with a maximum reduction of over 50% recorded. Furthermore, the results from the study demonstrate the advantages of the intelligent segmentation method in enhancing process stability and maintaining, or marginally decreasing, process error. The variable feedrate intelligent segmentation method developed in this study provides, therefore, an enhanced methodology for path planning in high-speed, high-precision micromilling operations. [DOI: 10.1115/1.2931492] Keywords: micromachining, intelligent segmentation, path planning, feedrate optimization

Most of today's civil engineering students are unaware of the potential use of smart structures technology in the design, construction, and maintenance of civil infrastructure systems. This paper presents recent education development in the area of smart structures technology at Lehigh University. The goal of this education development is to prepare the future engineer of society for this cutting-edge technology, for which they may see broad application in their professional practice. An overview of the smart structures technology in civil engineering applications, from a systems perspective, is first given in the paper. Educational activities incorporating smart structures technology into civil engineering curriculum are next presented in this paper. DOI: 10.1061/(ASCE)1052-3928(2008)134:1(41) CE Database subject headings: Curricula; Engineering education; Intelligent structures; Sensors; Structural control; Structural engineering.

This paper proposes unconstrained functional networks as a new classifier to deal with the pattern recognition problems. Both methodology and learning algorithm for this kind of computational intelligence classifier using the iterative least squares optimization criterion are derived. The performance of this new intelligent systems scheme is demonstrated and examined using real-world applications. A comparative study with the most common classification algorithms in both machine learning and statistics communities is carried out. The study was achieved with only sets of second-order linearly independent polynomial functions to approximate the neuron functions. The results show that this new framework classifier is reliable, flexible, stable, and achieves a high-quality performance. Index Terms--Functional networks, minimum description length, statistical pattern recognition.

The industrial network, often referred to as fieldbus, becomes an indispensable component for intelligent manufacturing systems. Thus, in order to satisfy the real-time requirements of field devices such as sensros, actuators, and controllers, numerous fieldbus protocols have been developed. But, the application of fieldbus has been limited due to the high cost of hardware and the difficulty in interfacing with multivendor products. As an alternative to fieldbus, the Ethernet (IEEE 802.3) technology is being adapted to the industrial environment. However, the crucial technical obstacle of Ethernet is its nondeterministic behavior that cannot satisfy the real-time requirements. Recently, the switched Ethernet becomes a very promising alternative for real-time industrial application due to the elimination of uncertainties in Ethernet. This paper focuses on the application of the switched Ethernet with multiple levels (that is, cascade structure with multiple switching hubs) for real-time industrial networking. More specifically, this paper presents an analytical performance evaluation of the switched Ethernet with multiple levels from timing diagram analysis, and experimental evaluation from an experimental testbed of networked control system. Index Terms--Fieldbus, industrial network, network delay, networked control system (NCS), real-time requirements, switched Ethernet.

This paper reports on the use of multi-agent system technology to automate the management and analysis of SCADA and digital fault recorder (DFR) data. The multi-agent system, entitled Protection Engineering Diagnostic Agents (PEDA), integrates legacy intelligent systems that analyze SCADA and DFR data to provide data management and online diagnostic information to protection engineers. Since November 2004, PEDA agents have been intelligently interpreting and managing data online at a transmission system operator in the U.K. As the results presented in this paper demonstrate, PEDA supports protection engineers by providing access to interpreted power systems data via the corporate intranet within minutes of the data being received. In this paper, the authors discuss their experience of developing a multi-agent system that is robust enough for continual online use within the power industry. The use of existing agent development toolsets and standards is also discussed. Index Terms--Cooperative systems, decision support systems, fault diagnosis, intelligent systems, knowledge-based systems, power transmission protection.

Some major issues of human-friendly man-machine interaction/interfaces in an intelligent residential system are dealt with to cope with increasing needs of the elderly and the handicapped for a higher level of living conditions. Specifically, the existing systems in this area are first examined and the inadequacy of some current remote-control interfaces for the elderly/handicapped is pointed out. Then, some intention-reading techniques are introduced for the elderly and/or the physically handicapped, for easier and more convenient use of machines and engineering systems. Index Terms--Human-friendly interface, intelligent residential system, intention reading.

Byline: M. Fletcher (1), R. W. Brennan (1), D. H. Norrie (1) Keywords: Configuration management; control systems; intelligence; software tools; functional blocks Abstract: A holonic manufacturing system (HMS) represents a new breed of intelligent shop-floor management technology for the production of artifacts that satisfy unique customer requirements. Flexibility is an essential characteristic of the HMS in order to manufacture high-variety low-volume artifacts. Autonomous 'smart' entities called holons interact, via cooperation protocols, within a HMS to support the runtime reconfiguration demanded by such an agile shop-floor. This paper presents a framework to model and reconfigure, in real-time, the holons' abstract behavioral specifications through the application of Internet-based mobile agents. A tool is also described to convert these specifications into a corresponding implementation model (based on the IEC 61499 function block architecture) that holons can execute across an open network of controller devices. Author Affiliation: (1) Manufacturing Engineering Department, University of Calgary, Canada Article History: Registration Date: 05/10/2004

We present a new model for multiple-input-multiple-output (MIMO) outdoor wireless fading channels and their capacity performance. The proposed model is more general and realistic than the usual independent and identically distributed (i.i.d.) model, and allows us to investigate the behavior of channel capacity as a function of the scattering radii at transmitter and receiver, distance between the transmit and receive arrays, and antenna beamwidths and spacing. We show how MIMO capacity is governed by spatial fading correlation and the condition number of the channel matrix through specific sets of propagation parameters. The proposed model explains the existence of "pinhole" channels which exhibit low spatial fading correlation at both ends of the link but still have poor rank properties, and hence, low ergodic capacity. In fact, the model suggests the existence of a more general family of channels spanning continuously from full rank i.i.d. to low-rank pinhole cases. We suggest guidelines for predicting high rank (and hence, high ergodic capacity) in MIMO channels, and show that even at long ranges, high channel rank can easily be sustained under mild scattering conditions. Finally, we validate our results by simulations using ray tracing techniques. Connections with basic antenna theory are made. Index Terms--Antenna arrays, channel capacity, channel modeling, diversity, multiple-input-multiple-output channels, smart antennas, space-time coding, spatial multiplexing.

Different partial discharge (PD) detection and measurement procedures suitable for use on cables, capacitors, transformers and rotating machines are examined and compared. Both narrow and wide bandwidth PD detectors are considered; particular attention is given in regard to their suitability to different types of electrical apparatus and cable specimens under test as well as their applicability to discharge site location and their capability to detect different forms of PD. A rather substantial portion of the discussion is devoted to the use of intelligent machines as applied to ED pattern recognition in terms of either ED pulse-height/discharge epoch (phase) distributions or discharge pulse shape attributes.

In this letter, we present a study of the signal-to-interference-plus-noise ratio (SINR) and throughput efficiency achievable on the uplink of a multicellular environment in the presence of smart antennas at the base station receivers. Both intracell and intercell interferers are explicitly taken into account, as is the SINR gain yielded by optimal beamforming. Different cases are compared, and in particular the tradeoff involved in choosing the frequency reuse plan is considered. It is seen that the system operates most efficiently with full frequency reuse, even though this requires intercell synchronization. Index Terms--Capture, cellular systems, MAC, optimum beamforming, packet data, smart antennas, wireless.

This paper focuses on automotive applications and discusses the development of a suite of integrated radar and IR sensors that can be used to surround a vehicle (car, truck, boat, etc.). The primary function is to provide information to the vehicle systems and operator as enhancements to passenger and vehicle safety. It may also provide vehicle information (speed, location, destination, etc.) and integrate information (weather, road/traffic conditions, service/rest-area location, route details, etc.) from an intelligent vehicle highway system. Index Terms--Airplane, automotive, boat, car, GPS, highway, intelligent vehicle highway system, IR, radar, sensors, truck, vehicle.

Smart, or intelligent, packaging for food is discussed. This packaging senses and measures variations in the environment or the package and its contents and communicates to an observer. It can relate to counterfeiting, supply chain management and traceability as well as to freshness of food. Time-temperature integrators are discussed. Companies whose products and processes are discussed include Campbell's, Eatzi's, Trader Joe's, Toxin Alert, European grocery chains Monoprix and Alert Hiejn, Campden and Chorleywood Food Research in the UK, Allied Signal, Cox Recorders, Sira Technologies, 3M, and Electronic Article Surveillance. Brands discussed include LifeLine, Monitor Mark, Food Sentinel, Toxin Guard, Vitsab (from Sweden), Fresh-Check, and HEATmarker.

The range of experiments that a typical undergraduate energy conversion laboratory facility can support does not adequately prepare power engineering students for the digital-computer oriented power system industry. Traditional approach to experimentation involves manually reading several meters, logging data, performing necessary calculations and plotting results. In order to correct this problem, an Intelligent Data-Acquisition and Control (IDAC) system is implemented for the energy conversion laboratory at Penn State University-Harrisburg. Using the IDAC system, data gathering and analysis becomes automated. Students are therefore able to devote the bulk of their time to the intellectual aspects of the project.

Most homes have basic forms of automation, such as television remote controls and central heating timers. The Custom Electronic Design and Installation Association (CEDIA), the trade organization for the home automation industry was set up 10 years ago, catering for the high end of the home electronics market. The Joseph Rowntree Housing Trust has introduced home automation to two demonstrator homes, as part of broader research into the way people interact with their living environment. However the widespread introduction of home automation is hampered by cost and people's attitudes to change.

A distributed control system (DCS) for a turbine engine has been demonstrated and tested, consisting of prototype electronic interface units (EIUs) connected to data and power busses. In the DCS, a central control computer communicated with smart sensors and smart actuators via a 2.5 megabit/sec digital data bus, using the Fieldbus protocol. Power was distributed to the smart devices as 100 kHz 100V peak AC, allowing light, simple power converters at each smart device. All smart sensors, smart actuators, and cables were dual redundant. The smart actuators received position demand from the central control computer, exchanged data between channels to provide local redundancy management, closed the position loop locally, and reported actuator position to the central controller. Smart sensors converted sensed signals to digital values in engineering units, and performed local built-in tests. Testing of the DCS was done in a closed-loop simulation with an engine model. Frequency response of the DCS was almost identical with the conventional system.

Advance vehicle systems equipped with automated driver functions such as Adaptive Cruise Control (ACC) and Active Steering (AS) are expected to be introduced by the end of the 20th century. Despite the advantages that vehicle automation technology provide including increased ease in driving and reduction of road accidents, there is growing concern for its reliability. This is especially true with its operational application, as manufacturers have limited themselves to testing automated cars using model drivers.

Support vector machines (SVMs) provide a significant algorithm for machine learning that can lead to high performances in a wide range of practical applications. SVMs are better than other machine learning algorithms because they can be analyzed theoretically using simple ideas from computational learning theory. Examples of real problems that can be addressed by SVMs include text categorization and face detection. The algorithm can be implemented efficiently using sequential minimal optimization.

Robotic control systems incorporated with intelligence, the ability to perceive, reason, learn and enhance and expand knowledge through further processing, are being developed for use in industrial processes. Intelligence equipped robots recognize and classify patterns through approximation. By approximation, the robot will be able to represent and process pre-programmed conditions, acquire new knowledge, refine its knowledge base and make appropriate inferences. The fish-processing system at the Industrial Automation Laboratory is a practical example of such technology.

Side- and shock-loading of cranes can cause boom and turret drive gear failures with fatal results. However, traditional overload systems do not protect against these types of critical loading conditions, and crane capacity charts only consider the normal loading case, vertical lifts. In the maintenance of bridges, crane operators in any state department of transportation are presented with situations in which they have to pull debris and entire trees that are lodged against bridges. Dragging and shock-loading are commonplace. Researchers from the Construction Automation and Robotics Laboratory at North Carolina State University have developed an innovative crane monitoring system capable of warning an operator who enters a danger zone and storing information about critical events on an electronic device. Acting like a black box on an airplane, the storage device allows this information to be downloaded by a supervisor in order to assess how a particular crew 'worked' the crane. This paper presents the results of this project and discusses the basic components of the accident prevention system for cranes.

Intelligent packaging that improves the quality of chilled food reaching the customer after going through the risky distribution system has been developed. Using radiofrequency responders and transmitters for sending time-temperature signals is innovative H-E-B Food and Drug Co., a major retail supermarket chain, and its control of temperature in retail distribution are discussed.