Industrial Control

The use information received from remote stations to form automated supervisory commands.


Articles & Tech Transfers


An Alternative Evaluation of FMEA: Fuzzy ART Algorithm
Abstract Failure Mode and Effects Analysis (F MEA) is a technique used in the manufacturing industry to improve production quality and productivity. It is a method that evaluates possible failures in the system, design, process or ...

Fault diagnosis of pneumatic systems with artificial neural network algorithms
Abstract Pneumatic systems repeat the identical programmed sequence during their operation. The data was collected when the pneumatic system worked perfectly and had some faults including empty magazine, zero vacuum, inappropriate ...

Manufacturing cell formation with production data using neural networks
Abstract Batch type production strategies need adoption of cellular manufacturing (CM) in order to improve operational effectiveness by reducing manufacturing lead time and costs related to inventory and material handling. CM ...

Coordinated machine learning and decision support for situation awareness
Abstract Domains such as force protection require an effective decision maker to maintain a high level of situation awareness. A system that combines humans with neural networks is a desirable approach. Furthermore, it is ...

Critical Motion Detection of Nearby Moving Vehicles in a Vision-Based Driver-Assistance System
Abstract Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents. In this paper, a computational ...

A NEURAL-NETWORK-BASED CELL-FORMATION ALGORITHM IN CELLULAR MANUFACTURING
Abstract The Adaptive Resonance Theory (ART) neural network is a novel method for the cell formation problem in group technology (GT). The advantages of using an ART network over other conventional methods are its fast computation ...

INTELLIGENT DESIGN RETRIEVAL AND PACKAGING SYSTEM - APPLICATION OF NEURAL NETWORKS IN DESIGN AND MANUFACTURING
Abstract We describe a hybrid intelligent design retrieval and packaging system by utilizing techniques such as fuzzy associative memory, backpropagation neural networks, and adaptive resonance theory. As an illustrative example, a ...

DETECTION OF TOOL FAILURE IN END MILLING WITH WAVELET TRANSFORMATIONS AND NEURAL NETWORKS (WT-NN)
Abstract Detection of tool failure is very important in automated manufacturing. In this study, tool failure detection was conducted in two steps by using Wavelet Transformations and Neural Networks (WT-NN). In the first step, data ...

Adaptive resonance theory based neural network for supervised chemical pattern recognition (FuzzyARTMAP) [2] Classification of post-consumer plastics by remote NIR spectroscopy using an InGaAs diode a
Abstract The supervised working FuzzyARTMAP pattern recognition algorithm has been applied to automated identification of post-consumer plastics by near-infrared spectroscopy (NIRS). Experimentally, a remote operating parallel ...

ART-based multiple neural networks for monitoring offshore platforms
Abstract A novel scheme using artificial neural networks to automate the vibration monitoring method of detecting the occurrence and location of damage in offshore jacket platforms is presented. A multiple neural network system is ...

A deployed engineering design retrieval system using neural networks
Abstract We describe a neural information retrieval system (NIRS), now in production within the Boeing Company, which has been developed for the identification and retrieval of engineering designs. Two-dimensional and ...

Application of artificial neural networks for the development of a signal monitoring system
Abstract A prototype of a Signal Monitoring System (SMS) utilizing artificial neural networks is developed in this work. The prototype system is unique in: 1) its utilization of state-of-the-art technology in pattern recognition such ...

Using neural networks for the diagnosis of localized defects in ball bearings
Abstract Two neural network based approaches, a multilayered feed forward neural network trained with supervised Error Back Propagation technique and an unsupervised Adaptive Resonance Theory-2 (ART2) based neural network were used ...

Enhanced exchange heuristic based resource constrained scheduler using ARTMAP
Abstract The Exchange Heuristic (EH) has demonstrated superior results compared with other RCS methods in solving Resource Constrained Scheduling (RCS) problems. Selecting the most promising target constitutes the success of EH. The ...

Application of wavelets and neural networks to diagnostic system development, 1, feature extraction
Abstract An integrated framework for process monitoring and diagnosis is presented which combines wavelets for feature extraction from dynamic transient signals and an unsupervised neural network for identification of operational ...

Intelligent tool wear identification based on optical scattering image and hybrid artificial intelligence techniques
Abstract Tool wear monitoring is crucial for an automated machining system to maintain consistent quality of machined parts and prevent damage to the parts during the machining operation. A vision-based approach is presented for tool ...

A neural-network approach to recognize defect spatial pattern in semiconductor fabrication
Abstract Yield enhancement in semiconductor fabrication is important. Even though IC yield loss may be attributed to many problems, the existence of defects on the wafer is one of the main causes. When the defects on the wafer form ...

Unsupervised adaptive resonance theory neural networks for control chart pattern recognition
Abstract This paper describes the use of unsupervised adaptive resonance theory ART2 neural networks for recognizing patterns in statistical process control charts. To improve the classification accuracy, three schemes are proposed. ...

Wafer bin map recognition using a neural network approach
Abstract Although the fabrication of modern integrated circuits uses highly automatic and precisely controlled operations, equipment malfunctions or process drifts are still inevitable owing to the high complexity involved in the ...

On-line tool breakage monitoring in turning
Abstract Acoustic emission (AE) and motor power sensors were used to detect the tool breakage in turning. Time-frequency analysis was used to process different AE signals emitted from the cutting process (normal cutting condition, ...

Performance of Fuzzy ART neural network and hierarchical clustering for part-machine grouping based on operation sequences
Abstract The problem context for this study is one of identifying families of parts having a similar sequence of operations. This is a prerequisite for the implementation of cellular manufacturing, group technology, just-in-time ...

Model-based fault detection and isolation method using ART2 neural network
Abstract This article presents a model-based fault diagnosis method to detect and isolate faults in the robot arm control system. The proposed algorithm is composed functionally of three main parts: parameter estimation, fault ...

A syntactic methodology for automatic diagnosis by analysis of continuous time measurements using hierarchical signal representations
Abstract In this paper, we present a methodology for automatic diagnosis of systems characterized by continuous signals. For each condition considered, the methodology requires the development of an alphabet of signal primitives, and ...

Manufacturing quality control by means of a Fuzzy ART network trained on natural process data
Abstract In order to produce products with constant quality, manufacturing systems need to be monitored for any unnatural deviations in the state of the process. Control charts have an important role in solving quality control ...

Integration of ART-Kohonen neural network and case-based reasoning for intelligent fault diagnosis
Abstract This paper presents a new approach for integrating case-based reasoning (CBR) with an ART-Kohonen neural network (ART-KNN) to enhance fault diagnosis. When solving a new problem, the neural network is used to make hypotheses ...

Clustering in wavelet domain: A multiresolution ART network for anomaly detection
Abstract A method for process fault detection is presented, based on the integration of multiscale signal representation and scale-specific clustering-based diagnosis. Previous work has demonstrated the utility of our multiscale ...

Adaptive Resonance Theory-based neural algorithms for manufacturing process quality control
Abstract The demand for quality products in industry is continuously increasing. To produce products with consistent quality, manufacturing systems need to be closely monitored for any unnatural deviation in the state of the process. ...

A new ART-counterpropagation neural network for solving a forecasting problem
Abstract This study presents a novel Adaptive resonance theory-Counterpropagation neural network (ART-CPN) for solving forecasting problems. The network is based on the ART concept and the CPN learning algorithm for constructing the ...

Fuzzy-ART based adaptive digital watermarking scheme
Abstract In this paper, a novel transform domain digital watermarking scheme that uses visually meaningful binary image as watermark has been developed. The method embeds the watermark information adaptively with localized embedding ...

On the design of intelligent robotic agents for assembly
Abstract Robotic agents can greatly be benefited from the integration of perceptual learning in order to monitor and adapt to changing environments. To be effective in complex unstructured environments, robots have to perceive the ...

Fuzzy ART neural network algorithm for classifying the power system faults
Abstract This paper introduces advanced pattern recognition algorithm for classifying the transmission line faults, based on combined use of neural network and fuzzy logic. The approach utilizes self-organized, supervised Adaptive ...

Application of ART neural network to development of technology for functional feature-based reference design retrieval
Abstract Engineering design is a knowledge intensive process. The execution of each task in the process requires various aspects of knowledge and experience. Therefore, organizing, storing and retrieving product design information, ...

Understanding ART-based neural algorithms as statistical tools for manufacturing process quality control
Abstract Neural networks have recently received a great deal of attention in the field of manufacturing process quality control, where statistical techniques have traditionally been used. In this paper, a neural-based procedure for ...

ART artificial neural networks based adaptive phase selector
Abstract This paper introduces a new phase selector based on adaptive resonance theory (ART). Because conventional phase selector cannot adapt dynamically to the power system operating conditions, it presents different characters ...

Manufacturing cell formation using modified ART1 networks
Abstract The primary objective of group technology (GT) is to enhance the productivity in the batch manufacturing environment. The GT cell formation problem is solved using modified binary adaptive resonance theory networks known as ...

Integrated clustering approach to developing technology for functional feature and engineering specification-based reference design retrieval
Abstract Engineering design is a complex activity, and is heavily reliant on the know-how of engineering designers. Hence, capturing, storing, and reusing design information, design intent, and underlining design knowledge to support ...

Transformations in machining. Part 1. enhancement of wavelet transformation neural network (WT-NN) combination with a preprocessor
Abstract Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was ...

ART 2 - an unsupervised neural network for PD pattern recognition and classification
Abstract This paper introduces a method of classifying partial discharges of unknown origin. The innovative trend of using Artificial Neural Network (ANN) towards classification of Partial Discharge (PD) patterns is cogent and ...

A real time fault analysis tool for monitoring operation of transmission line protective relay
Abstract This paper proposes an integrated real time fault analysis tool for transmission line. The two primary techniques used in the fault analysis tool, fuzzy adaptive resonance theory (ART) neural network and synchronized ...

Hybrid data mining approach for pattern extraction from wafer bin map to improve yield in semiconductor manufacturing
Abstract Semiconductor manufacturing involves lengthy and complex processes, and hence is capital intensive. Companies compete with each other by continuously employing new technologies, increasing yield, and reducing costs. Yield ...

Fractional cell formation in group technology using modified ART1 neural networks
Abstract Group technology (GT) is a manufacturing philosophy that attempts to reduce production cost by reducing the material handling and transportation cost. The GT cell formation by any known algorithm/heuristics results in much ...

The application of clustering analysis for the critical areas on TFT-LCD panel
Abstract For thin film transistor-liquid crystal displays (TFT-LCD) factories in Taiwan, yield performance had become as an important competitiveness determinant during the competitive environment. As we known, the market for LCDs ...

ART-KOHONEN neural network for fault diagnosis of rotating machinery
Abstract In this paper, a new neural network (NN) for fault diagnosis of rotating machinery which synthesizes the theory of adaptive resonance theory (ART) and the learning strategy of Kohonen neural network (KNN), is proposed. For ...

Abnormality diagnosis of GIS using adaptive resonance theory
Abstract The paper presents an artificial neural network (ANN) approach using ART2 (Adaptive Resonance Theory 2) to a diagnostic system for gas insulated switchgear (GIS). To begin with, the authors show the background of abnormality ...

Comparison of an adaptive resonance theory based neural network (ART-2a) against other classifiers for rapid sorting of post consumer plastics by remote near-infrared spectroscopic sensing using an In
Abstract An Adaptive Resonance Theory Based Artificial Neural Network (ART-2a) has been compared with Multilayer Feedforward Backpropagation of Error Neural Networks (MLF-BP) and with the SIMCA classifier. All three classifiers were ...

Motorized system integrated control and diagnostics using vibration, pressure, temperature, speed, and/or current analysis
Abstract Systems and methods are disclosed for controlling, diagnosing and prognosing the health of a motorized system. The systems may comprise a diagnostics system, a prognostic system and a controller, wherein the diagnostics ...

Process and apparatus for monitoring a vehicle interior
Abstract A monitoring of a vehicle interior is effected by detecting sound waves in a vehicle interior, either from an incursion source or as reflected as echo waves and decomposing the electrical signals representing those detected ...

Method and system for diagnostics and prognostics of a mechanical system
Abstract A vibrational analysis system diagnosis the health of a mechanical system by reference to vibration signature data from multiple domains. Features are extracted from signature data by reference to pointer locations. The ...

Distributed energy neural network integration system
Abstract A system that couples distributed power generators together as a collective unit for the purposes of selling or purchasing energy from the electrical power grid. The apparatus includes a charge/discharge controller and an ...

Detection of pump cavitation/blockage and seal failure via current signature analysis
Abstract A system and method is provided for monitoring the operating condition of a pump by evaluating fault data encoded in the instantaneous current of the motor driving the pump. The data is converted to a frequency spectrum ...

Methods and system of monitoring and prognostics
Abstract A neural network learns the operating modes of a system being monitored under normal operating conditions. Anomalies can be automatically detected and learned. A control command can be issued or an alert can be issued in ...

Geographic location using multiple location estimators
Abstract A location system is disclosed for commercial wireless telecommunication infrastructures. The system is an end-to-end solution having one or more location centers for outputting requested locations of commercially available ...

Component machine testing using neural network processed vibration data analysis
Abstract A component machine testing technique is provided that performs diagnostic analysis on a vibration signal of the component machine that has been separated from power and load machine background noise in a first neural ...

Neural network based analysis system for vibration analysis and condition monitoring
Abstract A system and a method for tracking long term performance of a vibrating body such as a gas turbine, includes a vibration sensor who time domain outputs are transformed to the frequency domain, using a fast Fourier transform ...

ART 2-A for optimal test series design in QSAR
Abstract The family of adaptive resonance theory (ART) based systems concerns distinct artificial neural networks for unsupervised and supervised clustering analysis. Among them, the ART 2-A paradigm presents numerous strengths for ...

A Novel Approach to Fault Diagnosis in Multicircuit Transmission Lines Using Fuzzy ARTmap Neural Networks
Abstract The work described in this paper addresses the problems of fault diagnosis in complex multicircuit transmission systems, in particular those arising due to mutual coupling between the two parallel circuits under different ...

Machine vision approach for robotic assembly.
Abstract Purpose ? Outcome with a novel methodology for online recognition and classification of pieces in robotic assembly tasks and its application into an intelligent manufacturing cell. Design/methodology/approach ? The ...

SOVEREIGN: An autonomous neural system for incrementally learning planned action sequences to navigate towards a rewarded goal
Abstract How do reactive and planned behaviors interact in real time? How are sequences of such behaviors released at appropriate times during autonomous navigation to realize valued goals? Controllers for both animals and mobile ...