Showing papers on "Condition monitoring published in 1988"

Reliability improvement and economic benefits of on-line monitoring systems for large induction machines

Abstract: Microprocessor-based monitoring systems are being developed for the regular analysis of large induction machine variables and to predict possible fault conditions, so that preventive maintenance can be organized in a cost-effective manner. A method for the evaluation of the improvement of machine reliability made by such monitoring systems is presented. An economic and financial analysis to examine the viability of a condition monitoring system for a large machine using comprehensive rotor, stator, and other parameter measurements is developed. In two case studies, the costs of design, construction, mounting, and operation of condition monitoring systems are discussed, and estimates are made at current costs. These costs are balanced against the costs avoided in cases of unexpected machine failures, lost production, and repairs. Cost estimates for repairs and downtime are made using published information from previous reliability surveys on electrical machines. Information is presented for different machine sizes, which will indicate any relevance of the machine size when evaluating monitoring systems. >

Antifriction Bearing Fault Detection Using Envelope Detection

Abstract: A successful method of detecting bearing faults is described. The transducer is a standard 0-25 kHz industrial accelerometer whose output is processed by a FFT analyser which gives a digital frequency spectrum of the signal. The method of signal conditioning and the failure detection of two bearing faults is described. The method can detect very minor bearing defects and is a powerful tool for bearing condition monitoring.

Standard Defect Monitor

Abstract: The availability of confident defect density data contributes significantly to the control and improvement of a semiconductor process, both in the development phase and in the manufacturing phase [ l 3 1 . Conventional vehicles for defect density measurements, such as random access memories or logic circuits, must pass through the complete manufacturing line in order to reveal the distribution and origin of defects on an electrical test. Consequently, a source of defects in an early stage of the process will remain undetected until the first wafers exhibiting the problem emerge from the fabrication area. In the interim, additional wafers passing through the problematic process step may suffer significant and costly yield l o s s . Monitoring individual process levels separately with single-level electrical structures solves this problem, because fabricating individual process levels instead of the complete process drastically shortens the feedback loop for defect density data.

A knowledge-based system for sensor interaction and real-time component control

Abstract: This paper outlines the integration of a two-dimensional vision system with a pneumatic proximity-to-tactile sensing device to form a Co-ordinated ‘Hand-Eye’ system. With the aid of a knowledge base this system is utilised as an intelligent condition monitoring tool for recognition and detection of orientation of parts in a flexible manufacturing environment. An expert system is formulated to interrogate the acquired data streams for the purpose of comparative studies with the knowledge base. Appropriate data processing methods are employed to ensure rapid manipulation of data for real-time applications.

Modeling and Sensing Issues for Machine Diagnostics

Abstract: As motivated by the need to develop automated machine diagnostics for manufacturing systems, modeling and sensing issues for model based diagnostic systems are explored. Developing models of machine systems are argued to be important for accurately isolating and interpreting machine fault signals obtained from remote sensors. The idea of modeling faults as an unknown inputs to a model of the normally operating machine is introduced. A simultaneous state and input observer can then be used to determine the number of sensors and possible sensor locations required to observe the fault inputs. This technique is demonstrated by detecting a bearing fault in a computer simulated machine tool spindle system. Good results are obtained although the results are shown to be sensitive to measurement noise. Methods for dealing with the noise are discussed. Modeling faults as inputs to a model and monitoring them with a state and input observer appears to be a promising machine diagnostics technique.

Monitoring the condition of feedback control systems

Abstract: A condition monitoring scheme for feedback control systems is presented. This scheme is meant for detecting seriously deteriorating conditions of a feedback system, in both transient state and steady state, before instability becomes manifest. It is assumed that the process is disturbed by a random noise with a rational spectrum and by a series of deterministic signals. The frequency characteristics in steady state oscillatory characteristics in transient state are monitored. A transient detector is used to differentiate steady state from transient state. This scheme divides the monitoring task into three subtasks: transient detection, transient monitoring, and steady-state monitoring. Algorithms have been developed for each subtask, and logic rules have been employed to coordinate these algorithms so that they can function correctly to monitor the system in different situations. Simulation experiments demonstrated the promising performance of this monitoring scheme. >

Leakage Flow Detection in a Fluid Power Speed Control System Using a Personal-Computer-Based Condition Monitoring Package

Abstract: A relatively low-cost personal-computer-based system is used to condition monitor a servo-valve-motor speed control system. Line pressures-flowrates together with motor torque-speed are monitored via 12 bit analogue to digital converters, and a set of performance characteristics are transformed into a mathematical model for the system in its run-in condition. Leakage flows are then introduced from each line, to simulate the onset of failure, and across the lines to simulate motor cross-port leakage deterioration. A graphics and software package is then developed and used to indicate which of the faults is occurring.

Tool identification and condition monitoring

Abstract: The invention relates to an electro-optic device, which is capable of both identifying and monitoring the condition of material processing tools such as those used in cutting and forming operations. This leads to improvements in the efficiency of automatic or computer-integrated manufacturing procedures, wherein tools are inspected on the basis of signatures derived from an optical scattering system. A laser source is used to illuminate a tool which is rotated eg in a monitoring station prior to the commencement of a machining operation. Light scattered by the tool is picked-up by a photo-detection system and the resulting signature signal is compared with a reference signature signal.

Multi-processor simulation of diesel engines for condition monitoring applications

Abstract: The paper describes the development of a multi-processor diesel engine simulator for applications which include condition monitoring, control system design, investigation of engine transient behaviour and operator training. The uniqueness of this current work is the application of parallel processing computer hardware, which brings a dramatic reduction of computation time compared to supermini and mainframe computers, and is both very compact and relatively inexpensive.

On the application of the time series in structural failure detection and monitoring for offshore applications

Abstract: Because of the uncertainty of random loading within the life of offshore platform structures, the structural integrity should be checked frequently, especially during bad weather, using condition monitoring techniques to better understand the dynamic behavior of the system in time. It becomes obvious that processing the time data on structural response as accurately and rapidly as possible is the basic requirement for the application of online nondestructive testing. In the research presented in this paper, the Auto Regressive (AR) model, Moving Average (MA) model and a combination of AR and MA models--defined as the ARMA model--were studied. It was found that the ARMA model is the most significant for random data processing and that comparison of the index value of dispersion energy of each characteristic root of the ARMA model and inspection of the variation of the ARMA spectrum can often help to identify the nature and location of the structural failure. Local monitoring by suitable pickups is helpful and global monitoring on the topside is necessary.

Condition monitoring of an induction machine using a stochastic search technique

Abstract: This paper describes the principles of a new technique for electrical condition monitoring of the stator and rotor circuits in an induction machine. Using time-domain terminal voltages and currents with rotor position data, a stochastic search technique (simulated annealing) is able to confirm that the machine windings are healthy, or indicate that there is a fault and provide information about the location and nature of the fault. The technique is demonstrated using experimental data from a laboratory machine with both armature and secondary winding faults.

The ghost in the machine

Abstract: The first stage in engine room automation enabled removing the engineer from the engine room. This article discusses new developments in machinery monitoring methods that seem aimed at taking the engineer off the ship altogether. The requirements to be met in developing sophisticated automation systems are many: assuring inherent reliability of the machinery itself; providing the ability to prevent impending failure; the capability for condition monitoring, correct diagnosis, and remedial steps for running problems; accommodation to ship speed and load; and data gathering for planned maintenance. Monitoring systems that are being developed to deal with these problems are described. They include an AEG Telefunken system that monitors and controls all important data for both navigation and operation; Siemens AG equipment that combines autonomous subsystems with a central control/bridge control center in such a way that any one unit remains unaffected by a fault in any other; a "fault-indicating knowledge system" (FIKS) developed by Wartsila Diesel; a diagnostic system by Krupp MaK; and others. Although all have merit, the author notes that a true breakthrough awaits the combination of all shipboard tasks and operations into a single system sufficiently reliable to allow ships to operate in a manner similar to that of aircraft.

Condition monitoring and nodal vibrations in switched reluctance machines to detect rotor radial positioning faults

Abstract: This paper analyses the nodal vibration set up by different vibration modes in a switched reluctance machine which has an eccentric rotor. The unbalanced magnetic forces are calculated using finite element analysis and compared to the vibrations measured in the actual machine. It is concluded that vibration monitoring could be used in a switched reluctance machine as the basis of a condition monitoring system.

The Application of Condition Monitoring Techniques to Product Quality Monitoring

Abstract: Techniques normally associated with automated condition monitoring, such as dynamic analysis, spectrum comparison and fault diagnostics may be used to create a sensitive inspection technique for mechanical products capable of detecting faults not easily found from performance tests. This article outlines the concept of the technique, known as Product Quality Monitoring (PQM), examines some of the methods employed and discusses advantages, limitations and future development.

Diagnostic and preventive maintenance strategies in manufacturing systems : proceedings of the IFIP TC 5/WG 5.3 Working Conference on Diagnostic and Preventive Maintenance Strategies in Manufacturing Systems, Dubrovnik, Yugoslavia, 1-4 September, 1987

Abstract: Concepts and Maintenance Strategies in CIM Systems. Computerised Maintenance Management Systems - The Human Factor (M.F. Green). Automatic Condition Monitoring in the Hot Strip Mill of Rautaruukki Oy Raahe Steel Works (M. Pajukoski). The Future of the Maintenance - An Overview (D. Stanivukovic). Computer Simulation and Diagnostics. New Diagnostic Methods of Faults External to the Controller at Manufacturing Systems (A. Storr et al.). Safecontrol - A Millwide Condition Monitoring System (A. Ollila). On-Line Acquisition and Analysis of Mechanical Failure Data (T.R. Moss). Computer-Integrated Maintenance Systems. Organisational Aspects of Computer Applications in Maintenance Management (K. Smit). Overall Monitoring System by Means of Sound Recognition (S. Takata, J.H. Ahn). Pattern Recognition Based Learning and Decision Making in Complex Machine Tool Monitoring Systems (L. Monostori). Using Expert Systems in Decision Making in Maintenance Management (L. Mann). Expert Systems in Maintenance. The Future of Computerised Maintenance (V. Milacic, V. Majstorovic). Building an Expert System for Maintenance (G. Spur, D. Specht, T. Gobler). Predictive Maintenance: A New Paradigm for Diagnostic Expert Systems (G.M.P. O'Hare, W.J. Black, G.V. Conroy). EIDEMON - An Expert System for Fault Diagnosis (R.E. King). An Expert System in Diagnosis for Rotating Machines through the Vibration Measurements (D. Menexiadis, C. Tahon, R. Soenen). An Expert Diagnostic System of Mechanical Equipment (Wang Hangong, Yang Chun).

New opportunities in diesel condition monitoring

Abstract: The purpose of this paper is to describe the condition monitoring process and the extent to which the process can be automated using current technology. The capabilities of a hypothetical state-of- the-art system are illustrated by describing a fictional engine failure and the way in which the system could detect the failure, diagnose it, and advise the operator. The most advanced capabilities are chiefly due to developments in expert system technology. Expert systems enable better use to be made of data obtained from sensors.

A condition monitoring system for high pressure natural gas transmission plant

Abstract: The delivery of natural gas through the National Transmission System into the twelve regional systems and ultimately on to the consumer, requires a number of control functions to be performed. The major objectives when performing these functions can be broadly summarised as follows. System safety, integrity and security of supply. Minimisation of operating costs. Optimization of flow capacity and storage utilisation. Modern control technology coupled with the major advances in electronic microprocessor technology provided the basis for the development of schemes to overcome the current operational problems and thereby greatly improve the efficiency of control. The author briefly describes a microprocessor based control strategy which has been successfully implemented to overcome many of the operational problems and goes on to illustrate a strategy which provides a reliable condition monitoring system applicable to NTS offtakes. The ultimate condition monitoring system is embedded within the existing microprocessor based control structure in an attempt to avoid any possible degradation in terms of overall system reliability, which is always a major consideration in such applications. >

Intelligent Condition Monitoring of Gas Compressor Engines

Abstract: The intelligent condition monitoring of industrial plant is a rapidly expanding area of research. It combines two radically different disciplines: classical condition monitoring and intelligent knowledge-based systems.The paper presents an overview of the areas of orthodox condition monitoring systems, intelligent knowledge-based systems and intelligent condition monitoring. The paper also includes two examples of the diverse work underway in this area.Finally, there is a discussion of a current British Gas intelligent condition monitoring project, which is investigating the application of intelligent systems techniques to condition monitoring of gas compressor engines. This features a detailed summary of a particular element of the problem area. In addition the nature of the future development of this system is also discussed.