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Model-based fault detection and isolation (FDI) methods are used to determine faults by examining the deviation of sensed information from anticipated system trajectories. In this paper, a comprehensive model-based FDI framework is proposed to improve fault identifiability and reduce false alarms during maintenance testing. In this framework, robust maintenance tests are designed and conducted, followed by false alarm analysis. The optimal tests designed improve the identifiability of faults by manipulating system inputs to maximize information with respect to faults, in the form of sensitivities of the system outputs. Each test design is evaluated a posteriori using the system model to explore whether false alarms are plausible, given system uncertainty and measurement noise. The proposed framework is applied on two case studies that compare the identifiability of faults at nominal and optimal system test conditions. The first case study focuses on a plate fin heat exchanger with various levels of particulate fouling at steady-state and transient conditions. The second case study deals with the same type of fault but in an aircraft environmental control system with multiple sources of uncertainty.

In the process of transformer overhaul and maintenance in nuclear power plant, a large number of Chinese technical documents have been accumulated, including transformer structure and corresponding failure mode, failure cause analysis, maintenance test record, inspection and defect elimination record, fault problem and other information. It contains rich fault information, fault cause description and troubleshooting method and other key features of fault and maintenance, which is helpful for the maintenance of transformer To guide the operation and inspection work and fault diagnosis and analysis work. In CSCW and its related fields, artificial intelligence method and knowledge engineering technology, especially konwledge graphping technology and its intelligent application, have attracted extensive attention from academia and industry. Based on a series of data acquisition, analysis and algorithm flow, we have a deep understanding of the practical effect of applying intelligent algorithm directly to the construction of transformer fault konwledge graph and decision support application.

The on-board power supply system provides power for the launch vehicle. The power transmission and transformation system plays an irreplaceable role to ensure that the on-board power supply system receives the normal working voltage of the launch vehicle. There are many types of faults in power transmission and transformation systems. The traditional faulty diagnosis method of power transmission and transformation equipment has the disadvantages of being susceptible to experts’ subjectivity and model’s ossification. In this paper, a new method of equipment fault diagnosis based on big data is proposed. On the basis of big data, this paper introduces the failure mode clustering algorithm, the state parameter correlation analysis algorithm, the fault diagnosis method based on the correlation matrix, and other key fault diagnosis technologies. The fault record data of the 400 kV voltage grade oil-immersed transformer bushing in the past ten years by a Chinese combat unit is used as a case for demonstration. The results show that the accuracy rate of SC-LSTM-K-means clustering model exceeds 95%. And the fault classification mode can be accurately obtained. A priori correlation algorithm with TA coefficient can be used to evaluate the strong and weak relationship between the state parameters; the fault diagnosis matrix based on Pearson’s correlation coefficient can accurately determine the fault mode consistent with the actual operation and maintenance test results. Therefore, the fault diagnosis method of power transmission and transformation system based on big data can both effectively obtain the inherent laws of historical data and realize more accurate fault diagnosis with data adaptability.

The PRESLEEP project is aimed at the fine assessment and validation of the proposed proprietary methodology/technology, for the automatic detection and prediction of the transition between the behavioural states of a subject (e.g. wakefulness, drowsiness and sleeping) through a wearable Cyber Physical System (CPS). The Intellectual Property (IP) is based on a combined multi-factor and multi-domain analysis thus being able to extract a robust set of parameters despite of the, generally, low quality of the physiological signals measured through a wearable system applied to the wrist of the subject. An application experiment has been carried out at AVL, based on reduced wakefulness maintenance test procedure, to validate the algorithm’s detection and prediction capability once the subject is driving in the dynamic vehicle simulator.

This paper takes the construction and operation of city ecological park as the research object, and discusses the planning and design method and process based on BIM from the perspective of tourists. According to the study of the definition, function, value and difficulties of BIM, the application of BIM in the whole construction cycle of ecological park project is summarized and analyzed, and the principles and concepts of urban ecological park planning and design are clarified. Then we mainly introduces the layout template setting, 4D construction simulation, development of operation and maintenance test data interface, and realization of collaborative work. The research results show that BIM technology can realize the visual display of project design phase, which greatly increases the amount of construction drawings, and improves the design efficiency. It also controls the project cost and shortens the construction period, to promote the overall improvement of similar project management.

Medium voltage (MV) polymeric cables are critical assets in modern power systems, since their introduction, approximately five decades ago. More recently, there has been a growing emphasis on the maintenance testing of polymeric cables, with some of them being prone to premature failures. This paper covers the various techniques available for the forensic failure investigation of polymeric cables through practical examples. Some of these include diagnostic electrical tests such as Insulation Resistance, AC Hipot & PD, and nonelectrical procedures such as visual inspection, optical microscopy, and differential scanning calorimetry (DSC). The recommended order of performing these techniques is also presented, based on the suspected failure mode. This serves as a practical guideline for utilities, towards identifying the type of cable failure sustained in the field. Diagnostic electrical testing (post-failure) helps establish the most probable cause of failure associated with polymeric cables and/or their accessories. A very useful, but less explored technique in polymer morphology is the DSC, which can be used to reveal the thermal history of a polymeric cable since its processing. In this regard, a detailed case study is presented to highlight the use of a DSC thermogram for determining the maximum temperature experienced by a polymeric cable and the potential source of heat.

IEC 61850 is the established standard for substation communication. Since the standard describes different stages of lifecycle of Substation Automation Systems the demands for specification, testing, and especially simulation differ. The approach described in this study can be used in the different stages and fulfil practical requirements. It describes the requirements for simulation and proposes an implementation applicable. If a single Intelligent Electronic Device (IED) and its data model to be simulated in technical investigation phase is sufficient at Factory Acceptance Testing and Site Acceptance Testing multiple IEDs and utilised services as GOOSE and reports will be needed. In addition, the methods described for indicating test mode/behaviour and simulation indication become important. The simulation has to be embedded in testing environment and interact with tools to be used for visualisation of changes in IED's data model. Advanced services in IEC 61850 like setting groups control, switching device control and file transfer have to be added. The requirements will be discussed from a utility's perspective. The method described can be extended for routine testing and maintenance testing, e.g. after firmware upgrades. An outlook develops a vision to be utilised for automation and control testing.

Regression testing is one of the types of maintenance testing and it is performed in case of bug-fixing or whenever there is any new functionality incorporate in the dynamic environment of software...

This paper provides a new method for designing the load of transmitters switch components on provincial radar test platform. Based on the calculation of the specific parameters related to the actual charge switch components, the load-related data model is obtained, the simulation is carried out, and the results are consistent with the actual test results. Through the theoretical numerical analysis of the load of the charging switch components of the transmitter device in the new generation of weather radar maintenance test platform, radar maintenance personnel at all levels can deepen the thorough understanding of the CINRAD/SA transmitter and have some enlightenment and improvement on the maintenance guarantee ability of the new generation of weather radar.

A method is proposed to improve system reliability in terms of self-detection and isolation of discrete faults. The application of this method on the design of built-in tests for maintenance is presented using the case of aircraft environmental control system maintenance testing. Built-in testing during aircraft on-ground maintenance allows for wider system input variability due to the absence of operational constraints and requirements. This provides an opportunity to optimally design tests that improve the fault detection and isolation capabilities for operators and maintenance crews. A general mathematical framework for built-in test design is shown using a model-based active fault detection and isolation technique. The motivation for this paper is first illustrated through a case study showing the inability to detect and isolate faults at different conditions, demonstrating how system states contribute to these issues. The success of the proposed framework is demonstrated by designing built-in tests that are capable of fully detecting and isolating a multiplicity of faults common to aircraft environmental control systems. We conclude by presenting the value of the proposed method of detecting and isolating faults, as a solution to a constrained optimization problem with the admissible system inputs as manipulated variables.

In order to reach commercially-relevant availability, future fusion power plants must minimise the duration of maintenance shutdowns. However, as radiation levels increase, so too will the number of maintenance tasks that must be performed without human access. To meet these conflicting constraints, remote maintenance systems must therefore significantly increase their capabilities, performing tasks faster and in parallel. Unfortunately, the current teleoperation-based maintenance approach is inherently limited in these regards. Automation emerges as a potential solution, having demonstrated dramatic productivity gains in manufacturing across the world. The European DEMO project has begun to explore the feasibility of automated maintenance as a route to meeting the challenging availability targets. To this end, the Automated Inspection and Maintenance Test Unit (AIM-TU) has been designed and constructed, providing a highly versatile test platform able to adapt to evolving R&D programmes. It consists of a modular robot cell equipped with two robot arms mounted on linear rails, interchangeable end-of-arm-tooling, a variety of vision sensors and a fully integrated safety system. The hardware is supported by a modular software architecture, which permits different control input modes and provides a digital twin simulation of the cell for virtual verification and validation of control algorithms. This paper provides an overview of the system’s capabilities and reports on the first automated maintenance feasibility tests performed on the cell: automatic replacement of JET reactor tiles and automatic contactless inspection of tile anomalies.

Preventive maintenance may be performed on a few selected components when a component fails. Importance measures can be used to identify the most important component that requires maintenance. However, this process involves two problems: (a) the preventive maintenance time of the selected component may be bigger than the maintenance time of the failed component; (b) the most important component may incur the highest maintenance cost. Traditional importance measures do not consider the possible effect of maintenance time and cost, which significantly affect the improvement of system reliability. Given the joint effect of component maintenance cost and time on system reliability, this study proposes a cost-based integrated importance measure (IIM) to identify the component or group of components that may be selected for preventive maintenance. The characteristics of cost-based IIM are examined to determine the relationships among failure rates, shape parameters, and the scale parameters of different components. Finally, an application to a wind turbine system is used to illustrate its usage.

This paper presents an adaptive maintenance model for equipment that can be adjusted (minor preventive maintenance, imperfect state) or replaced (major preventive maintenance, as good as new) at specific scheduled times based on degradation measurements. An initial reliability law that uses a degradation-based model is built from the collection of hitting times of a failure threshold. Inspections are performed to update the reliability, the remaining useful life, and the optimum time for preventive maintenance. The case of both as good as new replacements and imperfect adjustments is considered. The proposed maintenance model is based on the optimization of the long-term expected cost per unit of time. The model is then tested on a numerical case study to assess its effectiveness. This results in an improvement for the occurrences of maintenance tasks that minimizes the mean cost per unit of time as well as an optimized number of adjustments that can be considered before replacing an item. The practical application is a decision aid support to answer the 2 following questions: Should we intervene now or wait for the next inspection? For each intervention, should we adjust or replace the item of equipment? The originality is the presence of 2 criteria that help the maintainer to decide to postpone or not the preventive replacement time depending on the measured degradation and to decide whether the item should be adjusted or replaced.

An important issue in maintaining the industrial equipment is to introduce an appropriate maintenance policy to monitor the conditions of the equipment. In this research, an investigation on the concurrent effects of erosion and random shocks during the useful life of the equipment is studied. In this regard a model is introduced to optimize the total cost including logistic, complete repair and incomplete repair costs. The proposed model determines the optimal number of the incomplete repairs, the time duration between inspections and the probability of equipment to be failed. A numerical example is solved by means of computer simulation. The results indicate that the proposed model performs well for minimizing the costs of maintenance and repair.

Condition-based maintenance is effective in improving availability by preventing failure occurrences, especially in the case where the lives of equipment or components are unstable because of varying operating and environmental conditions. However, failure symptoms are not necessarily detected by monitoring systems in an accurate manner. In such cases, we need to determine the proper criteria for the effective execution of preventive maintenance to minimize the total effects, which include both the effects of successful preventive maintenance and those of unsuccessful ones. This paper proposes a method to determine the optimum criteria for executing the preventive maintenance of the mechatronics equipment. The error messages generated from the sensor signals do not have one-to-one correspondence with the component deterioration and failures because the mechatronics equipment usually use sensors, which are equipped for control purposes, to monitoring the failure symptoms. Therefore, we need to devise the method to relate the error messages with the deterioration and failures. We propose a four-step procedure for this purpose, in which a structural and functional analysis is integrated with a history data analysis. The proposed methods are applied to the automatic ticket gates installed in the train stations in Japan to verify their effectiveness.

During the research there were two domain analyses performed: one of maintenance testing and the other of ontologies. The goal of the research was the increase of maintenance testing quality by developing a domain knowledge base and common scenarios which are used in the real life maintenance testing in the form of the ontology. The analysis shown, that it's possible to use ontologies to make the process of maintenance testing easier. The testing in the development process and testing in the process of software maintenance were defined and structured in the form of the ontology, necessary relations between them were established. Besides, the ontology of maintenance testing also presents the general knowledge of the domain in the formal way. It was found, that the decision-making in the area can be easier with the help of ontology.

In view of the long data collection period of Army armored equipment maintenance and repair test data, this paper is devoted to researching the method of verifying the maintenance index in the case of small sample size, analyzing the historical distribution type of maintenance quantitative index, and constructing the SPRT based method. The equipment maintenance quantitative index test verification model, and the maintenance test based on the model, can achieve effective verification of the maintenance index under a small number of trials. The method is carried out to verify the method through historical experimental data. Under the premise of obtaining the same result, the number of tests is effectively reduced, which fully proves the scientificity of the method, and has the adjustment of equipment maintenance test plan and the whole development cycle setting. Important reference value.

In order to solve the problem that the sample maintenance test of the ship equipment is less in the maintenance test and evaluation work of the ship equipment, it is difficult to adopt the classical statistical method for the maintenance analysis and verification. The maintenance information of a ship is taken as the research object in this paper, the content and characteristics of the maintainable data sample set collected around the ship’s pilot phase, the maintenance information fusion research on the research equipment and similar equipment was carried out by the method of goodness of fit. By introducing bootstrap method to compensate for the errors caused by insufficient sample size, the process of using the goodness of fit method to fuse the ship’s research equipment and similar equipment maintainability information is sorted out. It provides theoretical methods and technical means to support the maintenance testing and evaluation of equipment.

With the continuous expansion of the campus area, the campus traffic problem is becoming increasingly serious. For example, the shortage of campus travel tools and the difficulty of students traveling, these problems need to be solved urgently. The emergence of shared travel tools will bring more convenience and choices to college students. This article has preliminarily analysed and inquired into the design and management mode of sharing travel tools for university campus. And in view of the traffic conditions in the campus, the solution is put forward by taking full consideration of the problems such as borrowing and stopping, driving mode, charging and endurance distance, maintenance testing and so on. A substitute tool that can be used in campus, convenient access and low cost will provide convenience for students to travel, reduce pressure for school traffic, and be more conducive to the construction of a low carbon and environmental protection campus culture.

Immersive virtual maintenance is a standard practice for the evaluation of material sustainability. New techniques of service evaluation rely largely on multiple samples collected by realistic on-site tests, and it is complex for them to incorporate valuable knowledge from immersive virtual maintenance, leading to a high expense of maintenance evaluation. This paper therefore proposes a weighted data fusion approach using the t-test and F-test for virtual simulation data and real-life test data, based on a product's multi-stage immersive virtual maintenance simulation studies. The virtual and real fusion samples is then periodically fused by the multistage Bayesian iteration fusion method. Then to iteratively fuse the simulated and actual fusion samples, the multistage Bayesian iteration fusion method is used. Finally, on the basis of the maximum posterior statistical analysis of the final functional on-site samples, the maintenance index values are found. The results of the simulation show that the proposed approach can effectively combine virtual and real multi-stage maintenance details, reduce the total number of on-site maintenance test samples, and obtain more detailed results for maintenance evaluation.

This research aims for guidance in improving the productivity of the machines in case study of refinery plant based on the principle of preventive maintenance of machinery applications. This is to increase the availability and improve the reliability and overall equipment effectiveness (OEE) of the machines. From the data collected showed that high cost of maintenance is quite high caused by non-standard maintenance and no prioritization of machine maintenance. Therefore, the researchers proposed a maintenance program developed based on reliability engineering with failure mode and effects analysis (FMEA). FMEA was the first brought to analyze the root causes of machine failure and to evaluate the risk priority number (RPN). The data was performed preventive maintenance plan standardized the maintenance system in order to optimize maintenance task and maximize the efficiency of machinery. After applying FMEA, the result showed that the chance of failure in equipment was very low (1 time in 12 years) after the scheduled maintenance plan and opportunities to detect damage in advance was moderate to high. Therefore, the equipment with a moderate to high risk is likely more damage than the first round of maintenance (5 years). Moreover, the average of the residual risk level analysis of the machine decreased by 59.165% and overall equipment effectiveness (OEE) increased from 92.66% to 98%

Purpose – The purpose of the paper is to provide a method for selection of an optimum level of repair by replacement of an equipment based on its cost. In a ship where the engineer has a vast variety of equipment and systems to operate and maintain within limited time frames and availability of human resources, it is often difficult to disassemble a whole equipment to replace a faulty component. It is instead a lot easier to just replace the faulty equipment with whole new equipment. However, such a decision comes at an enormous capital cost. Therefore, the key question is, can we have a model to help us arrive at a decision on the correct level of carrying out repairs? Design/methodology/approach – The paper uses a model based on cost and convolution of failure distributions of critical sub-components of an equipment. Necessary assumptions based on real life experience have been incorporated in the model. Findings – The paper used an example of a particular type of motor driven sea water centrifugal pump which was commonly used in main engine sea water system, firefighting system, air conditioning system, etc. The pump had one of the highest failure rates in the ship (approximately one failure per 150 days) and the engineers found it cost and time effective to replace the entire pump on failure rather than carrying out replacement of the failed components. The model analyzed that the engineer’s hunch was not off the mark. Research limitations/implications – The implication of the work presented in the paper will be savings in maintenance cost and downtime due to optimal level of repairs on a multi-component equipment. The limitations of the work are assumption of independence of failures of components. This may not be true in all the cases. Further, opportunity based maintenance has also not been considered. Originality/value – The originality of the paper lies in the presentation of a method for selection of an optimum level of maintenance for a multi-component equipment

One of the strategic areas of development of all oil refineries (OR) in the Russian Federation is the improvement of equipment dependability and safety. The regulatory framework often does not take into consideration the design features of devices which, on the one hand, standardizes the service conditions, but, on the other hand, may cause inefficient maintenance of individual types of equipment. Due to the unpreparedness of the Russian oil refining complex to migration from scheduled preventive maintenance to condition-based maintenance, a large number of obsolete equipment and unceasing growth of technology complexity in modern ORs, it is required to improve and update the statistical and analytical base of dependability indicators of the equipment in operation. Russian and foreign experience of OR operation shows that damaged OR pump equipment can cause significant material damage and human casualties. A fair share of faults and failures that can cause accidents in ORs is concentrated in pump and compressor facilities. Ensuring safety of equipment operation and ORs as a whole requires reducing the probability of accidents. To that effect, technical condition monitoring facilities are deployed and equipment diagnostics are performed. A priori information analysis is also an option. Results. The article presents the results of documental inspection of performed maintenance of NK, NKV and NPS type pumps of a Russian OR conducted for the purpose of improving dependability and safety of pump operation. Probabilistic and statistical methods were used. The article presents an analysis of dependability indicators based on Gomertz-Makeham parametric distribution. This distribution is widely used in survival analysis and characterizes both system deterioration, and the influence of factors that do not depend on operation time. The authors analyze maintenance operations and repair cycles, identify the least dependable pump components and most frequent repair operations, show the influence of total operation time on pump dependability indicators. For the inspected pumps, the availability factors, utilization factors and average time between maintenance have been defined. The analysis identified that the availability factor of pumps depends not only on the average time between maintenance (that in turn depends on the frequency of required maintenance), but also on the utilization factor of the pumps. Beside the conventional dependability indicators, i.e probability of no-failure and failure rate, based on pump failure rate analysis ultimate times to failure for the inspected pumps were identified. Ultimate time to failure is the operation time beyond which gradual deterioration process significantly accelerates and causes a growth of the number and/or quality of partial failures. A significant accumulation of partial failures results in the loss of function or destruction of equipment. This dependability indicator is the most important in insuring the normal operation from the point of view of operating services. Conclusions. The article shows taht the identification of the ultimate time to failure for improved dependability and reliability of equipment operation must involve regular updates of input data in order to identify the beginning of the process of equipment “aging” for prevention of accidents caused by out-of-limit tear and wear of equipment.

Georeferenced 3D models are an increasingly common choice to store and display urban data in many application areas. CityGML is an open and standardized data model, and exchange format that provides common semantics for 3D city entities and their relations and one of the most common options for this kind of information. Currently, creating and maintaining CityGML models is costly and difficult. This is in part because both the creation of the geometries and the semantic annotation can be complex processes that require at least some manual work. In fact, many publicly available CityGML models have errors. This paper proposes a method to facilitate the regular maintenance of correct city models in CityGML. This method is based on the continuous deployment strategy and tools used in software development, but adapted to the problem of creating, maintaining and deploying CityGML models, even when several people are working on them at the same time. The method requires designing and implementing CityGML deployment pipelines. These pipelines are automatic implementations of the process of building, testing and deploying CityGML models. These pipelines must be run by the maintainers of the models when they make changes that are intended to be shared with others. The pipelines execute increasingly complex automatic tests in order to detect errors as soon as possible, and can even automate the deployment step, where the CityGML models are made available to their end users. In order to demonstrate the feasibility of this method, and as an example of its application, a CityGML deployment pipeline has been developed for an example scenario where three actors maintain the same city model. This scenario is representative of the kind of problems that this method intends to solve, and it is based on real work in progress. The main benefits of this method are the automation of model testing, every change to the model is tested in a repeatable way; the automation of the model deployment, every change to the model can reach its end users as fast as possible; the systematic approach to integrating changes made by different people working together on the models, including the possibility of keeping parallel versions with a common core; an automatic record of every change made to the models (who did what and when) and the possibility of undoing some of those changes at any time. This work was supported by the Optimised Energy Efficient Design Platform for Refurbishment at District Level (OptEEmAL) project, Grant Agreement Number 680676, 2015-2019, as part of the European Union’s Horizon 2020 research and innovation programme.

Defense budget decreases in recent years with increasingly complex weapon systems and component equipment has mandated innovative support solutions to control costs. Automatic Test Systems (ATS) have been standardized by service branch in an effort to control the costs of support for support equipment. Support contracts with the ATS provider for repair services leveraged repair volume to reduce cost per repair. Support contracts where the ATS provider also supplies loaner spares used centralized wholesale spares systems to reduce retail spares requirements. Commitment to aggressive turnaround times for repairs reduced wholesale spares requirements. Entrusting the ATS provider with hardware configuration management improved system availability by allowing design improvements to address bad actor concerns. Industry has shown that the next logical step in the progression is leased support equipment, where system configuration management including both hardware and software configuration is entrusted to the ATS provider. The ATS OEM has unique knowledge about the hardware and software interactions in the system that allow efficient resolution of availability detractors like false alarms. The OEM understands instrument peculiarities allowing increasingly efficient fault detection and isolation. The costs associated with the improvements will be spread across the installed base so that each customer benefits from the increased availability, whether they have one system or hundreds. The unique requirements associated with leased equipment in a military operating environment will be explored. These steps explore only the horizontal axis of test, where the vertical axis includes all layers of test, such as design verification test, factory test, acceptance test, qualification test, at-platform maintenance test and off-platform maintenance test. The potential savings by reuse along the vertical axis include ATS and Test Programs Set (TPS) components. The factory test, acceptance test and off-platform performance test requirements are often very similar, if not exactly the same. The unique requirements associated with TPS reuse in a military environment will be explored.

Civil aircraft maintenance tests are used to detect latent failures in the Flight Control System (FCS) that cannot be detected through continuous monitoring. And each maintenance tests have their required exposure time intervals. The exposure time intervals are used to determine whether the maintenance tests will be executed automatically or manually. This Paper focused on the study of automated tests hosted in the FCS, which do not require the maintenance user intervention, and these tests will be automatically initiated following rollout phase. Automated tests are capable of commanding the primary surfaces and injecting failures into the FCS components, therefore they will be allowed to execute only when the aircraft is in a safe state. The suite of logic that manages and controls automated tests could contribute to hazardous or catastrophic hazards. This logic is referred as post flight and needs to be investigated to ensure the safety of the civil aircraft.

Testing is an inevitable process in safety critical applications such as avionics, space research, etc. In those systems, apart from manufacturing test, which is carried out after the chip is fabricated, maintenance testing also to be done in order to ensure that the device functionality remains the same. Digital circuits that are fabricated these days contain Built-in Self Test (BIST) arrangements with in the chip to perform the above said tasks. Since power consumption of the chip is crucial in battery operated electronic systems, reducing power in design and test circuits become mandatory. The proposed approach is allowed power LFSR using three ring oscillators and fuzzy logic concept. It reduces power consumption during test pattern generation and test response analysis processes by replacing the Linear Feedback Shift Register (LFSR) by its low power version. The proposed approach reduces power consumption up to 4.5% by dipping the number of switching activities in the circuit during the testing process.

In this chapter, we describe the calibration of three real engines in GasTurb performance models, using only measured data and information from the public domain. We recommend following a specific sequence of tasks and show that starting from relatively little input data the analysis evolves to make reliable performance predictions down to component level across a wide range of power settings and operating conditions. We describe in detail how to check the input data for consistency and create a Cycle Reference Point. The focus then moves to the compressor and turbine maps with advice on positioning the reference point in the map, scaling and finally modifying efficiency and speed. Equally important are the hints on how to implement information on active control items such as variable guide vanes or tip clearance systems. The engines modeled are the Pratt & Whitney J57, a two-spool turbojet run in an altitude test facility, the CFM56-3, a high bypass ratio turbofan run on a maintenance test bed and the Williams F107, a low bypass ratio turbofan with mixed exhaust and data taken from a specification.

This paper presents an analysis of the main operating conditions that may lead to inappropriate differential relay operation. The specific numerical differential relay is established in the SIEMENS laboratory of the “Institut de Formation en Electricite et Gaz (IFEG) Ain Mlila”. The procedures of setting and testing, in particular, the SIEMENS 7UT613 numerical relay are described. In this regard, several tests are applied to verify their characteristics then the setting parameters are calculated and loaded to the numerical relays, using the DIGSI 4.87. In addition to this, the relays secondary tests are conducted using the OMICRON CMC 356 of the OMICRON electronic GmbH Company where the results are used to verify the exact operating characteristics of their protection elements.

Risk-Risk-based inspection (RBI) has been developed in order to identify risky equipments that can cause major accidents or damages in large-scale plants. This assessment evaluates the equipment's risk, categorizes their priorities based on risk level, and then determines the urgency of their maintenance or allocates maintenance resources. An earlier version of the risk-based assessment software is already installed within the equipment management system; however, the assessment is based on examination by an inspector, and the results can be influenced by his subjective judgment, rather than assessment being based on failure probability. Moreover, the system is housed within a server, which limits the inspector's work space and time, and such a system can be used only on site. In this paper, the development of independent risk-based assessment software is introduced; this software calculates the failure probability by an analytical method, and analyzes the field inspection results, as well as inspection effectiveness. It can also operate on site, since it can be installed on an independent platform, and has the ability to generate an I/O function for the field inspection results regarding the period for an optimum maintenance cycle. This program will provide useful information not only to the field users who are participating in maintenance, but also to the engineers who need to decide whether to extend the lifecycle of the power machinery or replace only specific components.

This paper focuses on maintenance test flying as pertaining to commercial jet aircraft. Aircraft maintenance manuals or regulatory prescriptions require aircraft to be test flown prior to being released to service, following specific maintenance, repair, overhaul or modification events. Further, such flights might be conducted to accept or return aircraft as demonstration of their serviceability. Similarly, test flights to verify aircraft performance are at times required.Such maintenance test flights are mostly conducted by pilots rated to fly those aircraft primarily in commercial line operations, typically with no or little training on such specific maintenance or performance test flight procedures or techniques. The international regulatory environment remains in flux with discussion ongoing.In conducting such flights a pilot is exposed to activities outside the normal aircraft standard operating procedures up to the edge of the operational flight envelope. Whilst not intentional, abnormal aircraft behaviour can nevertheless result in inadvertent flight outside the envelope with a consequential potential loss of control. History has shown that the predominant cause of fatal accidents during maintenance test flying result from complex loss of control scenarios not recovered or not recoverable. This raises the question of adequacy of pilot training.Maintenance test flights are a necessary component for the industry to maintain its exceptional safety standards and minimising loss of life. But such flights in themselves remain demonstrably one or two orders of magnitude more risky than commercial flights.

devices and equipment have become very complex and are expected to operate under stringent environments. Equipment's should be properly maintained in order to fulfil their objectives. The signs of equipment's failure may not be apparent to clinical staff. Therefore they should be inspected periodically. Scheduled inspections help ensure the safety and efficacy of the medical equipment. A software tool is developed to implement a risk oriented prioritization of devices for equipment maintenance. First establishing an effective, efficient Computerized Preventive Maintenance Management System, collecting the data of equipments in laboratories and implement them to the system. The reports based on the inspection results, help determining a better maintenance's schedule.

SUMMARY The inspection of power supply facilities can now be conducted with high accuracy using remote monitoring technology. In contrast, it is difficult to install sensors at demand facilities because their scale and installation environment differ among customers. As a result, the demand facilities are inspected at fixed time intervals. In this paper, we propose condition-based maintenance (CBM), which improves maintenance quality at demand facilities. The proposed method was developed using maintenance data from demand facilities, collected using time-based maintenance, and we conduct the analysis primarily using failure data. We use data mining to analyze transaction data that we modeled on the basis of the maintenance data and to construct a “failure predictive model” that can predict the failure of facilities and its causes from the results of the analysis. By using the constructed model, we will be able to identify the objects requiring maintenance which may most likely lead to failures in the future, and this study can contribute to improvement of maintenance technologies for demand facilities using the proposed CBM.

In my country, length of land coastline exceeds 18000 km and islands scatter in the sea, so coastal environment is typical operational environment. Characteristic of coastal environment is humid, hot and has a long rainy season, salt atmosphere and moulds also influence armored equipment. In this paper, deep analyzes performances influence of armored equipment in coastal environment, constructs indexes system of use and maintenance test in coastal environment, establishes evaluation model based on AHP, ADC and Fuzzy theory synthesis, availably realizes quantitative evaluation of use and maintenance of armored equipment in coastal environment.

This paper presents the review/monitoring history of all kind of service equipment organization on common platform with identical format for information entry. The equipment covers ranges of all sizes, cost, portability and its use for different applications like emission measurement, safety measurement, environmental conditioning, on road measurements, etc. Micro level information data consists of equipment information (Installation date, cost etc), daily usage, observation of condition of equipment, maintenance solution, down time etc. This also provides information on availability of equipment, its actual use and tracking of maintenance data with fault processing. Recording of technical and financial information of ongoing activities including utilization is done on daily basis. The information is linked to various analysis tools. It has Inbuilt feature to measure, calculate and compare the equipment performance, to move towards achievements of TPM (Total Productive Maintenance) and six sigma business development strategy. Analysis module consists of age analysis to follow bath tub curve in its full life cycle (Infant Mortality Rate), uncertainty in breakdown faults, cause- effect analysis, root cause analysis, time and condition of component failures, With the help of analysis tools the module is allowing us to review and draw action plans to remove all root causes, update preventive maintenance plans, proper planning step to move towards predictive maintenance and zero breakdown. It gives effective input to improve user vigilance for use of equipment. It also gives us equipment classification based on age, time, periodic utilization and /cumulative utilization, technological change by Stochastic dynamic programming solutions. By this module we can correctly quantify and assess break-down status and thereby reduce breakdowns significantly. We also can analysis reliability, availability, failures, machine up time, cost analysis for asset utilization like fix capital intensity, cost of repairs, equipment utilization % turn over, etc. This total data of all equipment (organization) are on one platform so we can go through all equipment history with analysis in one look. This platform consists of crew of equipment users, maintenance engineers & managers, so all are connected with each other with their responsibility. The module provides operational backbone and used to provide inputs to management on: 1. Emergency plans to overcome critical equipment areas. 2. To draw maintenance plans and various budgetary provisions with the help of factual data.3.Supplier control of services and spare parts.4.Corporate planning for new equipment, facilities.

IEC 61850 Generic Object-Oriented Substation Event (GOOSE) systems can be designed in a manner that allows testing personnel to easily identify problems and verify system functionality. This paper provides procedures and guidelines for successfully designing and integrating GOOSE protection schemes while keeping the feasibility of initial commissioning and maintenance testing in mind. The paper addresses the following questions: •How can GOOSE systems be designed to support testing? •How can GOOSE systems be designed with expansion in mind? •How should GOOSE signals be incorporated into drawing packages? •What impact do settings modifications have on test validation? •How can test engineers incorporate GOOSE system verifications into intelligent electronic device test procedures?

Commission testing should be designed to assure that the protection system is set and wired to operate correctly for the specific site application. This is especially important with modern micro-processor relays because of the large number of available protection and control elements and configurable logic. Commission testing also establishes a baseline of data to be used to support maintenance testing of all the protection system components of NERC PRC-005. This paper examines how and why the objective of commission testing is different from maintenance testing. Through real examples, the authors highlight the use of system study data and design documents during commission testing to verify proper protection system operation including all enabled protection elements and configured logic. Best practices for commissioning of each NERC PRC-005 protection system component and examples of real world issues found during commissioning are discussed as well as the importance of records keeping relative to PRC-005.

Transmission and Distribution (T&D) Companies tie to several generation plants and other utilities to make an electric transmission grid. Each of the interconnection facilities is governed by the Guidelines that ensure smooth operation of the Power System. However, the Interconnection guidelines are generally limited to equipment at the Point of Interconnection (POI), therefore a thorough investigation of protection schemes may not be carried out by the interconnecting Transmission Operator. North American Electric Reliability Corporation (NERC) PRC-001 requires review of the settings among interconnecting entities to ensure protection coordination. However, it does not cover a thorough review of settings that include oscillography requirements and other protective settings that may be critical to the operation of the interconnection but do not affect the protection coordination. Design standards and protection philosophies vary among generation and transmission operators. This variation in design standards makes it difficult for protection engineers to perform root cause analysis in an emergency event. In addition, testing procedures may be different from one facility to another and smaller interconnection parties may not have experienced staff to conduct maintenance testing or proper startup commissioning. A recent event at one of the combined cycle power plants recently acquired by PG&E is an example that points out some of the inadequacies of the existing interconnection guidelines. Lessons learned by PG&E have resulted in closer co-operation between the Transmission Operator and Generation Operator and is making us re-think about the way we interconnect to other customers. The policies and guidelines that govern third party interconnections are going to play even more important role in the future as the number of Interconnections are likely to increase due to the competitive bidding policy being pursued for new substations by the California Independent System Operator (CAISO) under FERC Rule 1000. As a result of CAISO's policy to bring competition to California electric transmission projects, there will be electric substations designed, owned and operated by a third party that would be surrounded by local utility grid. We as protection engineers need to re-think about how we review/analyze the third party protection schemes. The failure to do so can affect the whole electric grid. Protection Engineers should be more pro-active so that protection schemes and relay settings ensure the reliability of the Power System. Protective relays are the silent sentinels of the electric system, rules and policies need to be in place to allow the protection schemes to safeguard the power system.

Condition-based maintenance (CBM) has been extensively studied. However, the majority of existing CBM research either consider a periodic inspection schedule or a fixed preventive maintenance threshold. While policies with periodic inspections and/or fixed maintenance threshold are easy to implement in practice, they may incur more-than-necessary inspections and induce more failures. In this paper, we develop a sequential CBM policy for systems subject to stochastic degradation. The aim of the proposed policy is to prevent or delay failures and perform maintenance activities just in time. Unlike conventional preventive maintenance that often fixes the inspection interval and the preventive maintenance threshold, both the next inspection time and the corresponding maintenance threshold in this paper are dynamically determined based on the current state of the system. The proposed sequential predictive maintenance policy is particularly important and applicable for general non-homogeneous degradation processes. The proposed model enables optimal scheduling of inspection and preventive maintenance decisions, in order to minimize the long-run maintenance cost rate including inspection, preventive and corrective maintenance costs. The performance of the proposed predictive maintenance policy is evaluated using a simulation-based optimization approach. Frequency of system failures and total maintenance cost rates are computed and compared with a bench mark maintenance policy, a periodic inspection/replacement policy. Our results show that there can be potential savings from the proposed predictive maintenance policy.

The improvement of condition monitoring of critical equipment of complex systems supports the development of predictive maintenance planning. The main goal of predictive maintenance is to understand how the component degradation is affecting the performance of equipment. Based on performance degradation, the maintenance planner defines the necessity for intervention on the equipment. For complex systems, the monitored operational parameters may be used to support predictive maintenance decision-making. The combination of the parameters registered during operational campaign can be used to define the normal or abnormal equipment performance. The present paper presents a reliability-based methodology to support decision-making regarding operational performance of equipment. Based on FMEA analysis, the critical components for equipment performance are defined. The monitoring equipment is analyzed aiming at defining the registered parameters that can be used to evaluate critical components degradation associated to specific failure modes. In case of absence of monitoring parameters, an inspection route is proposed to be executed by maintainers. The main goal of the route is to use sensorial capabilities of human being to evaluate possible degradation of critical components that are not monitored by the control system. The findings of that inspection route may be used to support the evaluation of any abnormal component operational condition that may affect equipment performance. In order to combine the parameters registers and sensorial inspection results to diagnose degradation in equipment performance a Neural Network based on Radial Basis Function is developed. For the definition of normal or abnormal operational condition the decision-maker preference is modeled with utility functions that incorporate attitude toward risk. The proposed model is used to analyze the operational condition of a hydro generator. The parameters of temperature (from bearings and heat exchangers) and shaft vibration are used to characterize hydro generator operation. For other critical equipment a sensorial inspection route is proposed using mainly temperature information to support components degradation analysis. The registered and sensorial data representing one operational month are used to train the neural network regarding normal and abnormal equipment condition. After training, the Neural Network was able to detect abnormal operational condition. The use of utility functions incorporating operator attitude towards risk indicates that the definition of abnormal performance is strongly affected by operator's preference.

The condition of no fault found (NFF) has been accepted by engineers and operators for many years. Whilst there are known general reasons for NFF one of the areas that is overlooked is the importance of the test equipment, whether built-in test equipment or automatic test equipment, and specifically the effectiveness of the test. How much of a system or component is actually being test by the test equipment? This paper explores the system or component fault coverage effectiveness and the impact on NFF. In doing so a module is proposed to establish the relationship between NFF and test coverage effectiveness for different reliabilities. As the component or system reliability improves along with the test effectiveness the percentage of NFF occurrences decreases. Another consideration is the assumed number of random failures that the design engineers include during the development phases. This is usually an underestimate and the combination of this and the ineffective fault coverage have a negative impact on the operational availability.

Interactive Computer Based Instruction (CBI) systems involve teaching strategies to facilitate greater response opportunities during training in an effort to improve learner performance. The current study investigated the effect of online staff training videos with and without overt response requirements on posttest and maintenance test scores across six block-randomized instructional modules for four employees of a university located in the southeastern region of the United States. The overt response consisted of multiple-choice questions administered throughout select teaching modules using an alternating treatment design. Findings suggest that learning occurred as a result of the CBI training; however, the effectiveness of the overt response system varied across individuals, with no discernible differentiation between learning gains associated with response requirements. Other areas of research for expanding the efficacy of CBI and overt response systems are highlighted.

This paper presents the results of applying the optimal model of the concept of maintenance of modern radio-relay equipment (RRE). The model, is based on condition based preventive maintenancewith the control of the level of reliability, and uses a number of positive structural and technological capabilities of the machine in order to decrease overall maintenance costswhile maintaning the achieved level of the required device reliability. Introduction The aim of this paper is to review the maintenance models, with an emphasis on preventive maintenance, in order to identify the best RRE model maintenance and set up a proper maintenance organization. For the application of a model of maintenance, one must be familiar with construction-technological features and capabilities of the device which provide its reliability and maintainability. The ultimate goal of this research is to choose and establish an optimal maintenance model which will enable controlled monitoring of device reliability in order to fully utilize resources. Types of Preventive Maintenance Two types of preventive maintenance have been presented including: traditional planned maintenance and condition based maintenance. Condition based maintenance is a type of preventive maintenance based on a periodic or continuous control of devices in use. Based on the results of the control, decisions are made on the necessary time and extent of planned activities. Condition based maintenance, due to constant control during operation, allows full utilization of device modulecomponents , which makes it optimal compared to traditional preventive maintenance. Methods of condition based maintenance. There are two types of condition based maintenance: one with the parameter control and the other with the reliability control.The choice of an appropriate method is done based on the algorithm in Figure 3. Considering the requirements that must be met when choosing the model of condition based maintenance and the algorithm for model selection, a model of condition based maintenance is chosen with the control of the device reliability and component modules. The fact that the intensity of the failure of devices and modules is constant over the life of the device is a critical factor in choosing a model of condition based maintenance which will be used in further research. The model will enable the optimal maintenance of devices with maximum reliability and minimum maintenance costs. Condition based maintenance with the control of the level of reliability In models of condition based maintenance with the control of the level of reliability, a reliability level is a criterion of technical condition and expressed by reliability. The indication of the reliabilityis the parameter – failure intensity. In applying the model, there is another parameter used- allowed reliability level. The permitted level of reliability is calculated for each component separately and for the entire device. In this maintenance model, during the lifetime of the device, the actual level of reliability is constantly compared with the allowed value of the reliability of the device or module, as shown in the algorithm in Figure 4. The application of this maintenance model requires constant collection of operational data about the reliability of devices and modules during their lifetime. RRE characteristics from the aspect of the maintenance model In the selection phase of the maintenance model, it is stated that RRE must meet certain requirements such as: unit design is characterized by a high degree of technologicality and is based on the serial modular principle; the device operates within the mobile system in which the operation of the device is controlled by a computer system, and the device is pre-tested for the defectafion of device correctness. From the technological point of view, it was assumed that there is equipment for all levels of maintenance, trained personnel, and required technological procedures for all levels of maintenance. The application of the condition based maintenance with the control of the level of reliability and the results of the application In accordance with the defined assumptions,the maintenance model was applied. The RRE operation is controlled within the mobile system,using a compute with, appropriate software. . The communication ofthe computer with RREgives all the relevant information about the unit. A part of the maintenance data is entered manually into the appropriate application software. Based on the collected data, the computer calculates all relevant parameters for the implementation of the model maintenance, numerically and graphically. Figure 7 shows the algorithm of the optimal model of condition based maintenance of RRE with the control of the reliability level. The results of applying the optimal maintenance model are also shown. Based on the activities during the research and on the application of the maintenance model, it can be seen that the highest maintenance costs are directed to the replacement of component modules. The optimality of the condition based maintenance model allows the use of modules after the expiry of resources, or up to failure,without disrupting the functions of the device. Conclusion The conducted research shows that the assumed RRE maintenance model provides quality and cost-effective RRE maintenance of the latest generation with the use of existing resources and RRS units in which they are incorporated. The research also shows that the assumed model of condition based maintenance with the control of the level of reliability enables: - full use of structural and technological characteristics of the device as a function of efficient and cost-effective equipment maintenance, - better planning of preventive maintenance, - involvement of personnel and experts from the lowest level of maintenance and professional raising of the basic maintenance level, - availability of information on resources, equipment and maintenance, to higher levels of maintenance and decision-making structures, - uniform and organized data collection from service and device life and RRS, - reduction of maintenance costs to a minimum, - changing the constituent moduleswith the highest maintenance costs, upon failure and not upon the expiry of resources, provided that the module performs its functional purpose and does not violate the reliability of the device, - an option of applying the maintenance model to other devices in RRS.

INTRODUCTION: Decision-making on medical equipment management is a daily task for clinical engineers, but it may prove difficult to easily extract relevant information from the large amount of data from computerized maintenance management systems. This article describes a simple method of medical equipment classification based on corrective maintenance indicators. METHODS: Three indicators were calculated based on the number of events, duration and cost of corrective maintenance. Three classes were defined according to the indicator values of different equipment ages: class A for 0-4 years, class B for 5-9 years, and class C for equipment older than 10 years. The method was applied to 2,134 pieces of equipment from the Health Service system of the University of Campinas. RESULTS: From the total, 51.7% of the equipment were classified as C, 4.2% as B and 44.1% as A. The infusion pump for general use was the type of equipment of which most units were in the C class (84.7%), even though almost 50% of them were acquired within less than 9 years, and would thus be expected to be classified as A and B. Among the pumps in class C, 39.5% were from a single manufacturer, although the equipments were acquired recently. CONCLUSION: The developed classification may be an important tool for raising alerts about equipment more prone to maintenance problems, as well as for identification of equipments with acceptable maintenance history, supporting decision-making on equipment replacement.