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Number of results: 65
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Abstract

The paper presents a heuristic approach to the problem of analog circuit diagnosis. Different optimization techniques in the field of test point selection are discussed. Two new algorithms: SALTO and COSMO have been introduced. Both searching procedures have been implemented in a form of the expert system in PROLOG language. The proposed methodologies have been exemplified on benchmark circuits. The obtained results have been compared to the others achieved by different approaches in the field and the benefits of the proposed methodology have been emphasized. The inference engine of the heuristic algorithms has been presented and the expert system knowledge-base construction discussed.

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Authors and Affiliations

Andrzej Pułka
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Abstract

This paper is devoted to measuring the continuous diagnosis capability of a system. A key metric and its calculation models are proposed enabling us to measure the continuous diagnosis capability of a system directly without establishing and searching the sequential fault tree (SFT) of the system. At first a description of a D matrix is given and its metric is defined to determine the weakness of a continuous diagnosis. Then based on the definition of a sequential fault combination, a sequential fault tree (SFT) is defined with its establishment process summarized. A key SFT metric is established to measure the continuous diagnosis capability of a system. Two basic types of dependency graphical models (DGMs) and one combination type of DGM are selected for characteristics analysis and establishment of metric calculation models. Finally, both the SFT searching method and direct calculation method are applied to two designs of one type of an auxiliary navigation equipment, which shows the high efficiency of the direct calculation method.

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Authors and Affiliations

Jun-You Shi
Xie-Gui Lin
Meng Shi
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Abstract

Hypertension constitutes one of the most common diseases leading patients to the Outpatient Departments. Idiopathic hypertension is the prevailing type, but on the other hand, the possible presence of clinical entities responsible for the development of secondary hypertension should never be underestimated. We retrospectively studied 447 subjects aged between 20 and 84 years old and diagnosed with hypertension, who were thoroughly evaluated for secondary hypertension. Our analysis demonstrated that 35 out of the 447 subjects were fi nally diagnosed with secondary hypertension, representing a relative frequency of 7.8%. Most common causes of secondary hypertension identifi ed in our study group were: glucocorticoid intake (n = 14), obesity hypoventilation syndrome (n = 6), obstructive sleep apnea (n = 2) and preeclamspia (n = 2). Several other causes are also reported. Our study, conducted in a single center in Northern Greece, confi rms previous reports concerning the prevalence of secondary hypertension among Greek patients, shedding light on potential pathophysiologic mechanisms. In conclusion, a high proportion of hypertensive individuals still feature have an underlying cause, thus, diagnostic work-up should be thorough and exhaustive, in order the correct diagnosis to be made and the targeted treatment to be initiated.

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Authors and Affiliations

Theodoros Michailidis
Dimitrios Patoulias
Michalis Charalampidis
Petros Keryttopoulos
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Abstract

An elaborate study executed in the direction of exploring energy saving potential shows that more than 20% of electrical energy used in industry is used for pump systems. Experts calculate that more than 30% of this energy can be saved by improving control and diagnosis for pump systems. Unfortunately, the application ratio of such system is small and consequently a large demand for such technological advanced systems can still be observed in the pump industry. Because of this reason and still growing demand of saving energy in industry, two Universities in Germany and Switzerland together with leading German pump manufacturer decided to join their knowledge and skill to work on the project called "Smart Pump". This paper presents one of the first results of this project, which goal is the development of future control methods and diagnosis systems for intelligent pumps.

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Authors and Affiliations

Stefan Kleinmann
Anna Dąbrowska
Agathe Koller-Hodac
Domenico Leonardo
Ralf Stetter
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Abstract

The world population, and thus the need for food, is increasing every day. This leads to the ultimate question of how to increase food production with limited time and scarce land. Another obstacle to meet the food demand includes the stresses a plant goes through. These may be abiotic or biotic, but the majority are biotic, i.e., plant diseases. The major challenge is to mitigate plant diseases efficiently, more quickly and with less manpower. Recently, artificial intelligence has turned to new frontiers in smart agricultural science. One novel approach in plant science is to detect and diagnose plant disease through deep learning and hyperspectral imaging. This smart technique is very advantageous for monitoring large acres of field where the availability of manpower is a major drawback. Early identification of plant diseases can be achieved through machine learning approaches. Advanced machine learning not only detects diseases but also helps to discover gene regulatory networks and select the genomic sequence to develop resistance in crop species and to mark pathogen effectors. In this review, new advancements in plant science through machine learning approaches have been discussed.
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Authors and Affiliations

Siddhartha Das
1
ORCID: ORCID
Sudeepta Pattanayak
2
ORCID: ORCID
Prateek Ranjan Behera
3

  1. Department of Plant Pathology, M.S. Swaminathan School of Agriculture, Centurion University of Technology and Management, Paralakhemundi, Odisha, India
  2. Division of Plant Pathology, ICAR – Indian Agricultural Research Institute, New Delhi, India
  3. Department of Plant Pathology, College of Agriculture, Odisha University of Agriculture and Technology, Bhubaneswar, India
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Abstract

High-Temperature Proton-Exchange Membrane Fuel Cells (HT-PEMFCs) are a candidate for electrical energy supply devices in more and more applications. Most notably in the aeronautic industry. Before any use, an HT-PEMFC is preheated and after that supplied with its active gases. Only at this state, the diagnostics can be performed. A method of testing not requiring a complete start-up would be beneficial for many reasons. This article describes an extended version of the charging and discharging diagnostic method of HT-PEMFCs with no active gases. This extended approach is named “Test Without Active Gases” (TWAG). This paper presents original research on the influence of nitrogen temperature and pressure on the HT-PEMFC response to charging and discharging. A lumped-element model of an HT-PEMFC is also presented. A numerical result of using this model to recreate an experimentally obtained curve is also presented.
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Authors and Affiliations

Wojciech Rosiński
1
ORCID: ORCID
Christophe Turpin
2
ORCID: ORCID
Andrzej Wilk
1
ORCID: ORCID

  1. Faculty of Electrical and Control Engineering, Gdansk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdansk, Poland
  2. Team GENESYS, Laboratioire LAPLACE, 118 Rte de Narbonne, 31077 Toulouse, France
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Abstract

The attenuating properties of biological tissue are of great importance in ultrasonic medical imaging. Investigations performed in vitro and in vivo showed the correlation between pathological changes in the tissue and variation of the attenuation coefficient. In order to estimate the attenuation we have used the downshift of mean frequency (fm) of the interrogating ultrasonic pulse propagating in the medium. To determine the fm along the propagation path we have applied the fm estimator (I/Q algorithm adopted from the Doppler mean frequency estimation technique). The mean-frequency shift trend was calculated using Single Spectrum Analysis. Next, the trends were converted into attenuation coefficient distributions and finally the parametric images were computed. The RF data were collected in simulations and experiments applying the synthetic aperture (SA) transmit-receiving scheme. In measurements the ultrasonic scanner enabling a full control of the transmission and reception was used. The resolution and accuracy of the method was verified using tissue mimicking phantom with uniform echogenicity but varying attenuation coefficient.

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Authors and Affiliations

Ziemowit Klimonda
Andrzej Nowicki
Jerzy Litniewski
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Abstract

In the paper modeling of main inductances for mathematical models of induction motors is applied to study the effects caused by a rotor eccentricity and saturation effects. All three possible types of eccentricity: static, dynamic and mixed are modeled. The most important parameters describing rotor eccentricity include self and mutual inductances of the windings. The structural changes of the permeance function as a result of eccentricity appearance and the Fourier spectra of inductances in occurrence of saturation for each case are determined in the paper. The presented algorithm can be used for the diagnostically specialized models of induction motors.

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Authors and Affiliations

Tomasz Węgiel
Konrad Weinreb
Maciej Sułowicz
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Abstract

In this study, a preliminary evaluation was made of the applicability ofthe signalsof the cutting forces, vibration and acoustic emission in

diagnosis of the hardness and microstructure of ausferritic ductile iron and tool edge wear rate during its machining. Tests were performed

on pearlitic-ferritic ductile iron and on three types of ausferritic ductile iron obtained by austempering at 400, 370 and 320⁰C for 180

minutes. Signals of the cutting forces (F), vibration (V) and acoustic emission (AE) were registered while milling each type of the cast iron

with a milling cutter at different degrees of wear. Based on individual signals from all the sensors, numerous measures were determined

such as e.g. the average or maximum signal value. It was found that different measures from all the sensors tested depended on the

microstructure and hardness of the examined material, and on the tool condition. Knowing hardness of the material and the cutting tool

edge condition, it is possible to determine the structure of the material .Simultaneous diagnosis of microstructure, hardness, and the tool

condition is probably feasible, but it would require the application of a diagnostic strategy based on the integration of numerous measures,

e.g. using neural networks.

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Authors and Affiliations

D. Myszka
S. Bombiński
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Abstract

Anaphylaxis is an increasing problem in public health. Th e food allergens (mainly milk, eggs, and peanuts) are the most frequent cause of anaphylaxis in children and youth. In order to defi ne the cause of anaphylaxis, skin tests, the determination of the concentration of specifi c IgE in the blood and basophil activation test are conducted. In vitro tests are preferred due to the risk of allergic response during in vivo tests. Component-resolved diagnosis (CRD) is an additional tool in allergology, recommended in the third level of diagnostics when there are diagnostic doubts aft er the above mentioned tests have been carried out. The paper presents 3 cases of patients with anaphylactic response, and the application of CRD in these patients helped in planning the treatment. Patient 1 is a 4-year-old boy with diagnosed atopic dermatitis and bronchial asthma reported an anaphylactic shock at the age of seven months caused by cow’s milk and the exacerbation of bronchial asthma aft er eating some fruit. Patient 2 is a 35-year-old woman who has had anaphylactic shock three times: in June 2015, 2016, and 2017 and associates these episodes with the consumption of dumplings with a caramel, bun, and the last episode took place during physical exertion few hours aft er eating waffl e. Patient 3 is a 26-year-old man with one-time loss of consciousness after eating mixed nuts and drinking beer. CRD off ers the possibility to conduct a detailed diagnostic evaluation of patients with a history of anaphylactic reaction.

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Authors and Affiliations

Małgorzata Bulanda
Magdalena Leśniak
Judyta Szałkowska
Weronika Madej
Agata Wojtyna
Maria Czarnobilska
Daniel Bulanda
Ewa Czarnobilska
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Abstract

Analog circuits need more effective fault diagnosis methods. In this study, the fault diagnosis method of analog circuits was studied. The fault feature vectors were extracted by a wavelet transform and then classified by a generalized regression neural network (GRNN). In order to improve the classification performance, a wolf pack algorithm (WPA) was used to optimize the GRNN, and a WPA-GRNN diagnosis algorithm was obtained. Then a simulation experiment was carried out taking a Sallen–Key bandpass filter as an example. It was found from the experimental results that the WPA could achieve the preset accuracy in the eighth iteration and had a good optimization effect. In the comparison between the GRNN, genetic algorithm (GA)-GRNN and WPA-GRNN, the WPA-GRNN had the highest diagnostic accuracy, and moreover it had high accuracy in diagnosing a single fault than multiple faults, short training time, smaller error, and an average accuracy rate of 91%. The experimental results prove the effectiveness of the WPA-GRNN in fault diagnosis of analog circuits, which can make some contributions to the further development of the fault diagnosis of analog circuits.

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Authors and Affiliations

Hui Wang
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Abstract

Power big data contains a lot of information related to equipment fault. The analysis and processing of power big data can realize fault diagnosis. This study mainly analyzed the application of association rules in power big data processing. Firstly, the association rules and the Apriori algorithm were introduced. Then, aiming at the shortage of the Apriori algorithm, an IM-Apriori algorithm was designed, and a simulation experiment was carried out. The results showed that the IM-Apriori algorithm had a significant advantage over the Apriori algorithm in the running time. When the number of transactions was 100 000, the running of the IM-Apriori algorithm was 38.42% faster than that of the Apriori algorithm. The IM-Apriori algorithm was little affected by the value of supportmin. Compared with the Extreme Learning Machine (ELM), the IM-Apriori algorithm had better accuracy. The experimental results show the effectiveness of the IM-Apriori algorithm in fault diagnosis, and it can be further promoted and applied in power grid equipment.

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Authors and Affiliations

Jianguo Qian
Bingquan Zhu
Ying Li
Zhengchai Shi
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Abstract

The presence of an open-circuit fault subjects a three-phase induction motor to severely unbalanced voltages that may damage the stator windings consecutively causing total shutdown of systems. Unplanned downtime is very costly. Therefore, fault diagnosis is essential for making a predictive plan for maintenance and saving the required time and cost. This paper presents a model-based diagnosis technique for diagnosing an open-circuit fault in any phase of a three-phase induction motor. The proposed strategy requires only current signals from the faulty machine to compare them with the healthy currents from an induction motor model. Then the errors of comparison are used as an objective function for a genetic algorithm that estimates the parameters of a healthy model, which they employed to identify and localize the fault. The simulation results illustrate the behaviours of basic parameters (stator and rotor resistances, self-inductances, and mutual inductance) and the number of stator winding turn parameters with respect to the location of an open-circuit fault. The results confirm that the number of stator winding turns are the useful parameters and can be utilized as an identifier for an open-circuit fault. The originality of this work is in extracting fault diagnosis features from the variations of the number of stator winding turns.

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Authors and Affiliations

Raya A.K. Aswad
Bassim M.H. Jassim
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Abstract

This paper is focused on multiple soft fault diagnosis of linear time-invariant analog circuits and brings a method that achieves all objectives of the fault diagnosis: detection, location, and identification. The method is based on a diagnostic test arranged in the transient state, which requires one node accessible for excitation and two nodes accessible for measurement. The circuit is specified by two transmittances which express the Laplace transform of the output voltages in terms of the Laplace transform of the input voltage. Each of these relationships is used to create an overdetermined system of nonlinear algebraic equations with the circuit parameters as the unknown variables. An iterative method is developed to solve these equations. Some virtual solutions can be eliminated comparing the results obtained using both transmittances. Three examples are provided where laboratory or numerical experiments reveal effectiveness of the proposed method.
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Authors and Affiliations

Michał Tadeusiewicz
1
Marek Ossowski
1
Marek Korzybski
1

  1. Lodz University of Technology, Department of Electrical, Electronic, Computer and Control Engineering, Lodz, Poland
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Abstract

Atopic dermatitis (AD) is a chronic, recurrent inflammatory dermatosis. The most characteristic symptoms of the disease include itch, eczematous eruptions and excessive dryness of the skin. Elderly patients with AD represent a poorly characterized population because the physiological ageing, possible comorbidity and polypharmacy modify the clinical presentation typically observed in the younger age groups. The aim of the study is to comprehensively assess the clinical characteristics of elderly patients (>60 years old) with AD. Data were collected from 26 AD patients treated in the Department of Derma-tology of the University Hospital in Krakow. Late-onset AD with generalized/prurigo lesions was the most predominant phenotype. Skin biopsy was required in 15 (58%) patients in the differential diagnosis process. Allergic rhinitis, a positive family history of atopy and xerosis were associated with a higher number of hospitalizations during the year prior to the last admission (p = 0.034, p = 0.046 and p = 0.036, respectively). Xerosis was more prevalent among subjects with polypharmacy (p = 0.046) and higher serum total IgE concentration (p = 0.048). AD in elderly patients is a new phenotype of the disease that requires careful differential diagnosis. Aged patients with an individual or family history of atopy, due to the increased incidence of severe exacerbations of AD, may benefit from the introduction of proactive therapy.
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Authors and Affiliations

Andrzej Kazimierz Jaworek
1
Przemysław Hałubiec
2
ORCID: ORCID
Natalia Kachnic
3
Alicja Podolska
3
Julia Radzikowska
3
Arletta Kozłowska
2
Anna Wojas-Pelc
1

  1. Department of Dermatology, Jagiellonian University Medical College, Kraków, Poland
  2. University Hospital, Kraków, Poland
  3. Student Scientific Group of Dermatology, Jagiellonian University Medical College, Kraków, Poland
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Abstract

Incidence of colonic atresia in living infants ranges from 1:5,000 to 1:60,000 (average 1:20,000). It constitutes 1.8 to 15% of all cases of atresia of the gastrointestinal tract. In 58.56–75% of all cases is right-sided. We aim, through the presentation of two cases of colonic atresia which we encountered and after systematic research of the current literature, at addressing three major issues: diagnostic approach, operative strategy and management of the prognostic parameters of the colonic atresia. The common parameter in these two cases was the early diagnosis, which played a significant role in the uncomplicated postoperative course. The first case was a type I sigmoid atresia. Contrast’s escape during contrast enema examination due to accidental rupture of the distal part of the colon led to diagnosis. Side-to-side anastomosis, restoration of the rupture and a central loop sigmoidostomy were urgently performed. The second case was a type III atresia at the level of the ascending colon, which was early diagnosed via pregenital ultrasonography, in which colonic dilation was depicted. Restoration of the intestinal continuity early after birth was performed at a time. In conclusion, we believe that early diagnosis, selection of the appropriate operative strategy and prompt recognition of potential post-operative complications, especially rupture of the anastomosis, contribute to the optimization of the prognosis in patients with colonic atresia.

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Authors and Affiliations

Ioannis Patoulias
Thomas Feidantsis
Charalampos Doitsidis
Magdalini Mitroudi
Maria-Styliani Kalogirou
Dimitrios Patoulias
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Abstract

Finger tapping is one of the standard tests for Parkinson's disease diagnosis performed to assess the motor function of patients' upper limbs. In clinical practice, the assessment of the patient's ability to perform the test is carried out visually and largely depends on the experience of clinicians. This article presents the results of research devoted to the objectification of this test. The methodology was based on the proposed measurement method consisting in frame processing of the video stream recorded during the test to determine the time series representing the distance between the index finger and the thumb. Analysis of the resulting signals was carried out in order to determine the characteristic features that were then used in the process of distinguishing patients with Parkinson's disease from healthy cases using methods of machine learning. The research was conducted with the participation of 21 patients with Parkinson's disease and 21 healthy subjects. The results indicate that it is possible to obtain the sensitivity and specificity of the proposed method at the level of approx. 80 %. However, the patients were in the so-called ON phase when symptoms are reduced due to medication, which was a much greater challenge compared to analyzing signals with clearly visible symptoms as reported in related works.
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Authors and Affiliations

Jacek Jakubowski
1
ORCID: ORCID
Anna Potulska-Chromik
2
ORCID: ORCID
Jolanta Chmielińska
1
ORCID: ORCID
Monika Nojszewska
2
ORCID: ORCID
Anna Kostera-Pruszczyk
2
ORCID: ORCID

  1. Faculty of Electronics, Military University of Technology, Warsaw, Poland
  2. Department of Neurology, Medical University of Warsaw, Warsaw, Poland
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Abstract

The paper presents the most frequently encountered types and mechanism of damage of turbines' flow elements. The methods used nowadays for diagnosis of the damage are presented. A new possibility of localisation of damaged areas of turbine blades based upon the analysis of isotherm layout is proposed.
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Authors and Affiliations

Jerzy Madej
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Abstract

The paper is aimed at presenting a study of the main limitations and problems influencing the robustness of diagnostic algorithms used in diagnostics of complex chemical processes and to present the selected exemplary solutions of how to increase it. The five major problems were identified in the study. They are associated with: uncertainties of fault detection and reasoning, changes of the diagnosed process structure, delays of fault symptoms formation and multiple faults. A brief description and exemplary solutions allowing increase of the robustness of diagnostic algorithms were given. Proposed methods were selected keeping in mind applicability for the on-line monitoring and diagnostics of complex chemical processes.
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Authors and Affiliations

Jan Maciej Kościelny
Michał Syfert
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Abstract

A new soft-fault diagnosis approach for analog circuits with parameter tolerance is proposed in this paper. The approach uses the fuzzy nonlinear programming (FNLP) concept to diagnose an analog circuit under test quantitatively. Node-voltage incremental equations, as constraints of FNLP equation, are built based on the sensitivity analysis. Through evaluating the parameters deviations from the solution of the FNLP equation, it enables us to state whether the actual parameters are within tolerance ranges or some components are faulty. Examples illustrate the proposed approach and show its effectiveness.

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Authors and Affiliations

Wei Zhang
Longfu Zhou
Yibing Shi
Chengti Huang
Yanjun Li
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Abstract

This paper is devoted to multiple soft fault diagnosis of analog nonlinear circuits. A two-stage algorithm is offered enabling us to locate the faulty circuit components and evaluate their values, considering the component tolerances. At first a preliminary diagnostic procedure is performed, under the assumption that the non-faulty components have nominal values, leading to approximate and tentative results. Then, they are corrected, taking into account the fact that the non-faulty components can assume arbitrary values within their tolerance ranges. This stage of the algorithm is carried out using the linear programming method. As a result some ranges are obtained including possible values of the faulty components. The proposed approach is illustrated with two numerical examples.

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Authors and Affiliations

Michał Tadeusiewicz
Stanisław Hałgas
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Abstract

Current methods of fault diagnosis for the grounding grid using DC or AC are limited in accuracy and cannot be used to identify the locations of the faults. In this study, a new method of fault diagnosis for substation grounding grids is proposed using a square-wave. A frequency model of the grounding system is constructed by analyzing the frequency characteristics of the soil and the grounding conductors into which two different frequency square-wave sources are injected. By analyzing and comparing the corresponding information of the surface potentials of the output signals, the faults of the grounding grid can be diagnosed and located. Our method is verified by software simulation, scale model experiments and field experiments.

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Authors and Affiliations

Peng-He Zhang
Jun-Jia He
Dan-Dan Zhang
Lan-Min Wu
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Abstract

This paper presents a Kalman filter based method for diagnosing both parametric and catastrophic faults in analog circuits. Two major innovations are presented, i.e., the Kalman filter based technique, which can significantly improve the efficiency of diagnosing a fault through an iterative structure, and the Shannon entropy to mitigate the influence of component tolerance. Both these concepts help to achieve higher performance and lower testing cost while maintaining the circuit.s functionality. Our simulations demonstrate that using the Kalman filter based technique leads to good results of fault detection and fault location of analog circuits. Meanwhile, the parasitics, as a result of enhancing accessibility by adding test points, are reduced to minimum, that is, the data used for diagnosis is directly obtained from the system primary output pins in our method. The simulations also show that decision boundaries among faulty circuits have small variations over a wide range of noise-immunity requirements. In addition, experimental results show that the proposed method is superior to the test method based on the subband decomposition combined with coherence function, arisen recently.

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Authors and Affiliations

Xifeng Li Li
Yongle Xie
Dongjie Bi
Yongcai Ao
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Abstract

The paper deals with fault diagnosis of nonlinear analogue integrated circuits. Soft spot short defects are analysed taking into account variations of the circuit parameters due to physical imperfections as well as self-heating of the chip. A method enabling to detect, locate and estimate the value of a spot defect has been developed. For this purpose an appropriate objective function was minimized using an optimization procedure based on the Fibonacci method. The proposed approach exploits DC measurements in the test phase, performed at a limited number of accessible points. For illustration three numerical examples are given.

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Authors and Affiliations

Michał Tadeusiewicz
Stanisław Hałgas

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