Diagnostic Signal Informativeness Increase

Modern requirements for the operation of cars lead to the need to improve the efficiency of their maintenance. Diagnosis as an element of the maintenance process allows you to provide information about the technical condition of a particular element, which allows you to respond in a timely manner to the technical condition change of a diagnostic object with minimal resources. In this paper, we consider the way improving the diagnostic signal quality. It is known that a diagnostic signal must meet several requirements. The most important requirement is informativeness, which shows the decrease of uncertainty about the technical condition of an object, represented by a priori entropy after information application from this diagnostic signal, measured during the diagnosis. There are the methods for a diagnostic signal conversion, which allow to get rid of the noise entering it to a different degree or present it in such a way to facilitate the signal analysis process. Three methods are considered in the work: direct spectrum obtaining, signal envelope spectrum obtaining, and adaptive filtering. The analysis of these methods led to the conclusion that adaptive filtering has the greatest efficiency potential. We have proposed the method that is based on adaptive filtering, but with additional operations. In the course of the diagnostic signal studies and the adaptive filtering algorithm, we found that it is possible to set the function to be detected as a variable, as well as several parameters that affect the result quality. Based on this, a new method for a useful signal extraction was proposed. The results of the work were checked on a signal simulating a car gearbox signal. The results show that the method allows you to obtain the necessary knowledge about a defect, which can be used in the diagnosis. The developed method allows to increase the information content of the diagnostic signal by suppressing its other components. The results of the proposed method correlate with the results of other methods for general cases, i.e., when the ratio of the useful signal to noise is such that high sensitivity of the method is not required to identify the useful signal.

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Improving the precision of the selection of piecewise linear useful signal component under conditions of a priori uncertainty

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1029/1/012102 ◽

2021 ◽

Vol 1029 ◽

pp. 012102

Author(s):

I S Shrayfel ◽

V I Marchuk ◽

A B Mihailov ◽

I M Malcev ◽

A V Fisunov

Keyword(s):

Piecewise Linear ◽

A Priori ◽

Signal Component ◽

Useful Signal ◽

A Priori Uncertainty ◽

Selection Of

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A qualitative analysis of the Wikipedia N-Substate Algorithm's Enhancement Terms

Journal of Computer-Assisted Linguistic Research ◽

10.4995/jclr.2019.11159 ◽

2019 ◽

Vol 3 (1) ◽

pp. 67

Author(s):

Kyle Goslin ◽

Markus Hofmann

Keyword(s):

Qualitative Analysis ◽

A Priori ◽

Sole Source ◽

Human Interaction ◽

A Priori Knowledge ◽

Search Query ◽

Analysis Process ◽

Automatic Search ◽

The Individual ◽

Priori Knowledge

<p>Automatic Search Query Enhancement (ASQE) is the process of modifying a user submitted search query and identifying terms that can be added or removed to enhance the relevance of documents retrieved from a search engine. ASQE differs from other enhancement approaches as no human interaction is required. ASQE algorithms typically rely on a source of a priori knowledge to aid the process of identifying relevant enhancement terms. This paper describes the results of a qualitative analysis of the enhancement terms generated by the Wikipedia NSubstate Algorithm (WNSSA) for ASQE. The WNSSA utilises Wikipedia as the sole source of a priori knowledge during the query enhancement process. As each Wikipedia article typically represents a single topic, during the enhancement process of the WNSSA, a mapping is performed between the user’s original search query and Wikipedia articles relevant to the query. If this mapping is performed correctly, a collection of potentially relevant terms and acronyms are accessible for ASQE. This paper reviews the results of a qualitative analysis process performed for the individual enhancement term generated for each of the 50 test topics from the TREC-9 Web Topic collection. The contributions of this paper include: (a) a qualitative analysis of generated WNSSA search query enhancement terms and (b) an analysis of the concepts represented in the TREC-9 Web Topics, detailing interpretation issues during query-to-Wikipedia article mapping performed by the WNSSA.</p>

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ОСОБЛИВОСТІ АВТОМАТИЗАЦІЇ КОНТРОЛЮ ТЕХНІЧНОГО СТАНУ МОРСЬКОГО ТРАНСПОРТУ

World Science ◽

10.31435/rsglobal_ws/31032019/6400 ◽

2019 ◽

Vol 1 (3(43)) ◽

pp. 19-25

Author(s):

Коломієць Оксана Михайлівна

Keyword(s):

Water Transport ◽

A Priori ◽

Technical Condition ◽

Software Implementation ◽

Effective Strategy ◽

Kutta Method ◽

A Priori Information ◽

Automated Control ◽

Runge Kutta Method ◽

Priori Information

The article analyzes the principles of automation of the control of the technical condition of water transport vehicles, which has been determined: the principle of coherence; the principle of integration; Principle of independence of execution.It is determined that the most effective strategy is to improve the methods of automated control of the technical condition of water transport vehicles, which, unlike existing ones, is based on Markov processes, the Runge-Kutta method of numerical solution of the system of Kolmogorov differential equations and a priori information about the intensity of transitions from state to state.Using the software implementation of the model significantly improves performance due to the ergonomics of the interface and reduced number of operations.

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INTEGRATED LOGISTICAL SUPPORT OF AERONAUTICAL EQUIPMENT BASED ON PROBABILITY-GUARANTEEING ESTIMATION OF THE RISKS, ASSOCIATED WITH THE AIRCRAFT TECHNICAL CONDITION

Vestnik komp iuternykh i informatsionnykh tekhnologii ◽

10.14489/vkit.2021.08.pp.029-037 ◽

2021 ◽

pp. 29-37

Author(s):

V. N. Evdokimenkov ◽

R. V. Kim ◽

M. N. Krasilshchikov ◽

N. I. Selvesyuk

Keyword(s):

Residual Life ◽

A Priori ◽

Estimation Method ◽

Integral Characteristic ◽

Technical Condition ◽

Physical Parameters ◽

Additional Element ◽

Flight Data ◽

Integrated Logistical Support ◽

Information Database

In this article, we analyze the modern concepts in the field of the aeronautical equipment integrated logistical support (ILS). The key element of the traditional logistical support system under consideration is the data on detected failures and malfunctions, recorded in the air flight and maintenance log (AFML), chart-orders, non-routine write-ups and accumulated within the structure of the logistic support analysis database. We propose a method for expanding the ILS capabilities by means of including of an additional element, called the flight information database, in the logistics center structure, along with the traditional database for analyzing the logistical support. This database is constantly growing during the aircraft operation. It also contains the values of the parameters recorded by the standard onboard flight data recorder, which reflect the state of the onboard systems. The inclusion of a flight information database into the structure of the logistical support center makes it possible to implement the probability-guaranteeing estimation method in respect of the risks, associated with the aircraft technical condition, for benefit of the integrated logistical support. The proposed method uses an inverse probabilistic criterion (quantile) as an integral characteristic of the aircraft systems technical condition. This is fully consistent with modern approaches to organizing condition-based maintenance. Among these approaches, the data-driven methodology (DDM) has the greatest potential and practical efficiency. The applicative value of the described method is in the fact that its implementation needs neither a priori information about the principles of the maintained equipment operation, nor information about the functioning principles of the on-board controller network, which is used to control the equipment physical parameters. In this article, we also present the accuracy estimates of forecasting the residual life of an aircraft gas turbine engine, using the proposed method. These estimates are based on the actual flight data presented in the National Aeronautics and Space Administration (NASA) repository.

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Assessing and Extending Track Quality Index for Novel Measurement Techniques in Railway Systems

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120923661 ◽

2020 ◽

Vol 2674 (8) ◽

pp. 24-36

Author(s):

Tzu-Hao Yan ◽

Francesco Corman

Keyword(s):

Quality Index ◽

Measurement Techniques ◽

High Sensitivity ◽

Single Type ◽

Railway Systems ◽

The Status ◽

Sensitivity Data ◽

Maintenance Process ◽

Track Status ◽

Track Quality

A systematic maintenance process is essential to keeping railway systems safe and reliable. However, performing such maintenance is costly and often results in system disruption. There is a tradeoff between system safety and budgetary constraints; understanding the condition of the track infrastructure is essential to find the balance between needs and costs for decisions about when to perform maintenance. In this study, the track quality index (TQI), which is commonly used to evaluate the status of tracks and to decide maintenance interventions, is reviewed, including 12 TQIs for superstructure and six for substructure. A literature review indicates that TQIs for sleepers and subgrade have not yet been developed. The differences between TQIs are compared using a set of hypothetical raw data. Their capabilities for identifying track irregularities are also investigated based on the EN 13848 regulations. To classify TQI characteristics in a systematic way, this study proposes four concepts: accuracy, sensitivity, data required, and specificity. Accuracy indicates a TQI’s capability of detecting defects; sensitivity indicates how TQIs change according to variations in the defects; specificity relates to the amount of parameters considered, and the ability to pinpoint root causes or global consequences of defects. The results suggest a tradeoff between the four concepts, where high sensitivity can increase the ability to detect the smallest defects but may be affected by bias; more parameters considered may indicate low accuracy when detecting a single type of defect. Therefore, this study suggests railway regulators use multiple TQIs with complementary characteristics for classifying track status.

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REDUCTION OF RISK DUE TO THE DESTRUCTION OF INDIVIDUAL AND UNIQUE TECHNICAL DEVICES

Bulletin of the Angarsk State Technical University ◽

10.36629/2686-777x-2020-1-14-147-156 ◽

2020 ◽

Vol 1 (14) ◽

pp. 147-156

Author(s):

Anatoliy Cherepanov

Keyword(s):

Corrosion Resistance ◽

Limit State ◽

A Priori ◽

Technical Condition ◽

Technical Diagnostics ◽

A Priori Information ◽

Technical Device ◽

Priori Information ◽

Reserve Strength ◽

Degree Of Degradation

The article notes that reducing the risk due to destruction is possible by an a priori assessment of the maximum technical condition and the degree of degradation of the material of the technical device. The idea is to use a priori information about the technical condition and degradation processes that cause a decrease in strength and a decrease in resource. The application of numerical indicators of corrosion, corrosion resistance of materials, the degree of wear and reserve strength, defects, the risk of destruction and the effectiveness of technical diagnostics at any stage of the life cycle of a technical device is shown. The justification of the model of transition to the limit state is given. Numerical indicators of corrosion, corrosion resistance of materials, the degree of wear and reserve strength, defects, and the risk of destruction are applied. The possibility of developing recommendations for repair, strengthening or replacement of worn-out elements of individual and unique technical devices of various designs is shown.

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Using metagenomic methods to detect organismal contaminants in microbial materials

10.7287/peerj.preprints.2913 ◽

2017 ◽

Author(s):

Nathan D Olson ◽

Justin M Zook ◽

Jayne B Morrow ◽

Nancy J Lin

Keyword(s):

Genomic Dna ◽

Pathogen Detection ◽

A Priori ◽

High Sensitivity ◽

Chain Reaction ◽

Measurement Results ◽

Polymerase Chain ◽

Materials Used ◽

Genome Assemblies ◽

Generation Sequencing

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Information Value Measure for Optimization of Flexible Diagnosis Programs of Technical Objects

SPIIRAS Proceedings ◽

10.15622/sp.2019.18.6.1434-1461 ◽

2019 ◽

Vol 18 (6) ◽

pp. 1434-1461 ◽

Cited By ~ 1

Author(s):

Evgeniy Kopkin ◽

Igor Kobzarev

Keyword(s):

A Priori ◽

Technical Condition ◽

Diagnostic Information ◽

Information Value ◽

Technical State ◽

A Posteriori ◽

Automated Systems ◽

Maximum Value ◽

Diagnostic Signs ◽

The Difference

Existing methods of calculating of the value of diagnostic information circulating in the automated systems of monitoring of technical condition of objects do not take into account "losses" ("gains") resulting from making “wrong” decisions when identifying this state. The purpose of the work is to develop an algorithm that allows to solve the problem of recognizing the technical state of the object being analyzed by means of dynamic programming, the value of the diagnostic information as an optimized indicator being used. The solution to the optimization problem of a diagnostic procedure is based on the use of a measure of the information value proposed by R. L. Stratonovich. It is modified according to the subject area of the technical diagnostics and in the case when the diagnostic features presented in the form of intervals on the real numerical axis are used. The maximum value of the diagnostic information is achieved by minimizing the average "losses" (maximizing the average "gains") obtained when performing tests of diagnostic signs in the process of recognizing the technical condition of an object. To solve the problem, a recurrent expression possessing a scientific novelty has been proposed. It allows to calculate the value of the information obtained when performing tests of diagnostic signs in each of the analyzed information states of the diagnostic process. In the process of the diagnostics program implementation when recognizing the technical condition of the object both “losses” and “winnings” are possible. The difference between their a priori and a posteriori means values characterizes the value of the diagnostic information numerically. The magnitude of the information value indication depends on the probabilities of the results of the diagnostic signs checks and is proportional to the difference between the a posteriori and a priori probabilities of achieving the diagnostic goal. By using the proposed solution, it is possible to synthesize the flexible diagnostics program that is optimal according to the maximum value of diagnostic information in the form of a oriented graph or sets of tests in proper sequence of their execution. This is necessary in order to recognize the specific technical state in which the object is located. The implementation of the algorithm developed is possible in the software and algorithmic support of the automated systems for monitoring the state of complex technical objects.

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Mathematical Modeling and Numerical Methods of the Analysis of Neural Structures

Proceedings of Telecommunication Universities ◽

10.31854/1813-324x-2019-5-3-98-107 ◽

2019 ◽

Vol 5 (3) ◽

pp. 98-107

Author(s):

L. Makarov ◽

A. Pozdnyakov ◽

S. Protasenya ◽

D. Ivanov ◽

V. Lvov ◽

...

Keyword(s):

A Priori ◽

Magnetic Resonance Tomography ◽

Research Process ◽

Telecommunication Service ◽

Computing Environment ◽

Neural Structure ◽

Cloud Computing Environment ◽

Analysis Process ◽

Topological Description ◽

Quantitative Indicators

In this article we can observe a mathematical model of the topological description of neural structure of human brain, which describes the results of numerical analysis process of a magnetic resonance tomography. The created model provides a possibility to organize a cloud computing environment, which achieves the synthesis of quantitative indicators of distinctions in analyzed fragments of neural tissue, it is created by means of the telecommunication service which is promoting the involvement of a large number of experts in to a research process, to create a set of a priori judgments of evolution of the registered processes.

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Challenging a bioinformatic tool’s ability to detect microbial contaminants usingin silicowhole genome sequencing data

PeerJ ◽

10.7717/peerj.3729 ◽

2017 ◽

Vol 5 ◽

pp. e3729 ◽

Cited By ~ 6

Author(s):

Nathan D. Olson ◽

Justin M. Zook ◽

Jayne B. Morrow ◽

Nancy J. Lin

Keyword(s):

Binary Mixtures ◽

Genome Sequencing ◽

Pathogen Detection ◽

A Priori ◽

High Sensitivity ◽

False Positives ◽

Sequencing Data ◽

Materials Used ◽

The Individual ◽

Genome Assemblies

High sensitivity methods such as next generation sequencing and polymerase chain reaction (PCR) are adversely impacted by organismal and DNA contaminants. Current methods for detecting contaminants in microbial materials (genomic DNA and cultures) are not sensitive enough and require either a known or culturable contaminant. Whole genome sequencing (WGS) is a promising approach for detecting contaminants due to its sensitivity and lack of need fora prioriassumptions about the contaminant. Prior to applying WGS, we must first understand its limitations for detecting contaminants and potential for false positives. Herein we demonstrate and characterize a WGS-based approach to detect organismal contaminants using an existing metagenomic taxonomic classification algorithm. Simulated WGS datasets from ten genera as individuals and binary mixtures of eight organisms at varying ratios were analyzed to evaluate the role of contaminant concentration and taxonomy on detection. For the individual genomes the false positive contaminants reported depended on the genus, withStaphylococcus,Escherichia, andShigellahaving the highest proportion of false positives. For nearly all binary mixtures the contaminant was detected in thein-silicodatasets at the equivalent of 1 in 1,000 cells, thoughF. tularensiswas not detected in any of the simulated contaminant mixtures andY. pestiswas only detected at the equivalent of one in 10 cells. Once a WGS method for detecting contaminants is characterized, it can be applied to evaluate microbial material purity, in efforts to ensure that contaminants are characterized in microbial materials used to validate pathogen detection assays, generate genome assemblies for database submission, and benchmark sequencing methods.

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