scholarly journals Evaluation of the effectiveness of the forecasting system for special cases in flight based on the analysis of diagnostic data of the aircraft technological equipment

Connectivity ◽  
2020 ◽  
Vol 146 (4) ◽  
Author(s):  
I. O. Padalka ◽  
◽  
D. O. Parkhomenko ◽  
O. V. Shchenyakín ◽  
◽  
...  
Keyword(s):  
Expert Knowledge ◽  
Transition Probabilities ◽  
A Priori ◽  
Information Support ◽  
Main Task ◽  
Technological Equipment ◽  
Diagnostic Data ◽  
Production Models ◽  
Special Cases ◽  
Forecasting System

The paper proposes an approach to assessing the effectiveness of the forecasting system for special cases in flight based on the analysis of diagnostic data of the aircraft technological equipment. Prediction of special cases in flight is the main task of parametric diagnostics of aircraft technological equipment. To solve this problem, on-board automated monitoring, diagnostics and control of onboard equipment, unloading and information support of the crew make it possible to measure a large number of parameters of the aircraft technological equipment and obtain arrays of such information in digital form. It is proposed to process the received information using the method of predicting special cases in flight based on the identification of abnormal sequences in the diagnostic data of the aircraft technological equipment. To identify anomalous sequences, it is proposed to use a hybrid stochastic model based on the combination of Markov and production models that use temporal rules to refine the transition probabilities between process states. Due to the inclusion of refining production rules in the model, the probability of describing random processes that are not Markovian increases, and it also becomes possible to integrate a priori expert knowledge into the model, which is very important for predicting special cases in flight. It is proposed to evaluate the effectiveness of the forecasting system by two criteria: the efficiency and reliability of the decisions made by the aircraft crew. In the robot, a simulation was carried out on the simulator of a winding ship A-320 for evaluating the situation as well as taking decisions from the negative inheritance of particular types of problems in the country.

scholarly journals A method for detecting abnormal sequences in the diagnostic data of technological equipment of an aircraft to prevent special cases in flight

2020 ◽  
Vol 69 (2) ◽  
Author(s):  
I. O. Padalka ◽  
◽  
P. V. Open’ko ◽  
V. M. Rudenko ◽  
M. P. Stolyarenko ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Expert Knowledge ◽  
Transition Probabilities ◽  
Economic Effect ◽  
Operating Time ◽  
Process Equipment ◽  
Main Task ◽  
Technological Equipment ◽  
Diagnostic Data ◽  
Special Cases

Prediction of special cases in flight is the main task of parametric diagnostics of aircraft technological equipment. To solve this problem, on-board means of automated control, diagnostics and control of on-board equipment, unloading and information support of the crew use mathematical models based on the trend analysis of some registered operating time parameters. However, existing diagnostic models based on the corresponding mathematical models do not always allow predicting the occurrence of process equipment failures. What makes the task of forecasting special cases in flight relevant. The paper proposes a method for predicting special cases in flight based on identifying abnormal sequences in the diagnostic data of aircraft technological equipment. To identify abnormal sequences, it is proposed to use a hybrid stochastic model based on a combination of Markov and production models using temporal rules to specify transition probabilities between process states. By including more precise production rules in the model, the probability of describing random processes that are not Markovian is increased, and it becomes possible to integrate a priori expert knowledge into the model, which is very important for predicting special cases in flight. The application of the proposed method will allow to implement the prognostic principle of flight safety management, as well as to obtain the economic effect of preventing aircraft downtime due to sudden equipment failure.

scholarly journals The monitoring system based on lookup algorithm for objects described by ordinary differential equations

2018 ◽  
Vol 21 ◽  
pp. 00006
Author(s):  
Przemysław Hawro ◽  
Tadeusz Kwater ◽  
Dariusz Strzęciwilk
Keyword(s):  
Neural Networks ◽  
Kalman Filter ◽  
Expert Knowledge ◽  
A Priori ◽  
Monitoring Systems ◽  
Main Task ◽  
New Approach ◽  
Incremental Method ◽  
Filter Approach

The article presents a new approach to monitoring systems of a certain class using the lookup algorithm. The main task is to generate object signals based on measured but only some selected signals. This idea is based on the Kalman filter approach, but the calculation method of the gain coefficients is different. Its values are determined in a similar way as weights in neural networks during learning (incremental method). The proposed lookup algorithm uses expert knowledge a priori for determining gain corrections, and its functioning is presented for the case of two monitoring error zones. The presented results clearly indicate the advantage of the lookup algorithm over the Kalman filter. Two RMSE and MPE indicators were used for the quality of monitoring.

On the Theory of Thermally Weighted Electron-Phonon Transition Probabilities

1980 ◽  
Vol 35 (9) ◽  
pp. 902-914
Author(s):  
J. Schupfner
Keyword(s):  
Transition Probabilities ◽  
Algebraic Method ◽  
Calculation Technique ◽  
Radiative Transitions ◽  
Special Cases ◽  
Explicit Formulae ◽  
The Common ◽  
Common Transition ◽  
Franck Condon ◽  
Refined Calculation

Abstract We present a refined calculation method for the phonon part (Franck-Condon Overlaps) of the transition probabilities of electron-phonon radiative and non-radiative transitions in crystals. The evaluation of the thermal averaged Franck-Condon integrals is a purely algebraic method and the transition probabilities we use are derived from first principles and completely atomistic. For the electronic transitions we take into account the frequency shift of the lattice and the change of the phonon normal coordinates. Explicit formulae of the phonon parts are derived and it is shown that the common transition probabilities used in literature are special cases of our functional calculation technique.

scholarly journals Modeling the Process of Event Sequence Data Generated for Working Condition Diagnosis

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Jianwei Ding ◽  
Yingbo Liu ◽  
Li Zhang ◽  
Jianmin Wang
Keyword(s):  
Working Condition ◽  
Sequence Data ◽  
A Priori ◽  
Real Data ◽  
Data Sets ◽  
Main Task ◽  
Event Sequence ◽  
Telemetry Data ◽  
Condition Monitoring Systems ◽  
Condition Diagnosis

Condition monitoring systems are widely used to monitor the working condition of equipment, generating a vast amount and variety of telemetry data in the process. The main task of surveillance focuses on analyzing these routinely collected telemetry data to help analyze the working condition in the equipment. However, with the rapid increase in the volume of telemetry data, it is a nontrivial task to analyze all the telemetry data to understand the working condition of the equipment without any a priori knowledge. In this paper, we proposed a probabilistic generative model called working condition model (WCM), which is capable of simulating the process of event sequence data generated and depicting the working condition of equipment at runtime. With the help of WCM, we are able to analyze how the event sequence data behave in different working modes and meanwhile to detect the working mode of an event sequence (working condition diagnosis). Furthermore, we have applied WCM to illustrative applications like automated detection of an anomalous event sequence for the runtime of equipment. Our experimental results on the real data sets demonstrate the effectiveness of the model.

scholarly journals Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model

2017 ◽  
Vol 17 (11) ◽  
pp. 6663-6678 ◽  
Author(s):  
Shreeya Verma ◽  
Julia Marshall ◽  
Mark Parrington ◽  
Anna Agustí-Panareda ◽  
Sebastien Massart ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Transport Model ◽  
A Priori ◽  
Atmospheric Composition ◽  
Random Errors ◽  
Chemical Transport Model ◽  
Spatial Coverage ◽  
Forecasting System ◽  
The Impact ◽  
Total Column

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 and 34 ppb, respectively). In comparison, the a priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

THEORETICAL PRINCIPLES OF OPERATING ASSETS MANAGEMENT OF ENTERPRISES

2018 ◽  
Author(s):  
Olexandr Yemelyanov ◽  
◽  
Tetyana Petrushka ◽  
Anatolii Havryliak ◽  
Ostap Ivanchyna ◽  
...  
Keyword(s):  
Economic Activity ◽  
The Other ◽  
Information Support ◽  
Main Task ◽  
Effective Mechanism ◽  
Current State ◽  
Complex Process ◽  
Model Of Management ◽  
The One ◽  
Assets Management

The efficiency of economic activity of enterprises largely depends on the proper management of their assets. Whereas, an important type of assets of enterprises is its operating wealth, which serves the processes of production and marketing of products of economic entities. This is a complex process of circulation of operating assets, during which transformation from one species to another is being carried out. The course of such a process may involve different amounts of demand for current assets for a certain volume of production and sales. In other words, these assets are characterized by a certain level of flexibility and the main task of managing them is to establish their rational value. This value should ensure, on the one hand, the continuity of the production process at the enterprise and the timeliness of receipt of funds from the sale of products, and, on the other hand, the absence of excess inventories and other types of operating assets. The solution of this problem requires the introduction of an effective mechanism for managing its current assets. Considering this, the purpose of this article is to develop theoretical principles for managing operating assets of enterprises. It has been shown that the process of such management should be based on the system, created at the enterprises of information support of this process. Under this system is proposed to understand a set of information arrays and formalized algorithms for its processing, with which it is possible to assess the current state of use of operating assets of the company and develop a set of measures aimed at structuring and optimizing its volume. The basic requirements to designing of system of information maintenance of management of operating assets of the enterprises have been presented. The required information for the management of operating assets has been grouped. The areas grouping of operating assets management of the enterprise depending on the stages of its circulation has been carried out. The model of management of debts receivable of the enterprises has been specified. The use of the developed theoretical principles of operating assets management of enterprises in the practice of their activities increases financial results by streamlining the volume and structure of current assets of economic entities.

scholarly journals Bayesian wavelet de-noising with the caravan prior

2019 ◽  
Vol 23 ◽  
pp. 947-978
Author(s):  
Shota Gugushvili ◽  
Frank van der Meulen ◽  
Moritz Schauer ◽  
Peter Spreij
Keyword(s):  
Empirical Bayes ◽  
Expert Knowledge ◽  
Estimation Error ◽  
A Priori ◽  
Real Data ◽  
Detailed Comparison ◽  
Wavelet Coefficients ◽  
Visual Appearance ◽  
Bayesian Wavelet ◽  
Clustering Patterns

According to both domain expert knowledge and empirical evidence, wavelet coefficients of real signals tend to exhibit clustering patterns, in that they contain connected regions of coefficients of similar magnitude (large or small). A wavelet de-noising approach that takes into account such a feature of the signal may in practice outperform other, more vanilla methods, both in terms of the estimation error and visual appearance of the estimates. Motivated by this observation, we present a Bayesian approach to wavelet de-noising, where dependencies between neighbouring wavelet coefficients are a priori modelled via a Markov chain-based prior, that we term the caravan prior. Posterior computations in our method are performed via the Gibbs sampler. Using representative synthetic and real data examples, we conduct a detailed comparison of our approach with a benchmark empirical Bayes de-noising method (due to Johnstone and Silverman). We show that the caravan prior fares well and is therefore a useful addition to the wavelet de-noising toolbox.

The ‘Corroborative Rule’ from a comparative and critical perspective

2019 ◽  
Vol 23 (3) ◽  
pp. 282-298
Author(s):  
Guy Ben-David
Keyword(s):  
A Priori ◽  
Critical Discussion ◽  
Reasonable Doubt ◽  
Critical Examination ◽  
Judicial Discretion ◽  
Criminal Proceedings ◽  
Clear Trend ◽  
Single Piece ◽  
Special Cases ◽  
Anglo American

In general, a conviction may be based on a single piece of evidence or a single testimony if the court is convinced that it proves the accused’s guilt beyond a reasonable doubt. Nevertheless, in some jurisdictions special cases were established by statute and case law in which a single piece of evidence cannot suffice to prove a defendant’s guilt and additional evidence is required to support the main evidence. This rule, known as the Corroborative Rule (hereinafter ‘the rule’ or ‘CR’) constitutes a barrier against conviction on the basis of individual evidence, without the judge or jury cautioning themselves against reliance on a single piece of evidence in order to convict the accused. In general, the requirement for additional evidence exists in cases where there is a single piece of incriminating evidence, but there is concern regarding its reliability. In order to reduce the risk of a mistake that will lead to a false conviction (conviction of an innocent defendant), the law requires additional evidence as a condition for conviction. The first purpose of this article is to provide a comparative-descriptive perspective on the CR as practised in Anglo-American and Israeli law. While in continental law a defendant’s conviction is not subject to any requirement for a specific quantity of evidence, in Anglo-American law there is a clear trend to reduce the application of a requirement for additional evidence. Yet in Israeli law, an opposite trend is evident, expressed in increased application of the Corroborative Rule in order to convict the accused. The second purpose of the article is to undertake a critical examination of the theoretical infrastructure underpinning the CR. According to this infrastructure, the justification for the CR is epistemic and relates, as a rule, to testimony whose reliability is, a priori, dubious. Thus the CR is linked to one of the purposes of some of the rules of criminal proceedings, which is to prevent the conviction of innocent defendants. However, at the same time, the CR restricts judicial discretion and harms the prosecutor’s and the court’s ability to ensure conviction of guilty defendants, even in cases where there is a single piece of evidence, which the court trusts. The first section provides a comparison of the use of the CR in English, Canadian, Scottish, American and Israeli law. The second section is devoted to the description of the theoretical infrastructure of the CR, while the third section contains a critical discussion on both the theoretical infrastructure described in the second section and also the requirement for evidential supplements, in general. To conclude the article, I provide a summary of its contents.

scholarly journals Cut finite element methods for partial differential equations on embedded manifolds of arbitrary codimensions

2018 ◽  
Vol 52 (6) ◽  
pp. 2247-2282 ◽  
Author(s):  
Erik Burman ◽  
Peter Hansbo ◽  
Mats G. Larson ◽  
André Massing
Keyword(s):  
Finite Element ◽  
Finite Element Methods ◽  
Stiffness Matrix ◽  
A Priori ◽  
Beltrami Operator ◽  
Optimal Order ◽  
Codimension One ◽  
Special Cases ◽  
Arbitrary Codimension ◽  
Background Mesh

We develop a theoretical framework for the analysis of stabilized cut finite element methods for the Laplace-Beltrami operator on a manifold embedded in ℝd of arbitrary codimension. The method is based on using continuous piecewise linears on a background mesh in the embedding space for approximation together with a stabilizing form that ensures that the resulting problem is stable. The discrete manifold is represented using a triangulation which does not match the background mesh and does not need to be shape-regular, which includes level set descriptions of codimension one manifolds and the non-matching embedding of independently triangulated manifolds as special cases. We identify abstract key assumptions on the stabilizing form which allow us to prove a bound on the condition number of the stiffness matrix and optimal order a priori estimates. The key assumptions are verified for three different realizations of the stabilizing form including a novel stabilization approach based on penalizing the surface normal gradient on the background mesh. Finally, we present numerical results illustrating our results for a curve and a surface embedded in ℝ3.

Regional Assimilation System for Transformed Retrievals from Satellite High-Resolution Infrared Data

2020 ◽  
Vol 59 (7) ◽  
pp. 1171-1193
Author(s):  
Paolo Antonelli ◽  
Tiziana Cherubini ◽  
Steven Businger ◽  
Siebren de Haan ◽  
Paolo Scaccia ◽  
...  
Keyword(s):  
Temperature Field ◽  
Water Vapor ◽  
North Pacific Ocean ◽  
A Priori ◽  
Satellite Sensors ◽  
Forecasting System ◽  
Cycling System ◽  
Priori Information ◽  
The Impact ◽  
Vapor Distribution

AbstractSatellite retrievals strive to exploit the information contained in thousands of channels provided by hyperspectral sensors and show promise in providing a gain in computational efficiency over current radiance assimilation methods by transferring computationally expensive radiative transfer calculations to retrieval providers. This paper describes the implementation of a new approach based on the transformation proposed in 2008 by Migliorini et al., which reduces the impact of the a priori information in the retrievals and generates transformed retrievals (TRs) whose assimilation does not require knowledge of the hyperspectral instruments characteristics. Significantly, the results confirm both the viability of Migliorini’s approach and the possibility of assimilating data from different hyperspectral satellite sensors regardless of the instrument characteristics. The Weather Research and Forecasting (WRF) Model’s Data Assimilation (WRFDA) 3-h cycling system was tested over the central North Pacific Ocean, and the results show that the assimilation of TRs has a greater impact in the characterization of the water vapor distribution than on the temperature field. These results are consistent with the knowledge that temperature field is well constrained by the initial and boundary conditions of the Global Forecast System (GFS), whereas the water vapor distribution is less well constrained in the GFS. While some preliminary results on the comparison between the assimilation with and without TRs in the forecasting system are presented in this paper, additional work remains to explore the impact of the new assimilation approach on forecasts and will be provided in a follow-up publication.

Sign in / Sign up

Export Citation Format

Share Document