Methods and tools of causal mnemonic schemes in monitoring and control systems for complex dynamic objects

Размещено на http://allbest.ru

Russian academy of sciences

V.A. Trapeznikovinstitute of control sciences

Laboratory of dynamic information-control systems,

Guchuk Vladimir Vsevolodovich

PhD in Engineering, Senior Researcher

Moscow

Abstract

In interactive control systems for complex dynamic objects, the human operator must have a complete understanding of the state of the controlled objects. This is a huge amount of fast-changing data. At the same time, it is necessary to ensure the possibility of an adequate perception of the person of the information presented in order to take conscious and effective control actions in order to take measures in advance to prevent the occurrence of abnormal or emergency situations. The paper describes the methods and tools of a new class of representations - causal mnemonic schemes designed to display the interconnectedness of processes occurring in a controlled system, as well as a causal picture of observed events and interconnected reactions of subsystems to control actions, including the mapping of the dynamics of distribution of tension of nodes and assemblies.

Keywords: control system, human-operator, visualization, causal mnemonic scheme, abnormal situation.

Аннотация

Методы и инструментарий каузальных мнемосхем в системах мониторинга и управления сложными динамическими объектами

Гучук Владимир Всеволодович - кандидат технических наук, старший научный сотрудник, лаборатория динамических информационно-управляющих систем, Институт проблем управления им. В.А. Трапезникова Российская академия наук, г. Москва

В интерактивных системах управления сложными динамическими объектами человек - оператор должен иметь полное представление о состоянии управляемых объектов. Это огромный объем быстроменяющихся данных. В то же время надо обеспечить возможность адекватного восприятия человеком представленной информации. В работе описываются методы и инструментарий нового класса представлений - каузальных мнемосхем, предназначенных для отображения взаимосвязи процессов, протекающих в управляемой системе, причинно-следственной картины наблюдаемых событий, взаимоувязанных реакций подсистем на управляющие воздействия, отображения динамики распределения напряженности узлов и агрегатов.

Ключевые слова: система управления, человек - оператор, визуализация, каузальная мнемосхема, нештатная ситуация.

Then creating interactive systems for monitoring and managing complex scientific and technical objects, one of the most important is the task of developing mechanisms to prevent abnormal and emergency situations [1, 2].

The processes occurring in the new developed scientific and technical objects are often not fully understood and not properly formalized. Therefore, in addition to the appropriate design of control algorithms, it is necessary to ensure the full participation of the human operator in the control process.

Hypothetically, this will make it possible to detect trends in the departure of controlled processes from the regular modes at the earliest stages of their manifestation.

For effective participation of the human operator in the process of monitoring and management, it is necessary to create such visualization that will give a fairly complete (valid, competent) understanding of the state of the controlled object, and at the same time allow it to adequately perceive the information presented and take informed and correct actions.

In [3], a new class of representations was proposed -- causal mnemonic schemes that extend the capabilities of ordinary mnemonic schemes.

Causal mnemonic schemes are exactly the tools that make it possible for a human operator to get a detailed and detailed understanding of the state of a controlled object, identify the root cause of an abnormal situation, assess the scale of an event and determine the possibility of its localization, take conscious actions to prevent an abnormal or emergency situation.

Causal mnemonic schemes are designed to display not only the elements of the system, but the interrelationship of the processes occurring in it, the causal pattern of the observed events, interrelated reactions of the subsystems to control actions, the display of the dynamics of the distribution of the intensity of nodes and units, etc. In a sense, the elements of such an analysis are realized when a human operator works in already existing systems.

The main difference is that for greater efficiency, visual analysis is supported by causal mnemonic schemes, which presumably will allow for more meaningful and operational analysis. Fig. 1 illustrates this type of presentation.

Fig. 1. Generalized causal mnemonic scheme

In the figure, the degree of darkening of a rectangle in each element of the scheme (which we will call the pictogram) corresponds to the degree of “trouble” or deviation from the norm of the corresponding element.

The thickness of the connecting lines - the degree of relevance of this connection. The number before the point is the number of the level in the hierarchy, and after the point is the sequence number at this level (for a human operator instead of numbers, the names of icons - processes, nodes, phenomena, etc.) are displayed. In reality, a wider range of tools is used, including numerical data, color labels, etc.

With a downward analysis (II), i.e. when moving from the upper level down, a “search for causes” is performed. Otherwise (i) the “effects detection” is performed.

When developing causal mnemonic schemes for solving specific problems, it is advisable to use the accumulated experience in solving similar problems. It is necessary, in any case, to be guided by the developed recommendations, methodologies, principles. We give a list of the basic principles of diagnostic studies. The basis for the organization of diagnostic studies should be the principles, the implementation of which will allow to increase the efficiency of the work carried out. causal mnemonic control operator information

These include the principle of a key element, the principle of consistency, the principle of cause and effect correspondence.

The principle of key link. The flow control system is a complex system. The processes occurring in it, are formed under the influence of many factors. It is practically impossible to take into account and investigate them all; it is necessary to choose the most crucial of them.

Isolation of the key problems and the main causes of the problem situation is one of the principles of the diagnostic study. This principle is achieved by decomposing the functions and objectives of the logistic system, classifying problems, and prioritizing individual factors in assessing problems.

The principle of consistency. Systematic diagnosis in a diagnostic study means a comprehensive and interrelated study of the problems of the control system and the identification of all the consequences and interrelationships of each particular problem solution.

In accordance with this principle, the program to improve the management of material flows and the inclusion in it of measures to eliminate individual problems should be assessed from the point of view of the functioning of the entire system of management of material flows as a whole, so as to eliminate the possibility of unexpected and unforeseen consequences.

The principle of causality. One of the requirements for diagnosis is the knowledge of the causes of violations in the system and deviations from the norm of its parameters.

One of the foundations of the construction of causal mnemonic schemes is causal analysis. As is known, causal dependence is a connection of phenomena, one of which gives rise to the other. We present the basic logical methods of causal analysis, which are closely interrelated. Exclusion method. The essence of this method lies in the fact that, analyzing a complex set of cause-and-effect relations, one can find the immediate cause by eliminating all the alleged circumstances (which do not really influence, although present), which can cause similar events, except for one factor, which after careful verification and taken for the cause of the phenomenon under study.

Method of similarity. The use of the method of similarity is due to the fact that events of interest, the cause of which the analyst wants to establish, arise in a variety of circumstances, but always with the presence of the same factor. The essence of this method comes down to the following: if the observed event occurs in various circumstances, but if there is one common factor, then this factor is the reason for what is happening.

Using this method, one can study different conditions for the occurrence of the same event and calculate from them the same general factor causing this phenomenon. With a certain probability, it can be argued that this factor is the reason of interest to the analyst.

The method of one difference. The method is reduced to comparing the case when the event of interest occurs, with the case when it does not occur. In both cases, the same conditions should be the same, except for one, which is absent in one of the cases. In other words, if in the same circumstances, if there is a factor, an event occurs, and in the absence of it, the phenomenon being investigated does not occur, then this factor is the cause of the phenomenon being studied.

The principles and methods given are of a general nature. Nevertheless, each new practical task requires a rethinking of existing experience and the development of quite specialized tools, in the arsenal of which causal mnemonic schemes can occupy quite a worthy place.

Along with them, a whole class of methods and technologies are needed to implement the aforementioned anticipatory criterial adaptation, such as: - updating the necessary exit algorithms from a possible abnormal situation, which requires additional data processing in real and often “hard” time; - release of the interrupt system from processing incoming data that are not relevant for the situation that arises; - adjustment of the threshold values of control parameters for an earlier determination of the fact of the disorder in the context of the current situation. The work touched upon several defining aspects of the interface arrangement of humanoperator interaction and software and hardware for monitoring systems and managing complex dynamic objects.

The organization of visual support for the logical analysis of the situation by a human operator based on causal mnemonic schemes is described. The basic principles that should be followed to create such support are given. Separate proposed solutions were used in the development of a specific system [4].

References / Список литературы

1. Dianov V.N. Conceptual characteristic features of fault-free hardware design // Automation and Remote Control, 2012. V. 73. № 7. P. 1202-1215.

2. Guchuk V. V. Compact visualization of dynamic parameters in monitoring and control systems // Scientific Visualization, 2018. № 2. P. 61-60.

3. Guchuk V.V. Applied aspects of the organization of an interactive mode for increasing the security of functioning of control systems of complicated objects // European science, 2018. № 1. P. 18-21.

4. Guchuk V.V. Development of information exchange of software and hardware tools of system of test of difficult scientific-technical objects // Proceedings of the Conference "MLSD". Moscow: IEEE Explore Digital Library, 2017. P. 1-5, 2017. [Электронный ресурс]. Режим доступа:http://ieeexplore.ieee.org/ document/8109636/(дата обращения: 17.12.2019

Размещено на Allbest.ru