Complex Automation Systems Research Articles

An Environmentally Adaptive and Contrastive Representation Learning Method for Condition Monitoring of Industrial Assets.

Condition monitoring of assets is significant to the efficiency and reliability of industrial automation systems. However, the accuracy of condition monitoring results is easily impaired by variational environments and volatile operations, especially for complex automation systems. In this article, an environmentally adaptive and contrastive representation learning method is proposed to address the problem. To suppress the unexpected effects of environmental variations on operating data, a regression model between the operational and environmental variables is developed. The variable regression adjustment is achieved by solving a penalized optimization problem based on spline functions, and the solution is explicitly derived. Then, negative samples and pseudo labels are generated based on the designed pattern of data augmentation, and valid data representations for asset condition monitoring can be obtained by contrastive learning. Moreover, the reference statue of healthy assets is established by kernel density estimation, and control charts are employed for online monitoring with alarm thresholds. Taking wind turbine blades as examples, the remarkable performance of the developed method is demonstrated with real-world measurements from wind farms. Furthermore, comparative analysis with benchmark approaches and ablation study are conducted to reveal the superiority and effectiveness of the proposed method.

Анализ цифровых информационных моделей на всех этапах жизненного цикла объекта капитального строительства

The accelerating pace of building automation requires industry professionals to be increasingly skilled. Complex automation systems appear on the application software market, which entails an expansion of the possibilities of their application in the practice of construction production. The development of such programs and software systems is carried out chaotically, based on the empirical experience of domestic specialists, foreign colleagues, or already existing foreign solutions.
 In this regard, there is a need to develop such solutions that would be adapted to the domestic consumer in terms of legal documentation, as well as compliance with the chosen path for the development of information technologies in construction.
 Application software in the field of information modeling technologies already now allows solving a wide range of tasks due to domestic solutions. Nevertheless, a significant part of the processes still remains untouched.
 The main purpose of the study presented in this article is to analyze the existing business process for analyzing digital information models to form its map and modeling the process based on it using SOD, as well as the subsequent implementation of some of its subprocesses in the domestic EXON BIM software package.
 The implementation of the tasks set was investigated using the BPMN and BPM notation of the Draw.io software system.

Intelligent controller for unmanned surface vehicles by deep reinforcement learning

With the development of the applications of unmanned surface vehicles (USVs), USV automation technologies are attracting increasing attention. In the industry, through the subtask division, it is generally believed that course-keeping is a critical basic sub-system in a series of complex automation systems and affects USV automation performance to a great extent. By course-keeping, we mean USV adjusts its angle to the desired angle and keeps it. In recent decades, course-keeping has been mainly achieved through classical first principles technologies, such as proportion–integral–differential (PID) controllers, leading to extremely laborious parameter tuning, especially in changeable wave environments. With the emergence and extensive application of data-driven technologies, deep reinforcement learning is conspicuous in sequential decision-making tasks, but it introduces a lack of explainability and physical meaning. To take full advantage of the data-driven and first principles paradigm and easily extend to the industry, in this paper, we propose an intelligent adaptive PID controller enhanced by proximal policy optimization (PPO) to achieve USV high-level automation. We then further verify its performance in path-following tasks compared with the PID controller. The results demonstrate that the proposed controller inherits the merits of explainability from PID and excellent sequential decision making from PPO and possesses excellent disturbance rejection performance when facing the disturbance of a changeable wave environment.

Negation-based transfer learning for improving biomedical Named Entity Recognition and Relation Extraction

Background and Objectives:Named Entity Recognition (NER) and Relation Extraction (RE) are two of the most studied tasks in biomedical Natural Language Processing (NLP). The detection of specific terms and entities and the relationships between them are key aspects for the development of more complex automatic systems in the biomedical field. In this work, we explore transfer learning techniques for incorporating information about negation into systems performing NER and RE. The main purpose of this research is to analyse to what extent the successful detection of negated entities in separate tasks helps in the detection of biomedical entities and their relationships. Methods:Three neural architectures are proposed in this work, all of them mainly based on Bidirectional Long Short-Term Memory (Bi-LSTM) networks and Conditional Random Fields (CRFs). While the first architecture is devoted to detecting triggers and scopes of negated entities in any domain, two specific models are developed for performing isolated NER tasks and joint NER and RE tasks in the biomedical domain. Then, weights related to negation detection learned by the first architecture are incorporated into those last models. Two different languages, Spanish and English, are taken into account in the experiments. Results:Performance of the biomedical models is analysed both when the weights of the neural networks are randomly initialized, and when weights from the negation detection model are incorporated into them. Improvements of around 3.5% of F-Measure in the English language and more than 7% in the Spanish language are achieved in the NER task, while the NER+RE task increases F-Measure scores by more than 13% for the NER submodel and around 2% for the RE submodel. Conclusions:The obtained results allow us to conclude that negation-based transfer learning techniques are appropriate for performing biomedical NER and RE tasks. These results highlight the importance of detecting negation for improving the identification of biomedical entities and their relationships. The explored techniques show robustness by maintaining consistent results and improvements across different tasks and languages.

A Tool-Assisted Approach for User-Friendly Definition of FB Constraints

Model-based software engineering is a promising approach for controlling complex automation systems. Automation engineers, unfortunately, do not routinely model the expected behavior, especially if they are not trained in software engineering. They rather focus only on the implementation. In this paper, we analyze potential causes for the low adoption of service sequences within IEC 61499, which define behavioral constraints for building blocks of control applications. We propose a methodology for mining constraints of software components, which are then classified by an engineer. Furthermore, we suggest extending the language to allow for forbidden and mandatory scenarios. Our approach facilitates the constraint definition for legacy software, where the effort of manual specification is extremely high. Tool support for all described extensions and modeling techniques is provided as part of the open source IDE Eclipse 4diac to facilitate applying the approach in practice.

Sizing of a fuel cell–battery backup system for a university building based on the probability of the power outages length

Hydrogen is a bright energy vector that could be crucial to decarbonise and combat climate change. This energy evolution involves several sectors, including power backup systems, to supply priority facility loads during power outages. As buildings now integrate complex automation, domotics, and security systems, energy backup systems cause interest. A hydrogen-based backup system could supply loads in a multi-day blackout; however, the backup system should be sized appropriately to ensure the survival of essential loads and low cost. In this sense, this work proposes a sizing of fuel cell (FC) backup systems for low voltage (LV) buildings using the history of power outages. Historical data allows fitting a probability function to determine the appropriate survival of loads. The proposed sizing is applied to a university building with a photovoltaic generation system as a case study. Results show that the sizing of an FC–battery backup system for the installation is 7.6% cheaper than a battery-only system under a usual 330-minutes outage scenario. And 59.3% cheaper in the case of an unusual 48-hours outage scenario. It ensures a 99% probability of supplying essential load during power outages. It evidences the pertinence of an FC backup system to attend to outages of long-duration and the integration of batteries to support the abrupt load variations. This research is highlighted by using historical data from actual outages to define the survival of essential loads with total service probability. It also makes it possible to determine adequate survival for non-priority loads. The proposed sizing is generalisable and scalable for other buildings and allows quantifying the reliability of the backup system tending to the resilience of electrical systems.

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was < 9 h for 95% of samples and < 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.

Efficient SARS-CoV-2 Quantitative Reverse Transcriptase PCR Saliva Diagnostic Strategy utilizing Open-Source Pipetting Robots.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was < 9 h for 95% of samples and < 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.

Sliding-mode variable structure control for complex automatic systems: a survey.

Automatic systems (ASs) can automatically control the work of controlled objects without unattended participation. They have been extensively used in industry, agriculture, automobiles, robots and other fields in recent years. However, the performance of the controller cannot meet the work requirements under complex environmental conditions. Therefore, improving the control performance is one of the difficult problems that automated systems should solve. Sliding-mode variable structure control has the advantages of fast response, insensitivity to uncertainty and interference and easy implementation; thus, it has been extensively used in the field of complex control systems. This article analyses and explains the research status of motors, microgrids, switched systems, aviation guidance, robots, mechanical systems, automobiles and unmanned aerial vehicles (UAVs) and prospects for the application of sliding-mode variable structure control in complex ASs.

Mechatronic Anti-Collision System for Electric Wheelchairs Based on 2D LiDAR Laser Scan.

Electric wheelchairs make it easier for disabled and elderly people to live, move, interact, and participate in society. Moving a wheelchair in open spaces is relatively easy, but in closed and small spaces, maneuvering is difficult. Solutions to such problems for people with disabilities are applicable to a relatively small group of recipients and are mostly custom-made solutions, whose considerable cost is a significant barrier to accessibility. New technologies can provide an opportunity to improve the quality of life of people with disabilities in this aspect. Using selected elements of complex automation and control systems, cost-effective solutions can be created that facilitate the functioning of people with disabilities. This paper presents an analysis of hazards and problems when maneuvering a wheelchair in narrow passageways, as well as the authors’ solution to this problem, and the concept and assumptions of a mechatronic anti-collision system based on 2D LiDAR laser scanners. This solution is composed of a proprietary 2D rotating scanner mechanism that ensures the acquisition of 3D images of the environment around the wheelchair. Preliminary tests of this solution yielded promising results. Further research will include miniaturization of the device.

Analysis of X-ray luminescent separation of diamond ores as an automation object

The paper discusses the basic principles of X-ray luminescent separation of diamond ores as an automation object and analyzes modern technical solutions and basic organizational and technical issues, the solution to which will contribute to the effective implementation of automated control systems in separation. The complex automation systems of processing plants (ore mills) are described. The process and principle of operation of the X-ray luminescent separator of diamond ores are described. It is expedient to automate the X-ray luminescent separation using an automated control system. The issues of designing an automated control system with a human-machine interface are considered. An APCS system and an interface of the automated operator-technologist workstation, upgraded through implementing RSLogix 5000 and FactoryTalk View production management software are described.

Dealing with Communication Channels within IEC61499 Component-Based Systems

Traditional approaches for developing automation systems consider system itself hardly can be changed. Current challenges in automation applications include the need of autoreconfiguration in response to process changes or event triggering. In order to face these requirements, new automation methodologies are necessary. Component-based technologies, initially defined for achieving efficient, structured and reusable designs can also be used to achieve adaptation. In this work, an IEC 61499-based framework that uses the concept to deal with reconfiguration issues is presented. The final output of the framework is a distributed system IEC61499 compliant. A new concept, the communication channel, is introduced providing a new abstraction layer to deal with communication between components. The joint use of automation components and communication channels allows defining complex automation systems in an easy way.

Application of Ant Colony Optimization for the Shortest Path Problem of Waste Collection Process

The search for the shortest path of the waste collection process is an interesting topic that can be applied to various cases, from a very practical basic problem to a complex automation system development. In a dense settlement, the waste collection system can be a challenging process, especially to determine the most optimized path. The obstacles can be circling streets, impassable roads, and dead-end roads. A wrong choice of method can result in wasteful consumption of energy. A possible method to solve the problem is the traveling salesman problem using ant colony search optimization, considering its relatively fast optimization process. Therefore, this paper proposes an application of ant colony and traveling salesperson problem in determining the shortest path of the waste collection process. The case study for the optimization algorithm application is the path UGM Sekip Lecturer Housing is considering. Firstly, the data was collected by measuring the distance between points. Then, the paths were modeled and then compared with the actual route used by waste transport vehicles. The last step is implementing the ant colony optimization and traveling salesman problem by determining the cost function and the parameters. The optimization process was conducted several times, considering the random generator within the algorithm. The simulation results show the probable shortest path with a value of about 752 meters so that the use of fossil fuels in waste transport vehicles can be more efficient. The results show that the algorithm can automatically recommend the minimized path length to collect waste.

ВДОСКОНАЛЕННЯ ERG-СИСТЕМИ УПРАВЛІННЯ ПІДПРИЄМСТВАМИ МОРЕГОСПОДАРСЬКОГО КОМПЛЕКСУ

In the article, we analyzed the ERG management system of enterprises of the maritime complex, the existing problems and prospects for the development of modern management systems in the changing challenges of today. At the present stage of development there is a need to support and improve the management system of maritime and river transport enterprises. The development of the maritime complex depends on the effective organization of the management system. The purpose of the article is to improve the ERG management system of the enterprises of the maritime complex. The management system of maritime transport enterprises is correlated with the management of the enterprise. Business owners, the project steering committee and the project manager develop a hierarchy and determine who is responsible for each component of the system implementation. It is unusual to find in-house IT staff that are aware of all the intricacies of ERP, so relying solely on in-house IT staff slows down the implementation process. Third-party consultants have experience with previous implementations in other organizations that work for them, so they understand what worked and what didn’t in those other implementations. However, the growing need of enterprises for specialized software can be fully met by ERP-management systems of enterprises of the maritime complex. We believe that this is one of the most useful platforms in which an investor can and should invest, because its use provides a number of advantages: formalization of business processes, automatic control over their implementation, and convenient access to information needed by employees, partners, and customers to making informed decisions. As for the shortcomings of the ERP system, they are the same as in all complex automation systems – it is data security and the need for a powerful server. The effectiveness of the implementation of the ERP system by enterprises of the maritime complex in view of the fact that manufacturers of enterprise resource management systems offer a wide range of products aimed at solving a variety of problems, prospects for further research may be market analysis of ERP systems.

Reduction of Uncertainties for Safety Assessment of Automated Driving Under Parallel Simulations

Many achievements concerning developments in the field of automated driving have been made. However, automated driving still faces the challenge of safety validation. Conventional methods are not suitable any more for this highly complex automation system. Therefore, the method named Virtual Assessment of Automation in Field Operation (VAAFO) is motivated. In this approach, automated driving system has no access to actuators but rather runs parallel to the human driver. Consequently, this approach is divided into two modules: online trajectory comparison and offline safety assessment. This paper focuses on the second module, in which uncertainties in world model are reduced and then the safety of Automated Vehicle (AV) is evaluated. Retrospective post-processing combined with Joint Integrated Probabilistic Data Association (JIPDA) tracker is put forward to reduce existence uncertainties. State uncertainties are reduced by an Unscented Rauch-Tung-Striebel smoother (URTSS). Furthermore, inverse TTC and remaining lateral distance are utilized to assess the safety of AV in the corrected world model. The results demonstrate that retrospective post-processing combined with JIPDA can reduce existence uncertainties greatly. URTSS is very useful for reducing state uncertainties. The studied case illustrates that the safety of AV can be assessed by parallel running and critical scenarios are found accordingly.

Совершенствование алгоритмов распознавания типов объектов в системах управления с применением нечеткой логики в условиях неопределенности

Introduction. The basis of modern information technology for complex automation systems in the face of uncertainty is the principle of situational management. Such technologies include the following: expert systems, neural network structures, fuzzy logic and associative memory. The development of intelligent technologies is associated with the combination of various methods of processing knowledge. This area provides increased performance, reduced knowledge. It is supposed that fuzzy logic and expert systems can be combined. Aim. Consider the task of improving recognition algorithms in control systems by combining optimal filtering methods and fuzzy logic at the stage of secondary processing of information about object parameters. Materials and methods. For preliminary processing, we will consider Kalman filters (FC), for the implementation of which in real time less computing resources are required in comparison with guaranteed estimation algorithms. In the proposed method, we apply FC Bank. We carry out mathematical modeling in the Mathcad 14. In the FuzzyTECH software environment, a fuzzy project “Recognizing the type of an object” is being developed. Development of a fuzzy model takes place in several stages. Firstly, the presentation of input variables in terms of linguistic variables. Secondly, relying on expert knowledge, we define terms for linguistic variables. Thirdly, the creation of a block of rules. Fourth, a study of the created fuzzy project. Results. The mathematical modeling of the FC in the devices for tracking the parameters of objects in the process of recognition in the Mathcad 14 software environment showed the possibility of using a filter bank in the considered devices. Algorithms for recognizing object types using fuzzy logic have been created and studied. Conclusion. The created control system algorithms, combining Kalman filtering and fuzzy logic, increase the efficiency of the recognition system.

Применение комплексной системы автоматизации медицинского учреждения

Применение комплексной системы автоматизации медицинского учреждения

Modeling of Petri-Net-based control algorithms for the simulation-based improvement of the planning process of building energy systems

The increasing integration of renewable forms of energy into building energy systems raises the need for the use of more complex energy conversion and distribution systems. These are often equipped with complex automation systems, which require methods for structured development of control algorithms. In practice, textual descriptions of control algorithms represent a considerable source of failures. The digitization of the planning process is a core element in facilitating control development and supporting the engineering in the process automation. With regard to the digitization of the planning process, we have introduced the MODI-method in previous work. This method allows structured control development in early stages of the planning process and can be extended by performing simulations, i.e. an algorithm implemented as a Petri-Net. In this paper, we investigate the integration of this method into the simulation-based planning and an approach to model an algorithm based on Petri-Net. The case study shows the functionality of this method and the modeling approach. In future work, the MODI-method will be compared with other control strategies and applied in complex systems for further development.

Advanced morphological approach to finding novel solutions for automated finishing of GTE blades

This article deals with the search, structural analysis, synthesis and modelling of complex automatic systems during preliminary design phase on a basis of advanced morphological approach. The research aims were to develop and use an advanced morphological approach, a technique for modelling the new systems for automated finishing of gas turbine engine (GTE) blades. The approach is based on cluster analysis, set theory, set of rules and maximization a gain by the innovative automation systems potential. Based on this study, the proposed method shows a meaningful potential compared to the methods presently used.

Ways of reduction of pollution of an environment by ship power installations

In the report are discussed ways of reduction of pollution of an environment by ship power installations. Among them it is necessary to select optimization of regimes of operations of main traditional ship sources of the electric power, the installation of systems of utilization of refuse energy of the exhaust gases and cooling water from main and auxiliary engines, application of new types of sources of the electric power and the using of complex automation and control systems for exhaust gases and for selecting of regimes main engine, auxiliary engine, utilize boiler, auxiliary boiler, shaft generator.