New Evolving Fuzzy System Algorithms Using Dynamic Constraint

An information granule has to be translated into significant frameworks of granular computing to realize interpretability-accuracy tradeoff. These two objectives are in conflict and constitute an open problem. Evolving information granules is a significant concept of granular computing which consider coarser partition (or lower granule i.e. higher error) to fine partition (or higher granule i.e. lower error). While this error reducing granular framework is considered, interpretability constraint is the factor to improve the tradeoff between interpretability and accuracy. Furthermore, overfitting and underfitting criteria are noteworthy to be considered while evolving process continues. In addition, the stability-plasticity tradeoff is another significant consideration to design a granular framework in order to find a consistent and up-to-date fuzzy information granule method. A new operational framework namely evolving fuzzy system (EFS) is developed in this research work, which ensures a compromise between interpretability and reasonable accuracy. Three models are designed based on EFS namely, evolving structural fuzzy system (ESFS), evolving output-context fuzzy system (EOCFS) and evolving information granule (EIG). The evolving information granule is initiated with the first information granule by translating the knowledge of the entire output domain. The initial information granule is considered as an underfitting state with a high approximation error. Then, the EFS starts evolving in the information granule by partitioning the output (or input) domain and uses a dynamic constraint to maintain semantic interpretability in the output (or input) contexts. The outcome on the synthetic and real-world data using the EFS shows the effectiveness of the proposed system, which outperforms state-of-the-art methods. The EFS needs less number of rules (i.e. high interpretable) and low error (i.e. high accuracy) with respect to the existing methods. For example, if the proposed EIG method is applied to the Nakanishi‘s nonlinear system then four fuzzy rules and 0.142 mean square error (MSE) are found. Furthermore, the EIG outperforms if compared with the existing methods. The important criterion in the EFS is to determine the prominent distinction (output or input context) and realize the distinct information granule that depicts the semantics at the fuzzy partition level. The EFS tends to evolve toward the lower error region and realizes the effective rule base by avoiding overfitting. Furthermore, the evolving overfitting index and uncertainty controller of the self-adaptive process are dynamically attained from past and current knowledge. Therefore, effective rule base is the balanced fuzzy model of the approximated system. Within the proposed three models (ESFS, EOCFS and EIG), EIG has the significant ability to tradeoff between interpretability and accuracy, while the proposed ESFS method shows the highly interpretable granular framework which also realizes the interpretability-accuracy tradeoff

An examination of thermal features' relevance in the task of battery-fault detection

Uninterruptible power supplies (UPS), represented by lead-acid batteries, play an important role in various kinds of industries. They protect industrial technologies from being damaged by dangerous interruptions of an electric power supply. Advanced UPS monitoring performed by a complex battery management system (BMS) prevents the UPS from sustaining more serious damage due to its timely and accurate battery-fault detection based on voltage metering. This technique is very advanced and precise but also very expensive on a long-term basis. This article describes an experiment applying infrared thermographic measurements during a long term monitoring and fault detection in UPS. The assumption that the battery overheat implies its damaged state is the leading factor of our experiments. They are based on real measured data on various UPS battery sets and several statistical examinations confirming the high relevancy of the thermal features with mostly over 90% detection accuracy. Such a model can be used as a supplement for lead-acid battery based UPS monitoring to ensure their higher reliability under significantly lower maintenance costs.Web of Science82art. no. 18

Особенности применения технологии Smart Grid в системах мониторинга и диагностирования теплоэнергетических объектов

Рассмотрены возможности использования «умных сетей» в системах мониторинга и диагностики теплоэнергетического оборудования. Проанализированы причины неисправностей и аварийных ситуаций оборудования генерации, транспортировки и потребления тепловой энергии. Рассмотрены основные методы неразрушающего контроля, применимые для диагностики технических узлов, и информативные сигналы, которые возникают в процессе эксплуатации энергетического оборудования. Предложены структуры функционирования теплоэнергетического оборудования для применения технологии Smart Grid в системах мониторинга и диагностирования соответствующих иерархических уровней. Исследованы основные преимущества энергетических сетей на базе технологии Smart Grid перед традиционными сетями. Разработана структура многоуровневой системы диагностики теплоэнергетического оборудования с возможностью использования проводных и беспроводных каналов передачи информаци

PENINGKATAN KOMPETENSI MELALUI PELATIHAN INSTALASI LISTRIK DALAM DIKLAT PEMBERDAYAAN MASYARAKAT

Abstrak: Teknisi yang tidak memiliki kualifikasi di bidang instalasi listrik dapat menghasilkan instalasi yang tidak aman. Untuk mengatasi kondisi tersebut diperlukan peningkatan keterampilan dari teknisi instalasi listrik melalui pendidikan non formal berbasis pada pengabdian kepada masyarakat (PKM) yaitu Diklat Pemberdayaan Masyarakat (DPM) Instalasi listrik. Tujuan dari pelaksanaan PKM adalah menghasilkan sumber daya manusia yang memiliki kualifikasi dalam bidang instalasi listrik. Peserta DPM Instalasi Listrik pada bulan juni 2022 ada sejumlah 20 peserta dari SMK Negeri 1 Madiun yang berlangsung dari tanggal 20 Juni 2022 sampai dengan 22 Juni 2022. Evaluasi diklat dilaksanakan dengan pengamatan secara langsung kemampuan peserta untuk menghasilkan hasil instalasi listrik yang dapat menyalakan beban lampu. Rata-rata peningkatan kompetensi dari peserta diklat instalasi listrik adalah 29,5% dari 5 (lima) indikator pengamatan yaitu pengetahuan akan komponen peralatan instalasi listrik, fungsi setiap komponen, pengetahuan akan simbol komponen instalasi listrik, mampu membaca dan memahami wiring instalasi listrik, serta memiliki kompetensi dalam intalasi listrik. Abstract: Technicians who are not qualified in the field of electrical installations can result in unsafe and reliable installations. To overcome this condition, it is necessary to increase the skills of electrical installation technicians through non-formal education based on Pengabdian Kepada Masyarakat (PKM), namely Diklat Pemberdayaan Masyarakat (DPM) Instalasi listrik. The aim of implementing PKM is to produce qualified human resources in the field of electrical installation. There were 20 participants in the Electrical Installation DPM in June 2022 from SMK Negeri 1 Madiun which took place from June 20 2022 to June 22 2022. The training evaluation was carried out by directly observing the participants' ability to produce electrical installations that can light up the lamp. The average competency increase of electrical installation training participants was 29.5% as seen from 5 (five) observation indicators, namely knowledge of electrical installation equipment components, function of each component, knowledge of electrical installation component symbols, ability understand electrical installation wiring, and had competency in electrical installations.

Аналіз методів діагностування теплоенергетичних об'єктів

В статье рассмотрены преимущества и недостатки разрушительных и неразрушающих методов контроля. Проведен анализ метода в неразрушающего контроля, их особенностей, характеристик и необходимого оборудования. Предложено оптимальное сочетание различных по своей природе методов НК.В статті розглянуті переваги та недоліки руйнівних та неруйнівних методів контролю. Проведено аналіз методів неруйнівного контролю, їх особливостей, параметрів та необхідного обладнання. Запропоновано оптимальне поєднання різних за своєю природою методів НК

Mantenimiento Predictivo: Historia, una guía de implementación y enfoques actuales

Debido al aumento del número de sensores utilizados en las plantas de producción, la posibilidad de obtener datos de estas ha incrementado considerablemente. Esto conlleva la posibilidad de detectar fallos antes de que estos ocurran y futuras paradas que afecten a las plantas de producción. Las tecnologías de mantenimiento predictivo permiten predecir eventos futuros, convirtiéndolas en herramientas para afrontar los retos que surjan en los mercados competitivos. Esta tesis está dividida en cinco partes. La primera, describe el mantenimiento a lo largo de la historia, mientras que la segunda está enfocada en el mantenimiento predictivo. El tercer punto es una guía de implementación de un programa de mantenimiento predictivo para cualquier organización interesada en el tema. Finalmente, las dos últimas partes hacen referencia a los enfoques más comunes en inteligencia artificial donde se explican técnicas importantes como “Artificial Neural Networks” y “Machine Learning”, describiendo algunos ejemplos donde fueron usadas para realizar mantenimiento predictivo.Departamento de Organización de Empresas y Comercialización e Investigación de MercadosHochschule Albstadt-SigmaringenGrado en Ingeniería en Organización Industria

Context-Enabled Visualization Strategies for Automation Enabled Human-in-the-loop Inspection Systems to Enhance the Situation Awareness of Windstorm Risk Engineers

Insurance loss prevention survey, specifically windstorm risk inspection survey is the process of investigating potential damages associated with a building or structure in the event of an extreme weather condition such as a hurricane or tornado. Traditionally, the risk inspection process is highly subjective and depends on the skills of the engineer performing it. This dissertation investigates the sensemaking process of risk engineers while performing risk inspection with special focus on various factors influencing it. This research then investigates how context-based visualizations strategies enhance the situation awareness and performance of windstorm risk engineers. An initial study investigated the sensemaking process and situation awareness requirements of the windstorm risk engineers. The data frame theory of sensemaking was used as the framework to carry out this study. Ten windstorm risk engineers were interviewed, and the data collected were analyzed following an inductive thematic approach. The themes emerged from the data explained the sensemaking process of risk engineers, the process of making sense of contradicting information, importance of their experience level, internal and external biases influencing the inspection process, difficulty developing mental models, and potential technology interventions. More recently human in the loop systems such as drones have been used to improve the efficiency of windstorm risk inspection. This study provides recommendations to guide the design of such systems to support the sensemaking process and situation awareness of windstorm visual risk inspection. The second study investigated the effect of context-based visualization strategies to enhance the situation awareness of the windstorm risk engineers. More specifically, the study investigated how different types of information contribute towards the three levels of situation awareness. Following a between subjects study design 65 civil/construction engineering students completed this study. A checklist based and predictive display based decision aids were tested and found to be effective in supporting the situation awareness requirements as well as performance of windstorm risk engineers. However, the predictive display only helped with certain tasks like understanding the interaction among different components on the rooftop. For remaining tasks, checklist alone was sufficient. Moreover, the decision aids did not place any additional cognitive demand on the participants. This study helped us understand the advantages and disadvantages of the decision aids tested. The final study evaluated the transfer of training effect of the checklist and predictive display based decision aids. After one week of the previous study, participants completed a follow-up study without any decision aids. The performance and situation awareness of participants in the checklist and predictive display group did not change significantly from first trial to second trial. However, the performance and situation awareness of participants in the control condition improved significantly in the second trial. They attributed this to their exposure to SAGAT questionnaire in the first study. They knew what issues to look for and what tasks need to be completed in the simulation. The confounding effect of SAGAT questionnaires needs to be studied in future research efforts