Wyszukiwarka
dr hab. inż. Michał Grochowski
Zatrudnienie
- Kierownik katedry w Katedra Inteligentnych Systemów Sterowania i Wspomagania Decyzji
- Profesor uczelni w Katedra Inteligentnych Systemów Sterowania i Wspomagania Decyzji
Publikacje
Filtry
wszystkich: 71
Katalog Publikacji
Rok 2021
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
Rok 2015
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublikacjaIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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Advanced Control Structures of Turbo Generator System of Nuclear Power Plant
PublikacjaIn the paper a synthesis of advanced control structures of turbine and synchronous generator for nuclear power plant working under changing operating conditions (supplied power level) is presented. It is based on the nonlinear models of the steam turbine and synchronous generator cooperating with the power system. Considered control structure consists of multi-regional fuzzy control systems with local linear controllers, including...
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ANALIZA MOŻLIWOŚCI ZASTOSOWANIA STEROWANIA PREDYKCYJNEGO TURBINĄ PAROWĄ ELEKTROWNI JĄDROWEJ
PublikacjaArtykuł przedstawia wyniki wstępnej analizy możliwości zastosowania sterowania predykcyjnego MPC turbiną parową elektrowni jądrowej. Tradycyjnie przyjmuje się, że turbina pracuje w jednym punkcie pracy odpowiadającym jej mocy nominalnej, co pozwala na stosowanie klasycznych regulatorów PID. Synteza sterowania dla warunków zmiennego punktu pracy wymaga uwzględnienia nieliniowego charakteru procesów turbiny oraz możliwości naruszania...
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BADANIE EFEKTYWNOŚCI WYKRYWANIA ANOMALII PROCESOWYCH W DZIAŁANIU TURBINY PAROWEJ ELEKTROWNI JĄDROWEJ PRZY POMOCY METOD WIELOWYMIAROWEJ ANALIZY STATYSTYCZNEJ
PublikacjaW artykule przedstawiono analizę możliwości wykrywania anomalii procesowych w działaniu turbiny parowej elektrowni jądrowej przy pomocy metod wielowymiarowej analizy statystycznej. Zasymulowano symptomy dwóch rodzajów uszkodzeń turbiny parowej tj. uderzenie wodne oraz, wyciek pary z zaworu części niskoprężnej. Jako narzędzie diagnostyczne wykorzystano Metodę Składników Podstawowych PCA (z ang. Principal Component Analysis). Jako...
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Dynamic model of nuclear power plant steam turbine
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Dynamic model of nuclear power plant turbine
PublikacjaThe paper presents the dynamic multivariable model of Nuclear Power Plant steam turbine. Nature of the processes occurring in a steam turbine causes a task of modeling it very difficult, especially when this model is intended to be used for on-line optimal process control (model based) over wide range of operating conditions caused by changing power demand. Particular property of developed model is that it enables calculations...
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Optimising approach to designing kernel PCA model for diagnosis purposes with and without a priori known data reflecting faulty states
PublikacjaFault detection plays an important role in advanced control of complex dynamic systems since precise information about system condition enables efficient control. Data driven methods of fault detection give the chance to monitor the plant state purely based on gathered measurements. However, they especially nonlinear, still suffer from a lack of efficient and effective learning methods. In this paper we propose the two stages learning...
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Pipeline system for heat transportation from nuclear power plant — An optimizing approach
Publikacja
Rok 2018
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Analiza istotności cech znamion skórnych dla celów diagnostyki czerniaka złośliwego
PublikacjaPomimo dynamicznego rozwoju metod uczenia maszynowego i ich wdrażania do praktyki lekarskiej, automatyczna analiza znamion skórnych wciąż jest nierozwiązanym problemem. Poniższy artykuł proponuje zastosowanie algorytmu ewolucyjnego do zaprojektowania, wytrenowania i przetestowania całych populacji klasyfikatorów (sztucznych sieci neuronowych) oraz ich iteracyjnego udoskonalania w każdej kolejnej populacji, w celu osiągnięcia jak...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Decision support system for design of long distance heat transportation system
PublikacjaDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). The paper proposes a Decision Support System (DSS) for optimized selection of design and operating parameters of a long distance Heat Transportation System (HTS). The method allows for evaluation of feasibility and effectiveness...
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Diagnozowanie stanu retinopatii cukrzycowej przy pomocy głębokich sieci neuronowych
PublikacjaW referacie opisano problem wykrywania oraz klasyfikacji stanu retinopatii cukrzycowej ze zdjęć dna oka przy pomocy głębokich sieci neuronowych. Retinopatia cukrzycowa jest chorobą oczu często występującą u osób z cukrzycą. Nieleczona prowadzi do uszkodzenia wzroku, a nawet ślepoty. W pracy badawczej opracowano system wykrywania retinopatii cukrzycowej na podstawie zdjęć dna oka. Opracowana sieć neuronowa przypisuje stan choroby...
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Optimal selection of input features and an acompanying neural network structure for the classification purposes - skin lesions case study
PublikacjaMalignant melanomas are the most deadly type of skin cancers however detected early enough give a high chances for successful treatment. The last years saw the dynamic growth of interest of automatic computer-aided skin cancer diagnosis. Every month brings new research results on new approaches to this problem, new methods of preprocessing, new classifiers, new ideas to follow etc. In particular, the rapid development of dermatoscopy,...
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
Publikacja
Rok 2017
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Application of data driven methods in diagnostic of selected process faults of nuclear power plant steam turbine
PublikacjaArticle presents a comparison of process anomaly detection in nuclear power plant steam turbine using combination of data driven methods. Three types of faults are considered: water hammering, fouling and thermocouple fault. As a virtual plant a nonlinear, dynamic, mathe- matical steam turbine model is used. Two approaches for fault detection using one class and two class classiers are tested and compared.
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Computed aided system for separation and classification of the abnormal erythrocytes in human blood
PublikacjaThe human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Intelligent system supporting diagnosis of malignant melanoma
PublikacjaMalignant melanomas are the most deadly type of skin cancers. Early diagnosis is a key for successful treatment and survival. The paper presents the system for supporting the process of diagnosis of skin lesions in order to detect a malignant melanoma. The paper describes the development process of an intel-ligent system purposed for the diagnosis of malignant melanoma. Presented sys-tem can be used as a decision support system...
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Multicriteria Optimization Approach to Design and Operation of District Heating Supply System over its Life Cycle
PublikacjaDistrict Heating (DH) systems are commonly supplied using local heat sources. Nowadays, modern insulation materials allow for effective and economically viable heat transportation over long distances (over 20 km). In the paper a method for optimized selection of design and operating parameters of long distance Heat Transportation System (HTS) is proposed. The method allows for evaluation of feasibility and effectivity of heat transportation...
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Nuclear Power Plant Steam Turbine - Modeling for Model Based Control Purposes
PublikacjaThe nature of the processes taking place in a nuclear power plant (NPP) steam turbine is the reason why their modeling is very difficult, especially when the model is intended to be used for on-line optimal model based process control over a wide range of operating conditions, caused by changing electrical power demand e.g. when combined heat and power mode of work is utilized. The paper presents three nonlinear models of NPP steam...
Rok 2023
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Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
PublikacjaThis paper provides the first review to date which gathers, describes, and assesses, to the best of our knowledge, all available publications on automating cerebral microbleed (CMB) detection. It provides insights into the current state of the art and highlights the challenges and opportunities in this topic. By incorporating the best practices identified in this review, we established guidelines for the development of CMB detection...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
Rok 2012
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublikacjaKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Modelowanie, sterowanie i wizualizacja quadrocoptera
PublikacjaArtykuł przedstawia podejście do budowy modelu matematycznego quadrocoptera. Głównym celem budowy modelu było zaprojektowanie odpowiedniego sterowania obiektu oraz analiza jego zachowania się w różnych sytuacjach. Jako założenie przyjęto budowę modelu, systemu sterowania oraz wszelkich towarzyszących algorytmów w otwartym środowisku programistycznym, co pozwoli na późniejszą ich implementację w rzeczywistym obiekcie, bez konieczności...
Rok 2019
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Deep neural network architecture search using network morphism
PublikacjaThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublikacjaMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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MACHINE LEARNING SYSTEM FOR AUTOMATED BLOOD SMEAR ANALYSIS
PublikacjaIn this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones - the healthy blood cells (erythrocytes) and the pathologic (echinocytes). The separated blood cells are analyzed in terms of their most important features by the eigenfaces method. The features are the...
Rok 2016
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Evolving neural network as a decision support system — Controller for a game of “2048” case study
PublikacjaThe paper proposes an approach to designing the neuro-genetic self-learning decision support system. The system is based on neural networks being adaptively learned by evolutionary mechanism, forming an evolved neural network. Presented learning algorithm enables for a selection of the neural network structure by establishing or removing of connections between the neurons, and then for a finding the beast suited values of the network...
Rok 2020
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
Rok 2008
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Hierarchical predictive control of integrated wastewater treatment systems
PublikacjaThe paper proposes an approach to designing the control structure and algorithms for optimising control of integrated wastewater treatment plant-sewer systems (IWWTS) under a full range of disturbance inputs. The optimised control of IWWTS allows for significant cost savings, fulfilling the effluent discharge limits over a long period and maintaining the system in sustainable operation. Due to the specific features of a wastewater...
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Leakage detection and localisation in drinking water distributionnetworks by MultiRegional PCA
PublikacjaMonitoring is one of the most important steps in advanced control of complex dynamic systems. Precise information about systems behaviour, including faults indicating, enables for efficient control. The paper describes an approach to detection and localisation of pipe leakage in Drinking Water Distribution Systems (DWDS) representing complex and distributed dynamic system of large scale. Proposed MultiRegional Principal Component...
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Lokalizacja wycieków w sieciach dystrybucji wody
PublikacjaSieć wodociągowa, podobnie jak każdy duży obiekt, w którym prowadzony jest złożony proces, wymaga odpowiedniego systemu monitorującego. Jednym z poważnych i wciąż aktualnych problemów są niekontrolowane straty wody w sieci. Jednym z możliwych sposobów szybkiego wykrywania wycieków z sieci jest umieszczenie czujników pomiarowych na każdej rurze i w każdym węźle. Oczywistym jest, że takie rozwiązanie wiaże się z olbrzymimi kosztami....
Rok 2022
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How high-tech solutions support the fight against IUU and ghost fishing: a review of innovative approaches, methods, and trends
PublikacjaIllegal, Unreported, and Unregulated fishing is a major threat to human food supply and marine ecosystem health. Not only is it a cause of significant economic loss but also its effects have serious long-term environmental implications, such as overfishing and ocean pollution. The beginning of the fight against this problem dates since the early 2000s. From that time, a number of approaches and methods have been developed and reported....
Rok 2004
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Intelligent control of integrated wastewater treatment system under full range of operating conditions.
PublikacjaW rozprawie przedstawiono struktury i algorytmy pozwalające na efektywne sterowanie łącznym usuwaniem azotu, fosforu i związków węgla w zintegrowanym systemie ściekowym, w szerokim zakresie jego obciążeń. Obiektem badań była oczyszczalnia ścieków w Kartuzach. Do sterowania tak złożonym i skomplikowanym systemem zaproponowano trójpoziomową i trójwarstwową, hierarchiczną strukturę sterowania. Poziomy sterowania (Nadzorujący, Optymalizacyjny,...
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Intelligent control structure for control of integrated wastewater systems.
PublikacjaArtykuł przedstawia podejście do tworzenia struktury sterowania zintegrowanym systemem oczyszczania ścieków (sieć kanalizacyjna- oczyszczalnia ścieków), w pełnym zakresie jego obciążeń hydraulicznych. System sterowania jest hierarchicznie zdekomponowany, tworząc wielopoziomową-wielowarstwową. Główną technologią sterowania wykorzystaną na poziomie optymalizacyjnym jest krzepkie sterowanie predykcyjne (RMPC) przy obecności niepewności...
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Intelligent Control Structure for Control of Integrated Wastewater Systems
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Model Predictive Controller for Integrated Wastewater Treatment System
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Model predictive controller for integrated wastewater treatment systems.
PublikacjaSterowanie optymalizujace systemem oczyszczania ścieków (WWTS) pozwala na zmniejszenie kosztów operacyjnych przy jednoczesnym spełnieniu narzuconych ograniczeń na wypływające ścieki, jednak wymaga zaawansowanych technologii sterowania. Sterowanie predykcyjne z modelem (MPC) jest bardzo użyteczną technologią sterowania takimi systemami. MPC doskonale radzi sobie z obecnością ogrniczeń na wielkości wyjściowe, wielowymiarowością problemu...
Rok 2011
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublikacjaMonitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
Publikacja
Rok 2005
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Miękko przełączane sterowanie predykcyjne w zastosowaniu do systemów ściekowych
PublikacjaNie zawsze jest możliwe sterowanie układami czy systemami przy pomocy jednej uniwersalnej strategii sterowania pozwalającej na efektywne sterowanie w pełnym zakresie warunków operacyjnych. Istnieje wówczas potrzeba stosowania dwóch lub większej liczby układów sterowania w zależności od stanu układu bądź postawionych przed nim celów. To implikuje konieczność znalezienia mechanizmu umożliwiającego ich przełączanie. Nie zawsze jest...
Rok 2014
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Modelling of Nuclear Power Plant Steam Turbine
PublikacjaThe paper describes the approach to a Nuclear Power Plant steam turbine modelling which would enable on-line optimal process control (model based) and diagnosis over wide range of operating conditions caused by changing power demand. Presented model is static, multivariable and nonlinear. Such model enables analyzing the heat cogeneration aspects. Developed model is validated and verified by using archive data gained from researches...
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Modelling of Nuclear Power Plant Steam Turbine
PublikacjaThe paper describes the approach to a Nuclear Power Plant steam turbine modelling which would enable on-line optimal process control (model based) and diagnosis over wide range of operating conditions caused by changing power demand. Presented model is static, multivariable and nonlinear. Such model enables analyzing the heat cogeneration aspects. Developed model is validated and verified by using archive data gained from researches...
Rok 2007
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MultiRegional PCA for leakage detection and localisation in DWDS - approach
PublikacjaMonitoring is one of the most important parts in advanced control of complex dynamic systems. Information about systems behavior, including failures indicating, enables for efficient control. The chapter describes an approach to detection and localisation of pipe leakage in Drinking Water Distribution Systems (DWDS) representing complex and distributed dynamic system of large scale. Proposed MultiRegional Principal Component Analysis...
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MultiRegional PCA for leakage detection and localisation in DWDS - Chojnice case study
PublikacjaThis chapter considers pipe leakage detection and localisation in Drinking Water Distribution Systems (DWDS) by using a novel approach the MultiRegional Principal Component Analysis (MR-PCA). The MR-PCA is an extension of well known PCA method. The main idea of MR-PCA consists in designing a number of regional PCA models and analysing their responses caused by the pipe faults. Moreover, DWDS is decomposed into suitable subnetworks...
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