Wyniki wyszukiwania - BazTech

1

Non-invasive Ultrasound Doppler Effect Based Method of Liquid Flow Velocity Estimation in Pipe

Biernacki Paweł, Gmyrek Stanisław, Magiera Władysław

Archives of Acoustics

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2023

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Vol. 48, No. 1

141--148

EN

This paper discusses the estimation of flow velocity from a multi-sensor scenario. Different estimation methods were used, which allow the effective measurement of the actual Doppler shift in a noisy environment, such as water with air bubbles, and on this basis the estimation of the flow velocity in the pipe was calculated. Information fusion is proposed for the estimates collected. The proposed approach focuses on the density of the fluid. The proposed method is capable of determining the flow velocity with high accuracy and small variations. Simulation results for plastic and steel (both galvanized and non-galvanized) pipes show the possibility of accurate fluid flow measurements without the need for sensors inside the pipe.

2

A fault location strategy based on information fusion and CODAS algorithm under epistemic uncertainty

Duan Rongxing, Chen Li, He Jiejun, Huang Shujuan

Eksploatacja i Niezawodność

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2022

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Vol. 24, no. 3

478--488

EN

Application of new technology in modern systems not only substantially improves the performance, but also presents a severe challenge to fault location of these systems. This paper presents a new fault location strategy for maintenance personnel to recover them based on information fusion and improved CODAS algorithm. Firstly, a fault tree is adopted to develop the failure model of a complex system, and failure probability of components is determined by expert evaluations to handle the uncertainty problem. Moreover, a fault tree is converted into an evidence network to obtain importance degrees, which are used to construct a diagnostic decision table together with the risk priority number. Additionally, these results are updated to optimize the maintenance process using sensor information. A novel dynamic location strategy is designed based on interval CODAS algorithm and optimal fault location strategy can be obtained. Finally, a real system is analyzed to demonstrate the feasibility of the proposed maintenance strategy.

3

Information fusion method of multichannel nanosensors based on neural network

Li Chaoke

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2022

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Vol. 70, nr 2

art. no. e140258

EN

Information fusion approaches have been commonly used in multi sensor environments for the fusion and grouping of data from various sensors which is used further to draw a meaningful interpretation of the data. Traditional information fusion methods have limitations such as high time complexity of fusion processes and poor recall rate. In this work, a new multi-channel nano sensor information fusion method based on a neural network has been designed. By analyzing the principles of information fusion methods, the back propagation based neural network (BP-NN) is devised in this work. Based on the design of the relevant algorithm flow, information is collected, processed, and normalized. Then the algorithm is trained, and output is generated to achieve the fusion of information based on multi-channel nano sensor. Moreover, an error function is utilized to reduce the fusion error. The results of the present study show that compared with the conventional methods, the proposed method has quicker fusion (integration of relevant data) and has a higher recall rate. The results indicate that this method has higher efficiency and reliability. The proposed method can be applied in many applications to integrate the data for further analysis and interpretations.

4

Multi-View Attention-based Late Fusion (MVALF) CADx system for breast cancer using deep learning

Iftikhar Hina, Shahid Ahmad Raza, Raza Basit, Khan Hasan

Machine Graphics and Vision

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2020

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Vol. 29, No. 1/4

55--78

EN

Breast cancer is a leading cause of death among women. Early detection can significantly reduce the mortality rate among women and improve their prognosis. Mammography is the first line procedure for early diagnosis. In the early era, conventional Computer-Aided Diagnosis (CADx) systems for breast lesion diagnosis were based on just single view information. The last decade evidence the use of two views mammogram: Medio-Lateral Oblique (MLO) and Cranio-Caudal (CC) view for the CADx systems. Most recent studies show the effectiveness of four views of mammogram to train CADx system with feature fusion strategy for classification task. In this paper, we proposed an end-to-end Multi-View Attention-based Late Fusion (MVALF) CADx system that fused the obtained predictions of four view models, which is trained for each view separately. These separate models have different predictive ability for each class. The appropriate fusion of multi-view models can achieve better diagnosis performance. So, it is necessary to assign the proper weights to the multi-view classification models. To resolve this issue, attention-based weighting mechanism is adopted to assign the proper weights to trained models for fusion strategy. The proposed methodology is used for the classification of mammogram into normal, mass, calcification, malignant masses and benign masses. The publicly available datasets CBIS-DDSM and mini-MIAS are used for the experimentation. The results show that our proposed system achieved 0.996 AUC for normal vs. abnormal, 0.922 for mass vs. calcification and 0.896 for malignant vs. benign masses. Superior results are seen for the classification of malignant vs benign masses with our proposed approach, which is higher than the results using single view, two views and four views early fusion-based systems. The overall results of each level show the potential of multi-view late fusion with transfer learning in the diagnosis of breast cancer.

5

Hardness identification of rock based on multi-sensor information fusion during the process of roadway tunnelling

Wang H., Lu S., Huang M., Zhao X.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2020

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Vol. 68, nr 6

1301--1309

EN

In this paper, a new dynamic model was proposed for identifying the rock hardness during the process of roadway tunnelling, thereby regulating the speed of the driving motor and the torque of the cutting head. The presented identification model establishes a multi-information feature database containing vibration signals in the y-axis, acoustic emission signals, cutting current signals, and temperature signals. Subsequently, we obtain the membership functions (MFs) of the given multiple signals with the amount of feature samples according to the principle of minimum fuzzy entropy. Furthermore, a rock hardness identification model was established based on multi-sensor information fusion and Dempster-Shafer (D-S) evidence theory. To prove the accuracy of the proposed model, an identification experiment was carried out through the cutting of a poured mixed rock specimen with five grades of hardness. As a result, the proposed identification model recognizes the rock hardness accurately for fifteen sampling points, which indicates the significance of the method with regard to the dynamic identification of rock hardness during the process of roadway tunnelling, and further provides data support for adjusting the speed of the cutting head adaptively, thereby achieving high efficiency tunnelling.

6

Fast BF-ICrA Method for the Evaluation of MO-ACO Algorithm for WSN Layout

Dezert Jean, Fidanova Stefka, Tchamova Albena

Annals of Computer Science and Information Systems

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2020

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Vol. 21

241--249

EN

In this paper, we present a fast Belief Function based Inter-Criteria Analysis (BF-ICrA) method based on the canonical decomposition of basic belief assignments defined on a dichotomous frame of discernment. This new method is then applied for evaluating the Multiple-Objective Ant Colony Optimization (MO-ACO) algorithm for Wireless Sensor Networks (WSN) deployment.

7

Enhancement of Damage Detectability in Aircraft Structures Using the Fusion of NDT Results

Zapłotny M., Katunin A., Dragan K.

Fatigue of Aircraft Structures

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2017

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Iss. 9

55--74

EN

Following the damage tolerance philosophy in aircraft design and operation, one of the most significant stages of maintenance is non-destructive testing of structures. It is, therefore, essential to use testing methods sensitive to particular damage types occurring in aircraft structures during operation. In this paper, the authors present a study on selection and comparison of methods of information fusion applied to testing the results of inspection of composite structures used in aircraft elements, obtained using various ultrasonic methods. The presented approach of fusion of ultrasonic scans allows for enhancement of damage detection and identification due to the presence of different parts of information about detected damage obtained from different initial information sources in a single resulting set. Such an approach can be helpful at the decision-making stage during inspection of aircraft elements and structures. Besides the methodology, the GUI-based software for performing fusion of various types of ultrasonic data is presented.

8

Potential Contour Ensembles

Tomczyk A.

Schedae Informaticae

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2015

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Vol. 24

113--121

EN

In the paper a contour ensemble image segmentation concept is presented. It bases on the previously observed relationship between contours and classifiers. Because of the specificity of the active contour segmentation the method requires a special procedure to obtain ensemble members with desired properties. In this work it is achieved by early stopping of randomized optimization algorithm. The results of the method are illustrated with a practical problem of heart ventricle segmentation by means of active potential contours. Automatically found contours may be of use in a process of pulmonary embolism diagnosis.

9

Songs Recognition Using Audio Information Fusion

Biernacki P.

International Journal of Electronics and Telecommunications

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2015

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Vol. 61, No. 1

37-41

EN

The article presents information fusion approach for song classification with use of acoustic signal. Many acoustic features can contribute to correct identification of a song. Taking into consideration only one set of features may result in omission of relevant information. It is possible to improve the accuracy of identification process by means of the information fusion technique, in which various aspects of acoustic fingerprint are taken into consideration. Two sets of signal features were distinguished: one were based on frequency analysis (harmonic elements) and the other were based on multidimensional correlation ratios. An identification of a commercial was made with use of SVM and k-NN classifiers. The music audio signal database was used for assessing the effectiveness of the proposed solution. Results show an improved effectiveness of identification in relation to applying only one set of song features.

10

Reliability and Risk Assessment of Aircraft Electric Systems

He L., Yin C., Peng W., Yuan R., Huang H.-Z.

Eksploatacja i Niezawodność

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2014

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Vol. 16, no. 4

497--506

EN

It is rather difficult in identifying the fault location and performing risk assessment for complex electronic systems. In this paper a reliability assessment method based on the interval analytic hierarchy process (IAHP) and Bayesian network is proposed to facilitate reliability and risk assessment. After considering the major fault factors, the interval eigenvector method (IEM) is also presented to assess the reliability and comprehensive weights of subsystems. The conditional probability matrices for the factors of risk are defined using an inference rule. Then an updating model of information fusion in the context of Bayesian network is established to assess the risk of system. The proposed method is demonstrated through the risk assessment of an aircraft electric system. The result of the illustrative example shows that the proposed method can not only incorporate the evidence information, but also synthesize all the historical information. A further dynamic adjustment in the safety and risk priority of control measures is quite effective to improve the reliability while mitigating the risk of the electric system.

PL

Lokalizacja uszkodzeń oraz ocena bezpieczeństwa i ryzyka w przypadku złożonych systemów elektronicznych jest zadaniem dość trudnym. W niniejszej pracy zaproponowano metodę prognozowania niezawodności opartą na procesie przedziałowej hierarchii analitycznej (IAHP), która ma na celu ułatwienie diagnozy uszkodzeń i kontroli ryzyka. Po rozważeniu głównych czynników wywołujących uszkodzenia, zaprezentowano metodę przedziałowych wektorów własnych oraz zdefiniowano, przy użyciu reguły wnioskowania, macierze prawdopodobieństwa dla czynników wpływających na bezpieczeństwo i ryzyko. Następnie, stworzono odnawialny model fuzji informacji w kontekście wnioskowania bayesowskiego służący do oceny stanu zagrożenia Udowodniono, iż włączenie wiedzy eksperckiej do dynamicznej symulacji ułatwia lokalizację uszkodzeń oraz pozwala uzyskać informacje dotyczące diagnozy uszkodzeń. Studium przypadku pokazuje, że dynamiczne dostosowanie priorytetowości związanej z bezpieczeństwem i ryzykiem stosowanych środków kontroli w sposób dość skuteczny zwiększa niezawodność przy jednoczesnym zminimalizowaniu ryzyka w złożonym systemie elektronicznym.

11

Generalizing Dempster's combination rule to fuzzy sets

Xiao J., Tong M., Song W.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 1b

45--47

EN

The fuzzy and imprecise information always exist in real systems. Several attempts have been made to generalize the Dempster-Shafer (D-S) evidence theory to deal with fuzzy sets. In order to combine bodies of evidence that may contain vague information, Dempster's combination rule was extended to fuzzy sets in the evidential reasoning. In this paper, a new definition of the weight between two fuzzy sets is described, and the improved extension combination rule of the evidence theory on fuzzy sets is put forward. Compared with other generalization of Dempster’s combination rules, the results of the numerical experiments show that the new combination rule in this paper can acquire more changing information to the change of fuzzy focal elements more effectively.

PL

W rzeczywistych systemach zwykle występuje informacja rozmyta i nieprecyzyjna. Istnieje szereg prób uogólnienia teorii Dempster’aShafer’a w zastosowaniu do zbiorów rozmytych. W wywodzie dowodowym, w celu dołączenia fragmentu danych, które mogą zawierać informację nieprecyzyjną, rozciągnięto regułę kombinacji Dempster’a na zbiory rozmyte. W opracowaniu opisano nową definicję wagi między dwoma zbiorami rozmytymi oraz przedstawiono udoskonalone rozszerzenie kombinacyjnej reguły badanej teorii na zbiory rozmyte. W porównaniu z innymi uogólnieniami reguł kombinacji Dempster’a, wyniki eksperymentalne pokazują, że nowa, przedstawiona w opracowaniu, reguła kombinacji może bardziej skutecznie uzyskać więcej zmieniających się informacji przy zmianie centralnych elementów zbioru.

12

Day-ahead Electricity Price Prediction Based on Improved ANN Information Fusion

Li K.

Przegląd Elektrotechniczny

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2013

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R. 89, nr 3b

78--80

EN

A novel information fusion method is proposed based on the characters of day-ahead electricity price. An improved BPNN is used for its better performance as the core algorithm of information fusion. Using the information fusion ideas, a new modelling approach is proposed to establish the prediction model. The day-ahead electricity price prediction model is tested by the real data. The experiments demonstrate that the new prediction model established by improved BPNN information fusion method has better performance.

PL

W artykule przedstawiono nową metodę fuzji danych w oparciu o charakterystyki cenowe elektryczności z dnia poprzedniego. Algorytm oparto na sieci neuronowej BPNN. Jego działanie poddano badaniom, bazując na prawdziwych danych, których wyniki wskazują na skuteczność działania proponowanego rozwiązania.

13

Klasyfikacja pojazdów za pomocą łączenia informacji akustycznej

Biernacki P.

Elektronika : konstrukcje, technologie, zastosowania

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2013

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Vol. 54, nr 10

70-72

PL

W artykule przedstawiono skuteczny sposób klasyfikacji pojazdów oparty na teorii informacji połączonej, wykorzystujący sygnał akustyczny generowany przez pojazdy. Wiele akustycznych czynników może przyczyniać się do trafnego rozpoznania pojazdu. Poleganie na jednym zbiorze cech może pomijać istotne informacje. Dokładność klasyfikacji można poprawić dzięki technice informacji połączonej, gdzie różne aspekty akustycznego ‘podpisu’ pojazdu brane są pod uwagę. Wyodrębniono dwa zbiory cech sygnału: oparte na analizie częstotliwościowej (elementy harmoniczne) oraz oparte na wielowymiarowych zależnościach korelacyjnych. Na ich podstawie używając klasyfikatorów SVM oraz k-NN dokonywana jest identyfikacja danej klasy pojazdów. Do oceny skuteczności rozwiązania wykorzystano bazę sygnałów audio pojazdów różnych klas. Rezultaty pokazują poprawę skuteczności rozpoznania w stosunku do zastosowania tylko jednej grupy cech charakterystycznych pojazdu.

EN

In the article an information fusion approach for vehicles classification using acoustic signal was presented. Many acoustic features can contribute to a right diagnosis of the vehicle. Consisting only one set of features can omit the relevant information. It is possible to improve the accuracy of classification thanks to the technique of information fusion, where various aspects of acoustic 'fingerprint' are being taken into consideration. Two sets of features of the signal were distinguished: based on frequency analysis (harmonic elements) and based on multidimensional correlation relations. Using SVM and k-NN classifiers identification of the given class of vehicles is being made. A vehicle different classes audio signal database was used for the assessment of effectiveness of the proposed solution. Results are showing the improvement the effectiveness of recognizing towards applying only of one features set of the vehicle.

14

Novel S-transform information fusion for filtering ultrasonic pulse-echo signals

Kubinyi M., Kreibich O., Neuzil J., Smid R.

Przegląd Elektrotechniczny

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2011

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R. 87, nr 1

290-295

EN

Direct evaluation of ultrasonic signals requires data analyses with an acceptable level of noise. Ultrasonic signals represent a specific category of time domain signals to be analyzed. In order to increase a difference between the level of noise and the amplitude of the ultrasonic pulse a suitable method for signal filtering has to be used. Within this article we discuss and evaluate a novel signal denoising method. The S-transform for signal analysis and processing was used. This transformation has been recently introduced for ultrasonic echo analyses. Proposed transformation represents an intermediate stage between the Fourier transform analysis and the wavelet transform analysis. In order to filter ultrasonic signals from the Electromagnetic Acoustic Transducer (EMAT) with a high level of noise, new, different approach in signal filtering was developed based on an information fusion. Suggested method is able to process the pulse-echo signal in its full complexity. Proposed method offers good results in studied ultrasonic signals in comparison to digital filter or wavelet denoising.

PL

Bezpośrednia ocean sygnału ultradźwiękowego wymaga analizy danych obciążonych szumami. W celu zwiększenia różnicy między amplitudą sygnału a szumami użyto specjalnej metody filtrowania. Zastosowano transformatę S do analizy ultradźwiękowego sygnału echa. Tego typu transformata jest metodą pośrednia między transformatą Fouriera a transformatą falkową. Użyto nowej metody bazującej na fuzji informacji. Testy potwierdziły że nowa metoda może być skuteczniejsza niż filtrowanie cyfrowe czy odszumianie falkowe.

15

SANPEV: a satisficting analytic network process framework for efficiency evaluation of alternatives

Tchangani A. P.

Foundations of Computing and Decision Sciences

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2006

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Vol. 31, No. 3-4

291-319

EN

The purpose of this paper is to derive a procedure to evaluate a group of alternatives or units considered as systems where a certain transformation process consums heteregenous input attributes or items (to be understood in a broad sense including effort that must be done, a negative impact, consumable resources, ...) to produce or deliver heteregenous output items (including subjective satisfaction, tangible products, beneficial impact. ...). In general, many actors with, different points of view as well as different information sources more or less reliable will be involved in the evaluation process. The evaluation context we consider here consists in stakeholders (decission makers, experts, users. ...) that give then- opinion regarding the impact of each item with, regard to the evaluation goal ; the information or data (values of items for different alternatives) about items are collected from or supplied by different more or less reliable information or data sources (news papers, magazines, web. agencies and consulting cabinets, experts. ...). The established model aims to integrate the interactions between these different components (stakeholders, items. information sources and alternatives) and consists bassically for each alternative or unit in computing two measures: an aggregated measure known as the selectability at the output of the system and an aggregated measure at the input known as the rejectability in the framework of satisficing game theory. The derivation of these measures is carried up by a pairwise comparison process using the analytic network process (ANP) approach, an extension of the well known analytic hierarchy process (AHP), that allows to take into account complex interactions of evaluation process components such as dependency and feedback.

16

Information fusion in temperature measurement

Kucharski J.

Metrology and Measurement Systems

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2002

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Vol. 9, nr 4

339-352

EN

New approach to intelligent temperature signal processing has been proposed. The method incorporates both samples of temperature signal and imprecise information concerning the conditions under which the temperature readings have been obtained. The fuzzy sets have been applied for representation of imprecise knowledge. Fusion algorithm of imprecise information and uncertain temperature readings has been proposed. As an example the method was examined for chosen thermal processes and electroheat plants.

PL

W artykule przedstawiono nową metodę przetwarzania (filtracji) sygnału temperatury, mającą cechy cenzurowania próbek pomiarowych, a bazującą na konsolidacji różnego rodzaju informacji (information fusion). Proponowany algorytm pozwala uwzględnić w procesie przetwarzania mierzonego sygnału dodatkowe informacje o warunkach w jakich przeprowadzany jest pomiar, np. informacje dotyczące fizycznych ograniczeń obiektu pomiaru i aktualnej fazy toczącego się procesu technologicznego. Ze względu na fakt, że takie dodatkowe informacje mogą mieć charakter nieprecyzyjny do ich reprezentacji i przetwarzania zastosowano zbiory rozmyte, pełniące rolę tzw. rozkładów możliwości. Podano sposób tworzenia takich zbiorów dla różnych faz cieplnych procesów technologicznych oraz przeanalizowano wpływ kształtu funkcji przynależności zbioru na jego zawartość informacyjną. Zaproponowano algorytm łączący (konsolidujący) informacje o różnym charakterze, tj.: próbki mierzonego sygnału oraz zbiory rozmyte reprezentujące warunki przeprowadzania pomiarów. Algorytm wykazuje dodatkowo takie korzystne cechy procedury filtracyjnej jak np. pozostawianie niezmienionych wartości tych próbek pomiarowych, które uznane są za prawidłowe. Przeprowadzono wszechstronną weryfikację metody zarówno na drodze symulacji komputerowych, jak i w trakcie eksperymentów z wykorzystaniem rezystancyjnych pieców komorowych. Uwzględniono przy tym typowe fazy cieplnych procesów technologicznych, takie jak np. rozgrzew obiektu czy programowa regulacja temperatury. Wykazano, że proponowany algorytm zapewnia lepsze odtwarzanie rzeczywistej wartości temperatury w porównaniu z typowymi algorytmami filtracyjnymi, szczególnie w przypadku dynamicznych zmian sygnału mierzonego.