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Assessment of the technical state of mining machinery and devices with the use of diagnostic methods

Biały Witold

Production Engineering Archives

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2024

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Vol. 30, Iss. 2

266--272

EN

In this article, one of the possible, effective methods of assessing the technical state of mining machinery and devices has been presented. The article's main goal is to show the possible methods and ways of measuring temperature, oscillations, and vibrations generated during the operation of mining equipment and machines’ gears, which are possible in underground conditions. Devices measuring temperatures without coming into contact with the given object are built based on different types of infrared radiation detectors or matrixes of such detectors. Thermal imaging devices picture the temperature distribution on the entire surface instead of pyrometers, which measure temperatures at a given point. However, vibrations and oscillations generated by the work of gears of devices and machinery have been made using a vibrometer pen and a machine condition tester, after which the obtained measurements were used to diagnose the degradation of individual elements of those machines. Such an assessment of the degradation of individual elements of machines in production conditions has been applied with positive results in one of the mines of the Polish Mining Group (Polska Grupa Górnicza – PGG).

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Classification of plantar foot alterations by fuzzy cognitive maps against multi-layer perceptron neural network

Ramirez-Bautista Julian Andres, Huerta-Ruelas Jorge Adalberto, Kóczy László T., Hatwágner Miklós F., Chaparro-Cárdenas Silvia L., Hernández-Zavala Antonio

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

404--414

EN

Load distribution analysis on foot surface allows knowing human mechanical behavior and aids the doctor in the detection of gait disorders like, the risk of foot ulcerations, leg discrepancy, and footprint alterations. Plantar pressure data combined with techniques that use integral reasoning produce easy understanding medical tools for assisting in treatment, early detection, and the development of preventive strategies. The present research compares the classification of human plantar foot alterations using Fuzzy Cognitive Maps (FCM) trained by Genetic Algorithm (GA) against a Multi-Layer Perceptron Neural Network (MLPNN). One hundred and fifty-one subject volunteers (aged 7–77) were classified previously with the flat foot (n = 70) and cavus foot (n = 81) by specialized physicians of the Piédica diagnostic center. The trial walking was conducted using plantar pressure platforms FreeMed®. The foot surface was divided into 14 areas that included toe 1 st to 5th, metatarsal joint 1st to 5th, lateral midfoot, medial midfoot, lateral heel, and medial heel. Pressure data were normalized for each area. Better performance in the classification using small amounts of data were found by using Fuzzy rather than non-Fuzzy approach.

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Fuzzy logic approach for infectious disease diagnosis: A methodical evaluation, literature and classification

Arji Goli, Ahmadi Hossein, Nilashi Mehrbakhsh, Rashid Tarik A., Hassan Ahmed Omed, Aljojo Nahla, Zainol Azida

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 4

937--955

EN

This paper presents a systematic review of the literature and the classification of fuzzy logic application in an infectious disease. Although the emergence of infectious diseases and their subsequent spread have a significant impact on global health and economics, a comprehensive literature evaluation of this topic has yet to be carried out. Thus, the current study encompasses the first systematic, identifiable and comprehensive academic literature evaluation and classification of the fuzzy logic methods in infectious diseases. 40 papers on this topic, which have been published from 2005 to 2019 and related to the human infectious diseases were evaluated and analyzed. The findings of this evaluation clearly show that the fuzzy logic methods are vastly used for diagnosis of diseases such as dengue fever, hepatitis and tuberculosis. The key fuzzy logic methods used for the infectious disease are the fuzzy inference system; the rule-based fuzzy logic, Adaptive Neuro-Fuzzy Inference System (ANFIS) and fuzzy cognitive map. Furthermore, the accuracy, sensitivity, specificity and the Receiver Operating Characteristic (ROC) curve were universally applied for a performance evaluation of the fuzzy logic techniques. This thesis will also address the various needs between the different industries, practitioners and researchers to encourage more research regarding the more overlooked areas, and it will conclude with several suggestions for the future infectious disease researches.

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Computational intelligence techniques for medical diagnosis and prognosis: Problems and current developments

Shahid Afzal Hussain, Singh M. P.

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 3

638--672

EN

Diagnosis, being the first step in medical practice, is very crucial for clinical decision making. This paper investigates state-of-the-art computational intelligence (CI) techniques applied in the field of medical diagnosis and prognosis. The paper presents the performance of these techniques in diagnosing different diseases along with the detailed description of the data used. This paper includes basic as well as hybrid CI techniques that have been used in recent years so as to know the current trends in medical diagnosis domain. The paper presents the merits and demerits of different techniques in general as well as application specific context. This paper discusses some critical issues related to the medical diagnosis and prognosis such as uncertainties in the medical domain, problems in the medical data especially dealing with time-stamped (temporal) data, and knowledge acquisition. Moreover, this paper also discusses the features of good CI techniques in medical diagnosis. Overall, this review provides new insight for future research requirements in the medical diagnosis domain.

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Review on plantar data analysis for disease diagnosis

Ramirez-Bautista J. A., Hernández-Zavala A., Chaparro-Cárdenas S. L., Huerta-Ruelas J. A.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 2

342--361

EN

Force distribution on foot surface allows to understand the human mechanical behavior, providing detailed information for the evaluation of foot alterations. In diagnosis for diseases related to plantar pathologies, there are many devices for plantar pressure mea-surement, and corresponding algorithms for data analyzing, providing medical tools for assisting in treatment, early detection, and the development of preventive strategies. In medicine, use of computational intelligence is increasing, making the diagnostic processes faster and more accurate. Clinical Decision Support Systems (CDSS) can handle large amounts of data to improve decision-making, helping to prevent the deterioration of people's health. Numerous approaches have been applied over the past few decades to solve medical problems such as hepatitis, diabetes, liver disease, pathological gait, and plantar diseases, among others. This paper presents the developments reported in the literature for detecting diseases through plantar pressure data and the corresponding algorithms for its analysis and diagnosis, using different electronic measurements systems. Finally, we present a discussion about the future work required to improve in the field of plantar pressure diagnosis algorithms using different approaches suggested by the authors as potential candidates. In this sense, hybrid systems which include fuzzy concepts are the most promising methodology.