online condition monitoring of bearings for improved reliability in packaging materials industry

The production processes in the packaging materials industry has to be very efficient and cost-effective. These processes usually take place under extreme conditions and high speeds that requires a high level of reliability and efficiency. Rollers including their supporting bearings and motors are the most common components of production machines in the packaging materials industry. Bearing faults, which often occur gradually, represent one of the foremost causes of failures in the industry. Therefore it is very important to take care of bearings during maintenance and detect their faults in an early stage in order to assure safe and efficient operation. We present a new automated technique for early fault detection and diagnosis in rolling-element bearings based on vibration signal analysis. After normalization and the wavelet transform of vibration signals, the standard deviation as a measure of average energy level and the logarithmic energy entropy as a measure of the degree of order/disorder are extracted in a few sub-bands of interest as representative features. Then the feature space dimension is optimally reduced to two using scatter matrices. In the reduced two-dimensional feature space the fault detection is performed by a quadratic classifier and the fault diagnosis by another two quadratic classifiers. Accuracy of the new technique was tested on the ball bearing data recorded at the Case Western Reserve University Bearing Data Center. In total four classes of the vibrations signals were studied, i.e. normal, with the fault of inner race, outer race and balls operation. An overall accuracy of 100% was achieved. The new technique can be used to increase reliability and efficiency by preventing unexpected faulty operation of machinery bearings

Online Condition Monitoring of Bearings to Support Total Productive Maintenance in the Packaging Materials Industry

The packaging materials industry has already recognized the importance of Total Productive Maintenance as a system of proactive techniques for improving equipment reliability. Bearing faults, which often occur gradually, represent one of the foremost causes of failures in the industry. Therefore, detection of their faults in an early stage is quite important to assure reliable and efficient operation. We present a new automated technique for early fault detection and diagnosis in rolling-element bearings based on vibration signal analysis. Following the wavelet decomposition of vibration signals into a few sub-bands of interest, the standard deviation of obtained wavelet coefficients is extracted as a representative feature. Then, the feature space dimension is optimally reduced to two using scatter matrices. In the reduced two-dimensional feature space the fault detection and diagnosis is carried out by quadratic classifiers. Accuracy of the technique has been tested on four classes of the recorded vibrations signals, i.e., normal, with the fault of inner race, outer race, and ball operation. The overall accuracy of 98.9% has been achieved. The new technique can be used to support maintenance decision-making processes and, thus, to increase reliability and efficiency in the industry by preventing unexpected faulty operation of bearings

Revista de educación

Análisis del sistema de admisión en las universidades en Yugoslavia. El sistema de educación y de instrucción en Yugoslavia se edifica y desarrolla en la dirección de los objetivos globales de la comunidad socialista yugoslava. Los principios y objetivos del programa fundamentales de educación y de instrucción en nuestras condiciones sociales son los siguientes: el desarrollo de una actitud creadora en los jóvenes hacia su profesión futura, el desarrollo de la conciencia socialista y la formación de los jóvenes para la participación en la vida social del país y en los órganos de la autogestión social y de dirección, el conocimiento y la adopción de las creaciones de nuestros pueblos y de la humanidad entera en diversos campos de la creación social, el desarrollo del espíritu de fraternidad y de unidad de los pueblos yugoslavos, y el desarrollo del internacionalismo, del espíritu de la solidaridad internacional. Respecto a la admisión para el curso escolar 1972-1973 se efectuó según las siguientes modalidades: inscripción libre para todos los que hayan terminado la escuela secundaria correspondiente; inscripción limitada a un cierto número, conforme a los resultados en la escuela secundaria; inscripción de todos los que pasen el examen de calificación, resultados obtenidos en la escuela secundaria durante toda la escolarización precedente y examen de calificación para los demás candidatos y por último inscripción en función exclusivamente de los resultados del examen de calificación. Como conclusión se señala que la admisión de nuevos estudiantes en la universidad es un problema de la sociedad global. En la comunidad socialista de autogestión yugoslava, este problema está condicionado por varios elementos: la existencia de un plan, verificado por la sociedad, de necesidades de cuadros formados en la universidad, para un período mínimo de diez años; una red desarrollada y de estructura adecuada de instituciones de enseñanza superior bien equipadas y una buena orientación profesional de todos los candidatos procedentes de las escuelas secundarias. Cumplidas estas tres condiciones, las universidades y las facultades podrán asumir toda la responsabilidad social para la admisión de los nuevos estudiantes, y solamente en ese momento es cuando se podrá pensar en aplicar la orientación general de la sociedad, la inscripción libre en todas las facultades.Ministerio Educación CIDEBiblioteca de Educación del Ministerio de Educación, Cultura y Deporte; Calle San Agustín, 5 - 3 Planta; 28014 Madrid; Tel. +34917748000; [email protected]

Online Condition Monitoring of Bearings to Support Total Productive Maintenance in the Packaging Materials Industry

The packaging materials industry has already recognized the importance of Total Productive Maintenance as a system of proactive techniques for improving equipment reliability. Bearing faults, which often occur gradually, represent one of the foremost causes of failures in the industry. Therefore, detection of their faults in an early stage is quite important to assure reliable and efficient operation. We present a new automated technique for early fault detection and diagnosis in rolling-element bearings based on vibration signal analysis. Following the wavelet decomposition of vibration signals into a few sub-bands of interest, the standard deviation of obtained wavelet coefficients is extracted as a representative feature. Then, the feature space dimension is optimally reduced to two using scatter matrices. In the reduced two-dimensional feature space the fault detection and diagnosis is carried out by quadratic classifiers. Accuracy of the technique has been tested on four classes of the recorded vibrations signals, i.e., normal, with the fault of inner race, outer race, and ball operation. The overall accuracy of 98.9% has been achieved. The new technique can be used to support maintenance decision-making processes and, thus, to increase reliability and efficiency in the industry by preventing unexpected faulty operation of bearings