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EN
Currently, emphasis is still placed on risk evaluations of physical factors in workplaces. The aim of this paper was to evaluate objectively and subjectively the noise parameters and microclimate conditions near conveyor systems at the workplace for the handling and sorting postal items. Objective noise measurements were performed using the Norsonic 140 sound analyser, Class 1 and microclimatic conditions using the Testo 435 instrument. The subjective evaluation was performed by the questionnaire method (120; F: 66; M: 54). The result of the research was the assessment of health risks, depending on the sources of noise caused by conveyor systems.
EN
Sound visualization tools are now widely used in industry. As a tool, acoustic cameras are also well- suited for faster identification of errors as well as individual states while operating devices. The aim of this paper was to locate and quantify noise sources on a packet sorting line using an acoustic camera and then to propose noise reduction measures. Localization of noise sources was performed by means of an acoustic camera with a microphone ring array. The result of these measurements and analyses was to sort the individual noise sources from less noisy to the noisiest, which gives a good assumption for better planning of spending on the implementation of noise reduction measures. The outputs of these measurements also give information on the character and frequency composition of the sound of individual sources, which will help out in the design of specific noise measures.
EN
Sound and noise are as old as humanity itself. They have accompanied civilization, evolution, and development for centuries. Music and speech represent not only the key elements of human life but also unpleasant feelings of noise that have always been an integral part of human existence. As industrial development has required more energy, powerful machinery, and equipment, there have been still noisier machines. Traffic has grown quickly due to the number and speed of vehicles. For that reason, an acoustic camera is used for the dynamic visualization of machinery and equipment noise as it analyses the sources of noise in details. Subsequently, qualified measures are introduced based on the results of the analysis. The paper considers launching another application. According to the proposed methodology, its use in identifying machinery and equipment failures and their maintenance is proved. The experiment was performed on a four-wheel lawn mower. The primary focus was on the identification of failures using an acoustic camera. The previous method allowed to quickly, precisely and efficiently identifying the failures in two out of five tested machines.
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