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Dust detection and control in real time, represent one of the most challenging problem in all those environments where fine and ultrafine airborne particulate solids products are present. The presence of such products can be linked to several factors, often directly related and influenced by the working-production actions performed. Independently from the causes generating dust, airborne contaminants are an occupational problem of increasing interest as they are related to a wide number of diseases. In particular, airborne dusts are well known to be associated with several classical occupational lung diseases, such as the pneumoconiosis, especially at high levels of exposure. Nowadays there is also an increasing interest in other dust related diseases, from the most serious as cancer and asthma, to those related with allergies or irritation and other illnesses, also occurring at lower levels of exposure.
Among the different critical factors influencing health risk for airborne dust exposure, mainly four have to be considered, that is: i) nature of the dust resulting from working in terms of presence of specific poisoning material, i.e. free silica, and morphological and morphometrical attributes of particulates constituting airborne dust; ii) size of the particles, iii) duration of exposure time and, finally, iv) airborne dust concentration in the breathing zone where the worker performs his activity.
A correct dust detection is not easy, especially if some of the previous mentioned factors, have to be detected and quantified in real time in order to define specific “on-line” control actions aimed to reduce the level of the exposure to dust of the workers, as for example: i) modification of aspirating devices operating condition, change of filtering cleaning sequence, etc. . The more severe are the environmental conditions, in terms of dust presence (in quantity and quality) more difficult is to utilize efficient sampling devices. Detection devices, in fact, tend to become “blind” to dust as dust presence increases, on the other hand severe dust production conditions is exactly the case where control strategies have to be applied to realize safer conditions for the workers.
In this paper the possibility to utilize a new logic to perform an “on-line” airborne dust sampling and analysis utilizing imaging is described with particular reference to dusts flowing in a duct after the caption and before their abatement by classical mechanical filtering. The study was particularly addressed to define, design and implement a logic able to extract those parameters affecting airborne dust behavior with respect to its efficient abatement. All dust sampling was performed directly in an industrial plant where tests were carried out in a controlled environment.
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