Abstract
In coal mining industry, the running state of mine ventilators plays an extremely significant role for the safe and reliable operation of various industrial productions. To guarantee the better reliability, safety, and economy of mine ventilators, in view of early detection and effective fault diagnosis of mechanical faults which could prevent unscheduled downtime and minimize maintenance fees, it is imperative to construct some viable mathematical models for mine ventilator fault diagnosis. In this article, we plan to establish a data-based mine ventilator fault diagnosis method to handle situations where engineers are absent or they are incapable of coming to a conclusion from multisource data. In the process of building the mine ventilator fault diagnosis model, considering that probabilistic rough sets (PRSs) could reduce the errors triggered by incompleteness, inconsistency, and inaccuracy without needing any additional assumptions and Pythagorean fuzzy multigranulation rough sets (PF MGRSs) over the two universes’ model could effectively handle data representation, fusion, and analysis issues, we generalize the existing PF MGRSs over the two universes’ model to the PRS setting, as well as to further establish a novel model named Pythagorean fuzzy multigranulation probabilistic rough sets (PF MG-PRSs) over two universes. In the granular computing paradigm, three types of PF MG-PRSs over two universes based on the risk attitude of engineers are proposed at first. Afterwards, several basic propositions of the newly proposed model are explored. Moreover, a PF multigranulation probabilistic model for mine ventilator fault diagnosis based on PF MG-PRSs over two universes is investigated. At last, a real-world case study of dealing with a mine ventilator fault diagnosis problem is given to illustrate the practicality of the presented model, and a validity test, a sensitivity analysis, and a comparison analysis are further explored to demonstrate the effectiveness of the presented model.
Highlights
Nowadays, the development of modern society and economy mainly depends on an adequate and reliable supply of energy to some extent
As one of the most abundant reserves of fossil fuel in the world, coal resources still play a crucial part in promoting the industrialization and social economic development of some areas; safe and reasonable exploration of coal resources is the key to most energy-dependent economies
Mine ventilator, a rotating electrical machine which ensures the safety of coal mines and underground coal miners through providing fresh air and eliminating harmful gases, acts as an indispensable component of the coal mine safety production, energy conservation, and automated administration
Summary
The development of modern society and economy mainly depends on an adequate and reliable supply of energy to some extent. The second merit is that the utilization of PRSs makes the proposed model owns the capacity of processing a number of noisy data, which is featured by positive, negative, and boundary fault diagnosis rules (3) By virtue of variable PF MG-PRSs over two universes, a PF multigranulation probabilistic model for mine ventilator fault diagnosis with PFSs is constructed and a numerical example, a validity test, a sensitivity analysis, and a comparison analysis illustrate that the superiorities of the proposed fault diagnosis rule could cut down uncertainty and improve accuracy of mine ventilator fault diagnosis to a great extent.
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