scholarly journals Application properties of methods for fault detection and isolation in the diagnosis of complex large-scale processes

2014 ◽  
Vol 62 (3) ◽  
pp. 571-582 ◽  
Author(s):  
J.M. Kościelny ◽  
M. Syfert
Keyword(s):  
Fault Detection ◽  
Large Scale ◽  
Fault Detection And Isolation ◽  
Industrial Processes ◽  
Industrial Practice ◽  
Potential Applicability ◽  
Diagnostic Approaches ◽  
Level Of Knowledge ◽  
High Level ◽  
Selection Of

Abstract The survey presents a selection of the methods of the fault detection and isolation suitable to be useful for the diagnostics of the complex, large scale industrial processes. The paper focuses on these methods that have appropriately high level of potential applicability in industrial practice. The novelty of the paper relies on the discussion of the dependency of the level of knowledge about diagnosed process and recommended diagnostic approaches. Appropriate recommendations were given in the convenient form of the table

A case-based reasoning system for fault detection and isolation: a case study on complex gearboxes

2019 ◽  
Vol 25 (2) ◽  
pp. 213-235 ◽  
Author(s):  
Soumava Boral ◽  
Sanjay Kumar Chaturvedi ◽  
V.N.A. Naikan
Keyword(s):  
Decision Making ◽  
Fault Detection ◽  
Large Scale ◽  
Fault Detection And Isolation ◽  
Decision Making Process ◽  
Case Based Reasoning ◽  
Content Type ◽  
Complex Decision Making ◽  
Complex Decision ◽  
Case Based

Purpose Usually, the machinery in process plants is exposed to harsh and uncontrolled environmental conditions. Even after taking different types of preventive measures to detect and isolate the faults at the earliest possible opportunity becomes a complex decision-making process that often requires experts’ opinions and judicious decisions. The purpose of this paper is to propose a framework to detect, isolate and to suggest appropriate maintenance tasks for large-scale complex machinery (i.e. gearboxes of steel processing plant) in a simplified and structured manner by utilizing the prior fault histories available with the organization in conjunction with case-based reasoning (CBR) approach. It is also demonstrated that the proposed framework can easily be implemented by using today’s graphical user interface enabled tools such as Microsoft Visual Basic and similar. Design/methodology/approach CBR, an amalgamated domain of artificial intelligence and human cognitive process, has been applied to carry out the task of fault detection and isolation (FDI). Findings The equipment failure history and actions taken along with the pertinent health indicators are sufficient to detect and isolate the existing fault(s) and to suggest proper maintenance actions to minimize associated losses. The complex decision-making process of maintaining such equipment can exploit the principle of CBR and overcome the limitations of the techniques such as artificial neural networks and expert systems. The proposed CBR-based framework is able to provide inference with minimum or even with some missing information to take appropriate actions. This proposed framework would alleviate from the frequent requirement of expert’s interventions and in-depth knowledge of various analysis techniques expected to be known to process engineers. Originality/value The CBR approach has demonstrated its usefulness in many areas of practical applications. The authors perceive its application potentiality to FDI with suggested maintenance actions to alleviate an end-user from the frequent requirement of an expert for diagnosis or inference. The proposed framework can serve as a useful tool/aid to the process engineers to detect and isolate the fault of large-scale complex machinery with suggested actions in a simplified way.

The “Diag” System for Fault Detection and Isolation in Industrial Processes

1994 ◽  
Vol 27 (5) ◽  
pp. 761-766
Author(s):  
Jan Macej Kościelny ◽  
Dariusz Sȩdziak ◽  
Andrzej Sikora
Keyword(s):  
Fault Detection ◽  
Fault Detection And Isolation ◽  
Industrial Processes

scholarly journals A Study on the Extent of Knowledge Gained and Adoption of Bio-Fertilizers and Bio-Pesticides by the Crop Growers of Keonjhar District in Odisha

2021 ◽  
Vol 10 (9) ◽  
pp. 351-356
Author(s):  
Isha Anindita Sahoo Bibudha Parasar ◽  
Swatee Prangya
Keyword(s):  
Sampling Technique ◽  
Study Data ◽  
Knowledge Gain ◽  
Statistical Measures ◽  
Ex Post ◽  
Ex Post Facto ◽  
Medium Level ◽  
Level Of Knowledge ◽  
High Level ◽  
Selection Of

The study entitled “A study on the Extent of Knowledge Gained and Adoption of Bio fertilizers and bio pesticides by the Crop Growers of Keonjhar District in Odisha” was undertaken in 2020. For the purpose, ex-post-facto research designed was followed with snow-ball sampling technique for selection of respondents, random sampling technique for selection of villages and purposive sampling method was followed for selection of panchayat, block as well as the district, where 80 no. of respondents were selected for the purpose of the study. Data were collected with the help of interview schedule and the collected data were analyzed with the help of statistical measures like frequency, percentage, mean, standard deviation, correlation co-efficient for flawless interpretation and drawing correct conclusion against the objectives set for the study. The major findings of the study revealed that (67.5%) i.e. majority of the respondents are at medium level of knowledge gain followed by (20%) with high level and only (12.5%) are at lower level of knowledge with regard of bio-fertilizers and bio-pesticides. The next part, level of adoption of respondents with regard to bio-fertilizer and bio-pesticides which was assessed and it was found that majority to the extent of (77.5%) are at medium level of adoption in the context of bio-fertilizers whereas again majority of the respondent to the extent of (67.5%) are at medium level of adoption when bio-pesticides are concerned.

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