Application of a knowledge based system for voltage monitoring and control on the NGC system

This chapter presents a method for ontology construction and its application in developing ontology in the domain of natural gas pipeline operations. Both the method as well as the application ontology developed, contribute to the infrastructure of Semantic Web that provides semantic foundation for supporting information processing by autonomous software agents. This chapter presents the processes of knowledge acquisition and ontology construction for developing a knowledge-based decision support system for monitoring and control of natural gas pipeline operations. Knowledge on the problem domain was acquired and analyzed using the Inferential Modeling Technique, then the analyzed knowledge was organized into an application ontology and represented in the Knowledge Modeling System. Since ontology is an explicit specification of a conceptualization that provides a comprehensive foundation specification of knowledge in a domain, it provides semantic clarifications for autonomous software agents that process information on the Internet.

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A Knowledge-Based System as a Sustainable Software Application for the Supervision and Intelligent Control of an Alcoholic Fermentation Process

Sustainability ◽

10.3390/su122310205 ◽

2020 ◽

Vol 12 (23) ◽

pp. 10205

Author(s):

Anca Sipos

Keyword(s):

Intelligent Control ◽

Fermentation Process ◽

Production Efficiency ◽

Alcoholic Fermentation ◽

Control Level ◽

Exponential Growth Phase ◽

Monitoring And Control ◽

Software Application ◽

Knowledge Based System ◽

Knowledge Based

One goal of specialists in food processing is to increase production efficiency in accordance with sustainability by optimising the consumption of raw food materials, water, and energy. One way to achieve this purpose is to develop new methods for process monitoring and control. In the winemaking industry, there is a lack of procedures regarding the common work based on knowledge acquisition and intelligent control. In the present article, we developed and tested a knowledge-based system for the alcoholic fermentation process of white winemaking while considering the main phases: the latent phase, exponential growth phase, and decay phase. The automatic control of the white wine’s alcoholic fermentation process was designed as a system on three levels. Level zero represents the measurement and adjustment loops of the bioreactor. At the first level of control, the three phases of the process are detected functions of the characteristics of the fermentation medium (the initial substrate concentration, the nitrogen assimilable content, and the initial concentration of biomass) and, thus, functions on the phase’s duration. The second level achieves the sequence supervision of the process (the operation sequence of a fermentation batch) and transforms the process into a continuous one. This control level ensures the quality of the process as well as its diagnosis. This software application can be extended to the industrial scale and can be improved by using further artificial intelligence techniques.

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Process Disturbances in Agricultural Biogas Production—Causes, Mechanisms and Effects on the Biogas Microbiome: A Review

Energies ◽

10.3390/en12030365 ◽

2019 ◽

Vol 12 (3) ◽

pp. 365 ◽

Cited By ~ 23

Author(s):

Susanne Theuerl ◽

Johanna Klang ◽

Annette Prochnow

Keyword(s):

Environmental Performance ◽

Biogas Production ◽

Efficient Production ◽

Monitoring And Control ◽

Crucial Importance ◽

Knowledge Based ◽

Complex Process ◽

Process Monitoring And Control ◽

Process Disturbances ◽

And Control

Disturbances of the anaerobic digestion process reduce the economic and environmental performance of biogas systems. A better understanding of the highly complex process is of crucial importance in order to avoid disturbances. This review defines process disturbances as significant changes in the functionality within the microbial community leading to unacceptable and severe decreases in biogas production and requiring an active counteraction to be overcome. The main types of process disturbances in agricultural biogas production are classified as unfavorable process temperatures, fluctuations in the availability of macro- and micronutrients (feedstock variability), overload of the microbial degradation potential, process-related accumulation of inhibiting metabolites such as hydrogen (H2), ammonium/ammonia (NH4+/NH3) or hydrogen sulphide (H2S) and inhibition by other organic and inorganic toxicants. Causes, mechanisms and effects on the biogas microbiome are discussed. The need for a knowledge-based microbiome management to ensure a stable and efficient production of biogas with low susceptibility to disturbances is derived and an outlook on potential future process monitoring and control by means of microbial indicators is provided.

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