Physico-Mathematical Model of an Ultrasonic Flow-Through System Based on Fuzzy Logic for Automated Counting of Shrimp Eggs in Aquaculture

whiteeva@list.ru Vladimirovich belyakov; Viktor Aleksandrovich Klimov

whiteeva@list.ru Vladimirovich belyakov Razumovsky Moscow State University of Technologies and Management (FCU) https://orcid.org/0009-0006-2127-095X
Viktor Aleksandrovich Klimov Razumovsky Moscow State University of Technologies and Management (FCU) https://orcid.org/0000-0002-9984-4574

Keywords: ultrasonic detection, aquaculture, Macrobrachium rosenbergii, egg counting, fuzzy logic, piezoelectric transducer, acoustic impedance, signal processing, non-destructive monitoring, flow-through system.

Abstract

This review article presents a theoretical foundation for the development of an ultrasonic flow-through system based on piezoelectric transducers and fuzzy logic algorithms for automated counting of giant river prawn (Macrobrachium rosenbergii) eggs in aquaculture. The study addresses the critical need for non-invasive, high-accuracy monitoring of reproductive processes under conditions of reduced water transparency, where traditional optical and mechanical methods exhibit significant limitations. A comprehensive physico-mathematical model is proposed, integrating fundamental principles of acoustics, wave scattering theory, and impedance matching to describe the amplitude of ultrasonic signals reflected from individual eggs. The model incorporates geometric diffraction coefficients, Fresnel reflection at media interfaces, and exponential attenuation according to the Bouguer–Lambert law. Key design parameters of high-frequency piezoelectric transducers (5–15 MHz) are analysed, including resonant frequency calculation and impedance matching strategies to minimise energy losses. A fuzzy logic controller architecture is introduced, utilising normalised signal amplitude and pulse duration as input variables to classify detected objects while accounting for biological variability and environmental noise. Theoretical projections suggest a ~40% reduction in false alarm rates compared to conventional threshold-based methods. Technical challenges, including temperature-induced sound speed drift and interference from air bubbles, are discussed alongside proposed mitigation strategies involving dynamic frequency correction and power spectral density analysis. The article concludes with a roadmap for experimental validation, algorithm optimisation, and system scaling, positioning the proposed approach as a promising solution for enhancing productivity and sustainability in shrimp aquaculture.