Adaptive filtering-based soft sensor method for estimating total nitrogen in aquaponic systems

Li, Hui; Li, Weijun; McEwan, Matthew; Li, Bingbing; Lian, Guoping; Chen, Tao

doi:10.1016/j.compag.2021.106175

Cited by 12 publications

(4 citation statements)

References 35 publications

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“…However, nitrogen sensors are often expensive or unreliable. Li et al (2021) developed a method to continuously estimate and predict the nitrogen concentration of aquaponic systems by integrating mechanistic models, online measurements, and infrequent offline measurement of total nitrogen. Danish et al (2021) proposed a conceptual forefront framework to enable interested parties to correctly model and design their aquaponic projects.…”

Section: Management Researchmentioning

confidence: 99%

Modeling aquaponics: a review on available models and simulation tools

Stalport¹,

Raulier²,

Jijakli³

et al. 2022

Biotechnol. Agron. Soc. Environ.

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Introduction. Aquaponics is quickly expanding. Specific models and modeling tools have been developed within different studies. However, no study has yet attempted nor succeeded in bringing the aquaponic community around a common modeling project to centralize knowledge and develop an effective tool for users and professional growers. Literature. This paper reviews the relevant literature to provide an overview of the available simulation models and associated modeling tools. Furthermore, it identifies the current needs to lead further modeling developments. Conclusions. Several powerful models and modeling tools have been developed but are highly specific to their research scope and are often inaccessible. The modeling knowledge specific to aquaponics is at an advanced stage but is scattered among many different works. Therefore, it is evident that a shared and accessible modeling tool, which is currently missing, would greatly accelerate the development of aquaponics.

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Section: Management Researchmentioning

confidence: 99%

Modeling aquaponics: a review on available models and simulation tools

Stalport¹,

Raulier²,

Jijakli³

et al. 2022

Biotechnol. Agron. Soc. Environ.

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“…The laboratory analysis gives precise measurement of the sulfur content, which however suffers from great measurement delays (up to hours or days). 4,5 The hardware analyzer uses spectrometers for direct measurements, which can shorten the measurement period but suffers from accuracy degradation and high investment and maintenance costs. 6,7 The soft analyzer, which is also known as "soft sensor" or "virtual sensor", virtually estimates the sulfur content of tail oil by developing a mathematical predictive model integrating process knowledge and operation data and by taking easy-to-measure variables (also called secondary variables, such as flow rate, pressure, and temperature) as inputs.…”

Section: Introductionmentioning

confidence: 99%

“…Currently, the ways of measuring the content of tail oil can be grouped into three types, that is, offline laboratory analysis, hardware analyzer, and soft analyzer. The laboratory analysis gives precise measurement of the sulfur content, which however suffers from great measurement delays (up to hours or days) 4,5 . The hardware analyzer uses spectrometers for direct measurements, which can shorten the measurement period but suffers from accuracy degradation and high investment and maintenance costs 6,7 .…”

Section: Introductionmentioning

confidence: 99%

Soft analyzer for sulfur content in tail oil of hydrocracking process based on adaptively regularized dynamic polynomial PLS

Yao,

Shen,

Qiao

et al. 2023

Asia-Pacific J Chem Eng

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Hydrocracking process is an essential and widely used means to remove impurities such as sulfur, nitrogen, and oxygen from heavy oil in refineries. The sulfur content in the tail oil of the hydrogenation process is a key quality index that must be strictly monitored and controlled. However, the traditional measurement ways of the sulfur content suffer from either large delays or high investment and maintenance costs. To this end, a predictive model named “adaptively regularized dynamic polynomial partial least squares (ARDPPLS)” is proposed to develop soft analyzer for sulfur content estimation. The ARDPPLS takes complicated characteristics of the hydrogenation process into consideration, including process dynamics, nonlinearities, and transportation delays of materials and energies. Specifically, the dynamics and nonlinearities are modeled by the finite impulse response paradigm and polynomial fitting, respectively, and the delays of explanatory variables are automatically determined using differential evolution. In particular, a Bayesian inference‐based adaptive regularization scheme for the polynomial partial least squares is designed to tackle overfitting that results from high‐order variable augmentation and high‐order polynomials. The performance of the ARDPPLS is evaluated by a real‐world industrial wax oil hydrocracking process, showing the effectiveness of the ARDPPLS.

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“…Aquaponics is a new type of circulating aquaculture technology that was created by combining two agricultural engineering technologies, i.e., aquaculture and hydroponics [1]. The ammonia nitrogen concentration in traditional aquaculture water, which is delivered to the hydroponic agriculture system of the aquaponic system, increases when fish excreta accumulate and gradually increases the toxicity of the aquaculture water.…”

Section: Introductionmentioning

confidence: 99%

A Co3O4 Nanoparticle-Modified Screen-Printed Electrode Sensor for the Detection of Nitrate Ions in Aquaponic Systems

Thuy

Wang

Zhao

et al. 2022

Sensors

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In this study, a screen-printed electrode (SPE) modified with cobalt oxide nanoparticles (Co3O4 NPs) was used to create an all-solid-state ion-selective electrode used as a potentiometric ion sensor for determining nitrate ion (NO3−) concentrations in aquaculture water. The effects of the Co3O4 NPs on the characterization parameters of the solid-contact nitrate ion-selective electrodes (SC-NO3−-ISEs) were investigated. The morphology, physical properties and analytical performance of the proposed NO3−-ion selective membrane (ISM)/Co3O4 NPs/SPEs were studied by X-ray diffraction (XRD), energy-dispersive spectroscopy (EDS), transmission electron microscopy (TEM), scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), potentiometric measurements, and potentiometric water layer tests. Once all conditions were optimized, it was confirmed that the screen-printed electrochemical sensor had high potential stability, anti-interference performance, good reproducibility, and no water layer formation between the selective membrane and the working electrode. The developed NO3−-ISM/Co3O4 NPs/SPE showed a Nernstian slope of −56.78 mV/decade for NO3− detection with a wide range of 10−7–10−2 M and a quick response time of 5.7 s. The sensors were successfully used to measure NO3− concentrations in aquaculture water. Therefore, the electrodes have potential for use in aquaponic nutrient solution applications with precise detection of NO3− in a complicated matrix and can easily be used to monitor other ions in aquaculture water.

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Adaptive filtering-based soft sensor method for estimating total nitrogen in aquaponic systems

Cited by 12 publications

References 35 publications

Modeling aquaponics: a review on available models and simulation tools

Modeling aquaponics: a review on available models and simulation tools

Soft analyzer for sulfur content in tail oil of hydrocracking process based on adaptively regularized dynamic polynomial PLS

A Co3O4 Nanoparticle-Modified Screen-Printed Electrode Sensor for the Detection of Nitrate Ions in Aquaponic Systems

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