Jianian Li , Yongzheng Ma , Chuanke Yang , Jiaoli Fang , Jiawen Liang
{"title":"基于多段电容式传感器与RLC共振相结合的肥料成分信息在线采集","authors":"Jianian Li , Yongzheng Ma , Chuanke Yang , Jiaoli Fang , Jiawen Liang","doi":"10.1016/j.flowmeasinst.2025.103029","DOIUrl":null,"url":null,"abstract":"<div><div>Irrigation-fertilization integration is a vital component of agricultural development, and the detection of fertilizer solution component information serves as a key link in this integration process. However, conventional detection methods for fertilizer solution components are plagued by deficiencies, including the incapacity to execute real-time online monitoring and a tendency to generate excessively large detection errors. In order to address these challenges, the study has designed a multi-segment capacitive sensor and proposed an online detection method based on RLC resonance and characteristic frequency response. The validity of the method is established through the utilization of urea, calcium superphosphate, potassium sulfate, potassium dihydrogen phosphate, ammonium dihydrogen phosphate, and compound fertilizers as test subjects. Firstly, the frequency response characteristics within the range of 1 kHz–30 MHz are investigated. The findings indicate that the sensor demonstrates optimal detection performance within the frequency range of 1 MHz–20 MHz Secondly, the characteristic frequencies of different fertilizer solutions are determined as 7.5 MHz, 9.5 MHz, 14.5 MHz, 3 MHz, 11.5 MHz, and 17.5 MHz based on the series resonance response characteristics. A concentration detection model based on the sensor's amplitude voltage is constructed, with determination coefficients (R<sup>2</sup>) all exceeding 0.9909. Finally, a detection strategy of multi-segment parallel operation with a “species-first-then-concentration\" approach is adopted for qualitative and quantitative analysis of fertilizer solutions. Validation results show that the species recognition accuracy exceeds 94 %, and the concentration detection error is less than ±7.5 %. This research meets the demand for online detection of fertilizer solution components and concentrations in agricultural engineering, providing technical support for the development of irrigation-fertilization integration technology.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"106 ","pages":"Article 103029"},"PeriodicalIF":2.7000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On-line acquisition of fertilizer ingredient information based on multi-segment capacitive sensor combined with RLC resonance\",\"authors\":\"Jianian Li , Yongzheng Ma , Chuanke Yang , Jiaoli Fang , Jiawen Liang\",\"doi\":\"10.1016/j.flowmeasinst.2025.103029\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Irrigation-fertilization integration is a vital component of agricultural development, and the detection of fertilizer solution component information serves as a key link in this integration process. However, conventional detection methods for fertilizer solution components are plagued by deficiencies, including the incapacity to execute real-time online monitoring and a tendency to generate excessively large detection errors. In order to address these challenges, the study has designed a multi-segment capacitive sensor and proposed an online detection method based on RLC resonance and characteristic frequency response. The validity of the method is established through the utilization of urea, calcium superphosphate, potassium sulfate, potassium dihydrogen phosphate, ammonium dihydrogen phosphate, and compound fertilizers as test subjects. Firstly, the frequency response characteristics within the range of 1 kHz–30 MHz are investigated. The findings indicate that the sensor demonstrates optimal detection performance within the frequency range of 1 MHz–20 MHz Secondly, the characteristic frequencies of different fertilizer solutions are determined as 7.5 MHz, 9.5 MHz, 14.5 MHz, 3 MHz, 11.5 MHz, and 17.5 MHz based on the series resonance response characteristics. A concentration detection model based on the sensor's amplitude voltage is constructed, with determination coefficients (R<sup>2</sup>) all exceeding 0.9909. Finally, a detection strategy of multi-segment parallel operation with a “species-first-then-concentration\\\" approach is adopted for qualitative and quantitative analysis of fertilizer solutions. Validation results show that the species recognition accuracy exceeds 94 %, and the concentration detection error is less than ±7.5 %. This research meets the demand for online detection of fertilizer solution components and concentrations in agricultural engineering, providing technical support for the development of irrigation-fertilization integration technology.</div></div>\",\"PeriodicalId\":50440,\"journal\":{\"name\":\"Flow Measurement and Instrumentation\",\"volume\":\"106 \",\"pages\":\"Article 103029\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Flow Measurement and Instrumentation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0955598625002213\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Flow Measurement and Instrumentation","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0955598625002213","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
On-line acquisition of fertilizer ingredient information based on multi-segment capacitive sensor combined with RLC resonance
Irrigation-fertilization integration is a vital component of agricultural development, and the detection of fertilizer solution component information serves as a key link in this integration process. However, conventional detection methods for fertilizer solution components are plagued by deficiencies, including the incapacity to execute real-time online monitoring and a tendency to generate excessively large detection errors. In order to address these challenges, the study has designed a multi-segment capacitive sensor and proposed an online detection method based on RLC resonance and characteristic frequency response. The validity of the method is established through the utilization of urea, calcium superphosphate, potassium sulfate, potassium dihydrogen phosphate, ammonium dihydrogen phosphate, and compound fertilizers as test subjects. Firstly, the frequency response characteristics within the range of 1 kHz–30 MHz are investigated. The findings indicate that the sensor demonstrates optimal detection performance within the frequency range of 1 MHz–20 MHz Secondly, the characteristic frequencies of different fertilizer solutions are determined as 7.5 MHz, 9.5 MHz, 14.5 MHz, 3 MHz, 11.5 MHz, and 17.5 MHz based on the series resonance response characteristics. A concentration detection model based on the sensor's amplitude voltage is constructed, with determination coefficients (R2) all exceeding 0.9909. Finally, a detection strategy of multi-segment parallel operation with a “species-first-then-concentration" approach is adopted for qualitative and quantitative analysis of fertilizer solutions. Validation results show that the species recognition accuracy exceeds 94 %, and the concentration detection error is less than ±7.5 %. This research meets the demand for online detection of fertilizer solution components and concentrations in agricultural engineering, providing technical support for the development of irrigation-fertilization integration technology.
期刊介绍:
Flow Measurement and Instrumentation is dedicated to disseminating the latest research results on all aspects of flow measurement, in both closed conduits and open channels. The design of flow measurement systems involves a wide variety of multidisciplinary activities including modelling the flow sensor, the fluid flow and the sensor/fluid interactions through the use of computation techniques; the development of advanced transducer systems and their associated signal processing and the laboratory and field assessment of the overall system under ideal and disturbed conditions.
FMI is the essential forum for critical information exchange, and contributions are particularly encouraged in the following areas of interest:
Modelling: the application of mathematical and computational modelling to the interaction of fluid dynamics with flowmeters, including flowmeter behaviour, improved flowmeter design and installation problems. Application of CAD/CAE techniques to flowmeter modelling are eligible.
Design and development: the detailed design of the flowmeter head and/or signal processing aspects of novel flowmeters. Emphasis is given to papers identifying new sensor configurations, multisensor flow measurement systems, non-intrusive flow metering techniques and the application of microelectronic techniques in smart or intelligent systems.
Calibration techniques: including descriptions of new or existing calibration facilities and techniques, calibration data from different flowmeter types, and calibration intercomparison data from different laboratories.
Installation effect data: dealing with the effects of non-ideal flow conditions on flowmeters. Papers combining a theoretical understanding of flowmeter behaviour with experimental work are particularly welcome.