Measurement of soil electrical conductivity based on direct digital synthesizer (DDS) and digital oscilloscope

Pei, Xiaoshuai; Meng, Chao; Li, Minzan; Yang, Wenhan; Zhou, Peng

doi:10.25165/j.ijabe.20191206.4840

Cited by 3 publications

(3 citation statements)

References 10 publications

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“…Once the central processing unit, XC6SLX45T, of the control cabinet receives instructions from the Bluetooth unit, the generator generates the corresponding signal. Signals in the generator are generated using direct digital synthesizer technology (Ryabov et al., 2018; Pei et al., 2019). A balanced weight is added to the vibration system to ensure the stability of the seismic signals.…”

Section: Methods and Principlesmentioning

confidence: 99%

Seismic communication data processing based on compressed sensing algorithm

Jiang,

Xing

2024

Geophysical Prospecting

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Geophysical prospecting signals encompass subsurface structural information and incorporate textual messages generated in accordance with a specific pattern. These signals can be employed in places without radio access to ensure public and worker safety. Therefore, the use of seismic signals to transmit information through the earth has attracted the attention of researchers in the last decade. Presently, achievements in seismic communication are mainly in the coding, generation, and propagation of seismic signals. Little work has been done on methods to convert seismic signals generated by vibroseis sources into text and broadcast them vocally. Therefore, we built a seismic communication system with 6‐bit code using the American Standard Code for Information Interchange. To better recommend the seismic communication system scheme, the origin, state and principles of seismic communication system are illustrated in detail. Then, a seismic transmitting system is devised with a 500 N vibroseis source, which compiles seismic signals through amplitude modulation. After seismic signals propagate through the earth, they are received by geophones and recorded in seismographs. Through data acquisition based on a compression algorithm, seismic signals are converted into text and voice signals, which significantly reduces the storage and transmission of seismic data.

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Section: Methods and Principlesmentioning

confidence: 99%

Seismic communication data processing based on compressed sensing algorithm

Jiang,

Xing

2024

Geophysical Prospecting

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“…The method of measuring ECa is the four-colter Wenner array method [18] , as shown in Figure 3 and Equation (1). This method has been proven to be stable and accurate.…”

Section: Eca Measurement Principle and Image Analysis Methodsmentioning

confidence: 99%

In-situ soil texture classification and physical clay content measurement based on multi-source information fusion

Meng

Yang

Ren

et al. 2023

International Journal of Agricultural and Biological Engineering

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Soil texture is one of the most important soil characteristics that affect soil properties. Rapid acquisition of soil texture information is of great significance for accurate farmland management. Traditional soil texture analysis methods are relatively complicated and cannot meet the requirements of temporal and spatial resolution. This research introduced a self-developed vehicle-mounted in-situ soil texture detection system, which can predict the type of soil texture and the particle composition of the texture, and obtain real-time data during the measurement process without preprocessing the soil samples. The detection system is mainly composed of a conductivity measuring device, a camera, an auxiliary mechanical structure, and a control system. The soil electrical conductivity (ECa) and the texture features extracted from the surface image were input into the embedded model to realize real-time texture analysis. In order to find the best model suitable for the detection system, measurements were carried out in three test fields in Northeast and North China to compare the performance of different models applied to the detection system. The results showed that for soil texture classification, ExtraTrees performed best, with Precision, Recall, and F1 all being 0.82. For particle content of soil texture prediction, the R 2 of ExtraTrees was 0.77, and RMSE and MAPE were 74.72 and 39.58. It was observed that ECa, Moment of inertia, and Entropy had larger weights in the drawn model influence weight map, and they are the main contributors to predicting soil texture. These results showed the potential of the vehicle-mounted in-situ soil texture detection system, which can provide a basis for fast, cost-effective, and efficient soil texture analysis.

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“…A constant current source provides a constant current between J and K, and the voltage between M and N is measured by a voltmeter. The voltage drop at both ends is calculated, and the soil EC is calculated by this voltage drop [27]. When a conductor has a regular shape, its EC value is a function of cross-sectional area and length.…”

Section: Soil Ec Measurement Principlementioning

confidence: 99%

Development and Application of a Vehicle-Mounted Soil Texture Detector

Meng

Yang

Hong

et al. 2020

Sensors

Self Cite

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It is of great significance to obtain soil texture information quickly for the realization of farmland management. Soil with good particle condition can well regulate the needs of plants for water, nutrients, air, and temperature during crop growth, thereby promoting high crop yields. The existing methods of measuring soil texture cannot meet the requirements of time and spatial resolution. For this reason, a vehicle-mounted soil texture detector was designed and developed based on machine vision and soil electrical conductivity devices. The detector does not require pretreatment such as air-drying and screening of the soil, and completely uses the original information of the farmland. The whole process can obtain the soil texture information in real time, omitting the complicated chemical process, and saving manpower and material resources. The vehicle-mounted detector is divided into a mechanical part, a control part, and a display part. The mechanical part provides measurement support for the acquisition of soil texture information; the control part collects and processes signals and images; the measurement results can be intuitively observed and recorded on the display, and can be operated through the mobile phone. The vehicle-mounted detector obtains soil conductivity through 4 disc electrodes, while the vehicle-mounted industrial camera captures the soil surface image, and extracts texture parameters through image processing, takes EC and texture parameters as input, and the embedded SVM model of the instrument was used to perform soil texture prediction. In order to verify the measurement accuracy of the detector, farmland verification experiments were carried out on farmland loam in Tongzhou District and Haidian District of Beijing. The R2 of the correlation between the measured value of soil EC and the actual value was 0.75, and the accuracy of soil texture prediction was 84.86%. It shows that the developed vehicle-mounted soil texture detector can meet the requirements for rapid acquisition of farmland texture information.

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Measurement of soil electrical conductivity based on direct digital synthesizer (DDS) and digital oscilloscope

Cited by 3 publications

References 10 publications

Seismic communication data processing based on compressed sensing algorithm

Seismic communication data processing based on compressed sensing algorithm

In-situ soil texture classification and physical clay content measurement based on multi-source information fusion

Development and Application of a Vehicle-Mounted Soil Texture Detector

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