Design of a New Seismoelectric Logging Instrument

To increase the accuracy of reservoir evaluation, a new type of seismoelectric logging instrument was designed. The designed tool comprises the invented sonde-structured array complex. The tool includes several modules, including a signal excitation module, data acquisition module, phased array transmitting module, impedance matching module and a main system control circuit, which are interconnected through high-speed tool bus to form a distributed architecture. UC/OS-II was used for the real-time system control. After constructing the experimental measurement system prototype of the seismoelectric logging detector, its performance was verified in the laboratory. The obtained results showed that the consistency between the multi-channel received waveform amplitude and benchmark spectrum was more than 97%. The binary phased linear array transmitting module of the instrument can realize 0° to 20° deflection and directional radiation. In the end, a field test was conducted to verify the tool’s performance in downhole conditions. The results of this test proved the effectiveness of the developed seismoelectric logging tool.

Online System for Power Quality Operational Data Management in Frequency Monitoring Using Python and Grafana

This article proposes a measurement solution designed to monitor the instantaneous frequency in power systems. It uses a data acquisition module and a GPS receiver for time stamping and traceability. A Python-based module receives data, computes the frequency, and finally transfers the measurement results to a database. The frequency is calculated with two different methods, which are compared in the article. The stored data is visualized using the Grafana platform, thus demonstrating its potential for comparing scientific data. The system as a whole constitutes an efficient, low-cost solution as a data acquisition system.

Design of Power Communication Data Network Management System and Implementation of Data Acquisition Module

The power communication network is a separate network from the power grid whose primary purpose is to ensure the power grid's safe operation. This paper expounds the composition of the comprehensive network management architecture of the power communication data network and the implementation of the data acquisition module in the network management system through theoretical analysis, for the reference of relevant personnel, in order to better promote the collection of power grid communication network data.

Analysis of power requirement of a small-sized tracked-tractor during agricultural field operations

A low-powered and high-efficiency electric tracked-tractor would be a suitable option for aged and female farmers to accomplish agricultural field operations such as grass mowing, land leveling, and chemical spraying. The purpose of the study was to analyze the power requirement of a small-sized tracked-tractor during agricultural field operations. A lawnmower and a rear sprayer-trailer were attached to the tractor base, and the average power requirement was measured. The forward speed was considered during the field experiment up to 6 km/h for four different operating stages. The torque data were obtained for unloaded and loaded conditions through a wireless data logger, and a GPS receiver was used to measure the working speed of the tractor. A data acquisition module was used to acquire the sensor signals. The average power requirements for the empty platform with the driver, a lawnmower, a sprayer-trailer (150-L payload), and a lawnmower and 150-L payload trailer were 0.93, 1.27, 1.45, and 1.70 kW, respectively. The result showed the lowest power was required for operating only the tractor, and it was about 51.15% of the motor rated power, where the maximum power consumed approximately 85% of the total rated power to operate both of the lawnmower and sprayer-trailer. The average power requirements of the tracked tractor varied due to the different payloads and operating stages. The experimental results presented in this study would provide guidelines to improve and commercialize the prototype of the small-scaled tracked-tractor for practical use on the agricultural fields.

Online System for Power Quality Operational Data Management in Frequency Monitoring using Python and Grafana

This article proposes a measurement solution designed to monitor instantaneous frequency in power systems. It uses a data acquisition module and a GPS receiver for time stamping. A program in Python takes care of receiving the data, calculating the frequency, and finally transferring the measurement results to a database. The frequency is calculated with two different methods, which are compared in the article. The stored data is visualized using the Grafana platform, thus demonstrating its potential for comparing scientific data. The system as a whole constitutes an efficient low cost solution as a data acquisition system.

Design of a Low-Cost Small-Size Fluxgate Sensor

Traditional fluxgate sensors used in geomagnetic field observations are large, costly, power-consuming and often limited in their use. Although the size of the micro-fluxgate sensors has been significantly reduced, their performance, including indicators such as accuracy and signal-to-noise, does not meet observational requirements. To address these problems, a new race-track type probe is designed based on a magnetic core made of a Co-based amorphous ribbon. The size of this single-component probe is only Φ10 mm × 30 mm. The signal processing circuit is also optimized. The whole size of the sensor integrated with probes and data acquisition module is Φ70 mm × 100 mm. Compared with traditional fluxgate and micro-fluxgate sensors, the designed sensor is compact and provides excellent performance equal to traditional fluxgate sensors with good linearity and RMS noise of less than 0.1 nT. From operational tests, the results are in good agreement with those from a standard fluxgate magnetometer. Being more suitable for modern dense deployment of geomagnetic observations, this small-size fluxgate sensor offers promising research applications at lower costs.

Research on Diagnostic Information of Smart Medical Care Based on Big Data

The medical field has gradually become intelligent, and information and the research of intelligent medical diagnosis information have received extensive attention in the medical field. In response to this situation, this paper proposes a Hadoop-based medical big data processing system. The system first realized the ETL module based on Sqoop and the transmission function of unstructured data and then realized the distributed storage management function based on HDFS. Finally, a MapReduce algorithm with variable key values is proposed in the data statistical analysis module. Through simulation experiments on the system modules and each algorithm, the results show that because the traditional nondistributed big data acquisition module transmits the same scale of data, it consumes more than 3200 s and the transmission time exceeds 3000 s. The time consumption of smart medical care under the 6G protocol is 150 s, the transmission time is 146 s, and the time is reduced to 1/10 of the original. The research of intelligent medical diagnosis information based on big data has good rationality and feasibility.

Smart Feeding Unit for Measuring the Pecking Force in Farmed Broilers

Feeding is one of the most critical processes in the broiler production cycle. A feeder can collect data of force signals and continuously transform it into information about birds’ feed intake and quickly permit more agile and more precise decision-making concerning the broiler farm’s production process. A smart feeding unit (SFU) prototype was developed to evaluate the broiler pecking force and average feed intake per pecking (g/min). The prototype consisted of a power supply unit with a data acquisition module, management software connected to a computer for data storage, and a video camera to verify the pecking force during signal processing. In the present study, seven male Cobb-500 broilers were raised in an experimental chamber to test and commission the prototype. The prototype consisted of a feeding unit (feeder) with a data acquisition module (amplifier), with real-time integration for testing and intuitive operation with Catman Easy software connected to a computer to obtain and store data from signals. The sampling of average feed intake per pecking per broiler (g) was conducted during the first minute of feeding, subtracting the amount of feed provided per the amount of feed consumed, including the count of pecking in the first minute of feeding. An equation was used for estimating the average feed intake per pecking per broiler (g). The results showed that the average broiler pecking force was 1.39 N, with a minimum value of 0.04 N and a maximum value of 7.29 N. The average feed intake per pecking (FIP) was 0.13 g, with an average of 173 peckings per minute. The acquisition, processing, and classification of signals in the pecking force information were valuable during broilers’ feeding. The smart feeding unit prototype for broilers was efficient in the continuous assessment of feed intake and can generate information for estimating broiler performance.

LabVIEW as Power Disturbances Classification Tools

Power disturbances monitoring is one of the important aspects on dealing power quality issue in electrical system. The aims of conducting monitoring process are to identify the real culprit which contribute to the Power Quality (PQ) problem. One of the vital steps during monitoring process is the classifying various type of power disturbance. This classification process is very important to give a right direction towards proposing the correct mitigation technique. In order to produce reliable classification technique, the devices which has a flexibility on accommodating the software and hardware part need to be deployed. The software is need for algorithm development such as signal processing, Artificial Intelligent (AI) as well as statistical analysis. On the hardware part, the device’s ability to acquire the electrical parameter within the electrical system operation is very important. The data acquisition based on the voltage and current is essential to be feed in the classification algorithm in software side. On the other hand, the interfacing devices and data acquisition module need to be developed at the hardware side, LabVIEW manage to accommodate both software and hardware need and further development of the LabVIEW for this purpose will be elaborated in this chapter.

UAV prototype for localization and identification of radioactive contamination and emitters

The Dragon (Drone for RAdiation detection of Gammas and Neutrons) prototype aims at designing and developing an unmanned aerial vehicle (UAV) equipped with a detection system able to identify radioactive materials, spread over an area or located in a specific position. The system is focused on the localization of the unknown emitter and its subsequently identification. The proposed prototype is made up of two easily interchangeable detection systems, one will be used as a counter while the second will be aimed to perform goodresolution gamma spectroscopy. Both solutions have neutron gamma discrimination capability in order to be suitable for special nuclear materials (SNM) detection in gamma contamination background. The data acquisition module is made up of a compact digitizer board (RedPitaya, sampling rate of 125 MHz and 14 bits of resolution.), a mini computer (Raspberry, for example). This combination allows to install an embedded operating system (e.g. Linux) that can run the necessary software for the Data Acquisition (DAQ), like the ABCD distributed DAQ. Our contribution will be aimed to show a comprehensive characterization of the two detection systems, a medium size CLLB scintillation detector, and a large plastic scintillator, EJ-276, in order to assess their potential use in a UAV-based radiation monitoring system.