Data Acquisition Module Research Articles

Clock and data alignment scheme for readout electronics prototype of PandaX-nT

This work proposes a clock and data alignment scheme for the readout electronics system of the future PandaX-nT dark matter detection experiments. Since the waveform information of the photomultiplier signal is obtained by accumulating all acquisition channels of the front-end digitization module (FDM), it is required that each FDM acquisition channel should be synchronized. The readout electronics system is composed of a clock distribution module, 64 FDMs, and 4 data acquisition (DAQ) modules. The multi-board synchronous acquisition circuit can provide the same REF CLOCK and SYSREF signal for multiple FDMs boards to ensure the alignment of the sampled data collected by the analog-to-digital converter. The data aggregation circuit can ensure that the sampled data of multiple FDM boards are aligned with each other when they are aggregated to the DAQ board. The functional verification test results show that the synchronization between the prototype electronics channels is less than 80 ps, thus enabling to meet the requirements of the readout electronics prototype of PandaX-nT.

598 Temperature profiles of sunlight-exposed surfaces in a desert climate: Determining the risks for pavement burns.

Abstract Introduction In the desert climates of the United States, plentiful sunlight and high summer temperatures cause significant burn injuries from hot pavement and other surfaces. Although it is well known that surfaces reach temperatures sufficient to cause full-thickness burns, the peak temperature, time of day, and highest risk materials is not well described. This work measured continuous temperature measurements of six materials in a desert climate over a five-month period. Methods Six different solid materials common in an urban environment were utilized for measurement. Asphalt, brick, concrete, sand, porous rock, and galvanized metal were equipped with thermocouples attached to a data acquisition module. All solid materials except metal were placed in a 2’x2’x3.5” form, and identical samples were placed in both shade and direct sunlight. Ambient temperature was recorded, and sunlight intensity was measured using a pyranometer. Measurement time interval was set at three minutes. A computational fluid dynamics (CFD) model was created using Star CCM+ to validate the data. Contour plots of temperature, solar irradiance, and time of day were created using MiniTab for all surfaces tested. Results 75,000 temperature measurements were obtained from March through August 2020. Maximum recorded temperatures for sunlight-exposed samples of porous rock was 170 F, asphalt 166 F, brick 152 F, concrete 144 F, metal 144 F, and sand 143 F. Peak temperatures were recorded on August 6, 2020 at 2:10 pm, when ambient temperature was 120 F and sunlight intensity 940 W/m2 (Table). Temperatures ranged from 36 F - 56 F higher than identical materials in the shade at the same time. The highest daily temperatures were achieved between 2:00 pm to 4:00 pm due to maximum solar irradiance. Contour plots of surface temperature as function of solar irradiation and time of day were created for all surfaces tested. Nearly identical results obtained from the CFD models to the experimentally collected data, which validated the experimental data. Conclusions Surfaces exposed to direct, continuous sunlight in a desert climate achieve temperatures from 143 F to 170 F in the early afternoon and are high enough to cause significant injury with sufficient exposure. Porous rock reached the highest temperature, followed closely by asphalt. This information is useful to inform the public of the dangers of exposed surfaces in a desert climate.

Optimization of Quantitative Financial Data Analysis System Based on Deep Learning

In order to better assist investors in the evaluation and decision-making of financial data, this paper puts forward the need to build a reliable and effective financial data prediction model and, on the basis of financial data analysis, integrates deep learning algorithm to analyze financial data and completes the financial data analysis system based on deep learning. This paper introduces the implementation details of the key modules of the platform in detail. The user interaction module obtains and displays the retrieval results through data parsing, calling the background, and computing engine. The data cleaning module fills, optimizes, and normalizes the data through business experience; the calculation engine module uses the algorithm and extracts the database information to get the similar time series and matching financial model. Finally, the data acquisition module fills the database with historical data at the initialization stage and updates the database every day. The data analysis platform for quantitative trading designed and implemented in this paper has carried out demand analysis, design, implementation, and test. From the perspective of function test and performance test, two functions of similar stock search and financial matching model are selected and tested, and the results are in line with the expected results.

Research of Harmonic Index and Testing Method Based on Virtual Instrument

In view of the practical problems such as the imperfect harmonic testing and evaluation methods of the variable frequency speed regulation system and the high operating cost, a harmonic evaluation index system including 9 indexes is established, and the calculation method of each index is clarified. At the same time, the harmonic testing and analysis method of the variable frequency speed regulation system based on virtual instruments is proposed. The Labview software platform is combined with an external data acquisition module to replace the traditional testing instruments for harmonic testing and signal acquisition, processing and analysis. On the basis of theoretical research, an experimental platform was built to conduct verification experiments, and then the application experiments of 2 working conditions were carried out. The results shows that the test method was correct and feasible. Based on the experimental results, further analysis of the impact of harmonics on the performance of the variable frequency speed control system, and the corresponding law of influence will be obtained, which will provide guidance for the subsequent development of harmonic prevention and other related work.

On the in-situ on-line structural health monitoring of composites using screen-printed sensors

This study aims at developing the screen-printed sensors as a viable means of depositing sensing tracks on composites for their on-line structural health monitoring. Conventional silk screen was employed in order to deposit a nano-composite solution comprising of a conductive nano-filler (carbon nano-particles) dispersed in a thermoplastic matrix (high density polystyrene) on laminated composite specimens. The solution was deposited using a squeegee and was allowed to dry. Commercially available metal foil strain gauges were also bonded alongside screen-printed sensor in order to compare the response of the screen-printed sensors with the commercially available strain gauges. The sensing ability of these screen-printed sensors was tested on a universal testing machine (MTS 810) in four-point bending configuration using a load cell of 100 kN. The sensor deposited using screen-printing technique underwent tensile loading at the lower side of the laminate. A data linearization and amplification module comprising of commercially available instrumentation amplifier (INA 118) was used in conjunction with data acquisition module (Keithley KUSB 3100). The results obtained show that the screen-printed sensors have higher gauge factors in tensile loading scenario with reasonably linear response as compared to traditional metal foil strain gauges. The ease of the deposition of a nano-composite solution via screen printing also makes the technique a viable alternative to the traditional resin bonded metal foil strain gauges which have to be bonded on the surface. Moreover, screen printing offers unlimited options for the development of smart composites in various configurations for a multitude of structural applications.

Smart Feeding Unit for Measuring the Pecking Force in Farmed Broilers

Simple SummaryWe present a novel method for assessing broiler pecking force data during feeding. 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. The acquisition, processing, and classification of the pecking force signal information were valuable during broilers’ feeding. The smart feeding unit (SFU) prototype was useful in the continuous generation of information that could be applied to evaluate the amount of pecking force and performance during the broilers’ growth.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.

Gesture recognition device based on cross reticulated graphene strain sensors

Perception and recognition of hand gestures have received much attention for their applications in the human–computer fields. The data-glove application in gesture recognition makes it expediently to track the movements of human fingers. Whereas, the development of the data-glove for hand gesture still face numerous technical difficulties, such as the sensitivity, flexible ability, and system integration under low-cost. In this paper, a simple gesture recognition glove system was developed to characterize the sign language, which consists of cross reticulated graphene (CRG) flexible sensors, a multi-channel data acquisition module, and an artificial neural network algorithm. The designed acquisition module has several channels, so that signs from five sensors can be collected and transferred to the intelligent terminal to execute the hand gesture recognition algorithm. Besides, the recognition results suggest that the recognition rate of the neural network for 22 letters in the English alphabet can reach more than 90% and the overall recognition has an over 86% accuracy.

Improved Timing for better performance of distributed data acquisition systems

Distributed data acquisition systems are the norm in the great majority of industry branches where the process to be controlled covers a physically large and often fragmented area. Many local smaller data acquisition modules are interfaced and pass raw or pre-processed data along with the timing signals. These timing signals are a vital part of data acquisition as oftentimes raw data is processed as time series and correlations are made based on timestamps. This paper presents a study for implementation of a cost-effective high precision time base (reference clock) using a GPS receiver as a primary time source and a local high precision real time clock as a secondary oscillator.

A Preclinical System Prototype for Focused Microwave Breast Hyperthermia Guided by Compressive Thermoacoustic Tomography

As a newly developed technique, focused microwave breast hyperthermia (FMBH) can provide accurate and cost-effective treatment of breast tumors with low side effect. A clinically feasible FMBH system requires a guidance technique to monitor the microwave power distribution in the breast. Compressive thermoacoustic tomography (CTT) is a suitable guidance approach for FMBH, which is more cost-effective than MRI. However, no experimental validation based on a realized FMBH-CTT system has been reported, which greatly hinders the further advancement of this novel approach. We developed a preclinical system prototype for the FMBH-CTT technique, containing a microwave phased antenna array, a microwave source, an ultrasound transducer array and associated data acquisition module. Experimental results employing homogeneous and inhomogeneous breast-mimicking phantoms demonstrate that the CTT technique can offer reliable guidance for the entire process of the FMBH. In addition, small phase noises do not deteriorate the overall performance of the system prototype. The realized preclinical FMBH-CTT system prototype is capable for noninvasive, accurate and low-side-effect breast tumor treatment with effective guidance. The experimentally validated FMBH-CTT system prototype provides a feasible paradigm for CTT guided FMBH, establishes a practical platform for future improvement of this technique, and paves the way for potential clinical translation.

Mobile Phone Remote Controlled Wastewater Treatment Equipment Used in Tribe

This study developed the data acquisition module which involves electronics control hardware and mobile phone APP software, the module could control and monitor wastewater treatment equipment by the APP software running on mobile phone for wastewater treatment in the tribe of eastern Taiwan. The APP user of the tribe can keep abreast of the situation of wastewater treatment and discharge to maintain the water resource with a good water quality.

Design and Implementation of a Real-Time Multi-Beam Sonar System Based on FPGA and DSP.

Aiming at addressing the contradiction between the high-speed real-time positioning and multi-channel signal processing in multi-beam sonar systems, in this work we present a real-time multi-beam sonar system based on a Field Programmable Gate Array (FPGA) and Digital Signal Processing (DSP) from two perspectives, i.e., hardware implementation and software optimization. In terms of hardware, an efficient high-voltage pulse transmitting module and a multi-channel data acquisition module with time versus gain (TVG) compensation with characteristics such as low noise and high phase amplitude consistency, are proposed. In terms of algorithms, we study three beamforming methods, namely delay-and-sum (D&S), direct-method (DM) and Chirp Zeta Transform (CZT). We compare the computational efficiency of DM and CZT in the digital domain. In terms of software, according to the transmission bandwidth of the Gigabit Ethernet and a serial rapid IO (SRIO) interface, the data transmission paths of the acquired data and the beam pattern between the FPGA, the DSP, and a personal computer (PC) are planned. A master-slave multi-core pipelined signal processing architecture is designed based on DSP, which enhances the data throughput of the signal processor by seven times as compared with that of the single-core operation. The experimental results reveal that the sound source level of the transmitting module is around 190.25 dB, the transmitting beam width is 64° × 64°, the background noise of the acquisition module is less than 4 μVrms, the amplitude consistency error of each channel is less than −6.55 dB, and the phase consistency error is less than 0.2°. It is noteworthy that the beam number of the sonar system is 90 × 90, the scanning angle interval is 0.33°, the working distance ranges from 5 m to 40 m, and the maximum distance resolution is 0.384 m. In the positioning experiment performed in this work; the 3-D real-time position of the baffle placed in the detection sector is realized. Please note that the maximum deviation of azimuth is 2°, the maximum deviation of elevation is 2.3°, and the maximum distance deviation is 0.379 m.

Smart wearable monitoring system based on multi-type sensors for motion recognition

Motion monitoring systems are often designed and researched to detect the movement of human lower limbs, and play an important role in the field of exoskeleton control. However, current wearable devices can still be improved to be more convenient or accurate in motion recognition. In this work, a comfortable smart wearable gait monitoring system was designed and tested. Inertial measurement units (IMUs) and flexible membrane compression sensors were implemented, integrated to a comfortable sport pant and insoles of both feet, respectively. Data acquisition module was designed, while software with user interface for data collection and storage was realized based on LABVIEW. Experiments were conducted to evaluate the recognition performance of the smart wearable gait monitoring system among nine common actions. Results show that the combined data set of IMUs and compression sensor provided by the system can highly improve classification performance. Based on the self-designed sensing network and the K-nearest neighbor machine learning algorithm, the recognition rate of nine motion patterns can reach as high as 99.96%, showing that the multi-channel wearable gait monitoring system is more effective for motion detection and prediction compared to that with single-type sensors.

Research on Computer System Implementation of ISO14443B Protocol Communication Data Acquisition based on FPGA

As a programmable logic device, FPGA can be used as a bridge for logic adaptation and timing matching between chip components. For example, in a data acquisition system, data of ten channels need to be collected at the same time. In this case, ten identical data acquisition modules can be instantiated in the FPGA to connect ten external data sensor chips respectively by taking advantage of the parallelism of FPGA, so as to realize the logical adaptation of chip devices. In certain applications such as audio processing, video processing, digital communications, encryption, decryption, etc., as a result of the FPGA computing can parallelism, and FPGA is algorithm Yu into hardware, namely a logic gate and a register, so its execution efficiency usually than machine code and assembly language of single thread special micro processing, the need to replace DSP parallel supercomputing occasions and microprocessors.

Design of embedded application software of 3D camera based on line laser

The embedded application software of the line laser 3D camera running on the Xilinx Zynq7000 SoC which is the control of circuit to extract and transmit the centre of the laser stripe in the line laser 3D contour scanning system to the PC was designed. First, by analysing the functional requirements of the system, a modular software structure for real-time multitasking is proposed, and then the program flow chart, which mainly includes a data acquisition module, parameter configuration module, communication module, and system management module. The system provides two data acquisition channels, namely the original image and the centre point coordinate data, which is convenient for system setup and debugging, and realizes the adjustment of ROI in different scenarios. It has the functions of real-time acquisition of line laser centre point coordinates and online configuration of camera parameters. The debugging of each module can work stably and reliably.

Noninvasive assessment of microbial activity by realtime monitoring degradation of cellulose acetate via electrochemical impedance measurement

Bacteria play essential roles in maintaining soil health, including decomposition of organic and inorganic materials as well as processing nutrients and fertilizers. Careful monitoring of microbial activity has become of great interest in agricultural processes as high levels of activity and diversity can be correlated to soil quality, nutrient availability, as well as provide insight on future crop yields. Although many methods and devices have been developed to enable a better understanding and quantification of the microbial activity levels, most of them are based on laboratory culture assays or are difficult to implement in fields. Here, for the first time, we demonstrate feasibility of a non-destructive, real-time monitoring technique that allows measuring the degradation kinetics of a cellulose acetate (CA) membrane as a direct indicator of the level of cellulase activity of the microorganism within the targeted ecosystem. The sensors are made by depositing a 50-micron thick layer of CA onto circular shaped interdigitated electrodes (IDEs) on a FR-4 glass epoxy substrate with an active sensing area of 12 mm2. The kinetic degradation of the CA membrane was determined by measuring the changes in differential impedance across the IDEs at an operating frequency of 10 kHz. As a proof of concept, the sensors were tested in liquid culture media to monitor the cellulase activity of Pseudomonas aeruginosa, as commonly found bacteria in soil and water. The biodegradation of the CA membrane was successfully measured as a distinct decrease in the impedance of the sensor as the number of Colony Forming Units (CFU/mL) increased in the culture environment with an average linear sensitivity of −139.6Ω/log(CFU/mL) and R2 = 0.98. Sensors were also tested on samples taken from agricultural fields used for crop production. Results of sensors performance in soil provides evidence for using this technique for in-field measurements. Unlike conventional culture-based and DNA extraction techniques, the proposed method provides a real-time assessment of the microorganisms’ activity within their ecosystem. Furthermore, the proposed simple electrical sensing approach paves the road towards developing a new class of biosensors able to easily interface with common wireless data acquisition modules for precision agricultural applications.

Simultaneous Measurements in Shape Memory Alloy Springs to Enable Structural Health Monitoring by Self-Sensing Actuation

The vital sensing parameter on self-sensing actuation in the spring form of shape memory alloy (SMA) is determined through experimental analysis. A unique measurement technique is adopted that interlinks the electro–thermo–mechano features during the shape memory effect in NiTi, NiTiCu, and NiTiFe springs. The influence of the spring index, the number of active turns, material composition, and transition temperature is assessed. SMA spring’s effective functional behavior to be used as an actuator and or a sensor is ensured via the measurement of electrical parameters—the resistance, inductance, and impedance variations revealed during the solid–solid phase change, i.e., displacement. However, the spring form of SMA would exhibit variation in inductance and a variation in electrical resistance, which in turn is considered a variation in the electrical impedance, which may also be appropriate sensing information. The thermo-mechanical and thermo-electrical measurements are synchronized using an impedance analyzer and data acquisition module with a specific programming technique. The active spring is equivalently a series resistance–inductance circuit, since the collective effect of a decrease in resistance and increase in inductance with an increase in temperature offers increased $$\frac{L}{R}$$ and vice versa to support structural health monitoring.

Deep Learning-Based Acoustic Emission Scheme for Nondestructive Localization of Cracks in Train Rails under a Load.

This research proposes a nondestructive single-sensor acoustic emission (AE) scheme for the detection and localization of cracks in steel rail under loads. In the operation, AE signals were captured by the AE sensor and converted into digital signal data by AE data acquisition module. The digital data were denoised to remove ambient and wheel/rail contact noises, and the denoised data were processed and classified to localize cracks in the steel rail using a deep learning algorithmic model. The AE signals of pencil lead break at the head, web, and foot of steel rail were used to train and test the algorithmic model. In training and testing the algorithm, the AE signals were divided into two groupings (150 and 300 AE signals) and the classification accuracy compared. The deep learning-based AE scheme was also implemented onsite to detect cracks in the steel rail. The total accuracy (average F1 score) under the first and second groupings were 86.6% and 96.6%, and that of the onsite experiment was 77.33%. The novelty of this research lies in the use of a single AE sensor and AE signal-based deep learning algorithm to efficiently detect and localize cracks in the steel rail, unlike existing AE crack-localization technology that relies on two or more sensors and human interpretation.

Design and Application of Modular Transportation Status Monitoring System

In this paper, combined with the actual engineering, a modular transportation status monitoring system is designed, which can be used to measure environmental conditions such as vibration, inclination, temperature and humidity during the process of transportation. The system consists of a main control module, a storage module, a data acquisition module, a real-time clock module, a power management module and an alarm module. The design scheme has high development efficiency and strong practicability. The measurement device used in the experiment for environmental monitoring during transportation process performs well, and can be a typical application case of innovative practice teaching

Research and Design of Over - irrigation Control System for Underwater Pouring Concrete of Pile Foundation

The quality of the pile head is the control difficulty of the concrete cast-in-situ pile technology when the bored piles, especially the deep foundation piles, are filled with underwater concrete. The hammer method and volume estimation method are widely used to control concrete over-irrigation height in the existing technology. However, in the actual operation, these two methods are inclined to cause mis-judgment by the field technicians, so it is difficult to accurately determine the over-irrigation height, resulting in the under-irrigation or the excessively high over-irrigation height of the pile head, which seriously affects the construction quality and greatly increase the cost of engineering costs. In order to solve this problem, combining modern sensing technology and communication technology, an over-irrigation height control system of underwater concrete cast-in-situ pile was developed in this paper based on the principle that the buoyancy changes at a certain depth due to the difference between the mud weight and the concrete proportion of the bored pile. The system is mainly composed of sensor based on Hall effect, data acquisition module, wireless communication module, remote network server and monitoring terminal, and serial tests were carried out. The test results show that the system can accurately monitor the concrete level to reach the pre-set height in advance, and timely alarm for overrun, and it is easy to operate and has high popularization value.

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.