Front-end Data Acquisition Research Articles

Design of multi-channel electronic prototype for 101Sn energy level lifetime measurement

In this study, a 32-channel front-end data acquisition unit (DAQU) with high temporal resolution and count rate was developed at the Heavy Ion Research Facility in Lanzhou (HIRFL), China, to measure the lifetime of 101Sn on the Spectrometer for Heavy Atoms and Nuclear Structure. The DAQU data analysis module uses a field programmable gate array (FPGA) to implement and time stamp extraction through an FPGA-based tapped delay line (TDL) time-to-digital converter. The energy measurements were implemented using a trapezoidal algorithm and a sliding baseline averaging method. The DAQU was tested and calibrated using a pulse generator and cosmic rays. The results show that the system had a dead time of less than 500 ns, a dynamic range of “0” to “500” mV, and an energy resolution of better than 4.8‰ (full width at the half-maximum, FWHM). In addition, the single-channel temporal resolution under multi-channel settings surpasses 111.2 ps (FWHM), satisfying the experiment's requirements for the electronics system.

Intelligent traffic congestion discrimination method based on wireless sensor network front-end data acquisition

Intelligent traffic congestion discrimination method based on wireless sensor network front-end data acquisition

The high performance parameterization for deep learning in pulse shaping

In high energy physics, front-end data acquisition systems based on analog-to-digital converters (ADC) can provide multiple aspects (time, energy, position) of information when an incident particle is detected. To process the shaped semi-Gaussian pulses from ADCs, multi-layer neural networks (aka. deep learning recently) show excellent accuracy and promising real-time capability. However, several factors, such as sampling rate and precision, neural network quantization bits, and intrinsic noise, complicate the problem and make it hard to find a cost-effective solution with high performance. In this article, we analyze above factors in a systematic way to study the effect of each one on the performance of the network individually when other factors are controlled. Moreover, the proposed network architecture can provide both the time and energy information from a single pulse. When the sampling rate is 2.5 MHz, sampling precision is 5-bit, the network tested in this work with an 8-bit encoder and a 16-bit decoder (designated as N2) achieved the best comprehensive performance in all conditions.

Intelligent traffic congestion discrimination method based on wireless sensor network front-end data acquisition

Intelligent traffic congestion discrimination method based on wireless sensor network front-end data acquisition

Stand-alone Low Power Consumption FEE and DAQ for the Readout of Silicon Photomultipliers.

We developed a front end electronics (FEE) and data acquisition (DAQ) system with a low power consumption, especially intended for stand-alone applications in unattended environments without standard electricity supply. The system works autonomously thanks to dedicated algorithms that are embedded. The FEE is based on the EASIROC chip, designed for the readout of Silicon photomultipliers (SiPMs). It digitizes the amplitude of the signals and provides time information with time of flight capability. The trigger logic is programmable and physical and accidental coincidences rates can be measured. The SiPMs temperature is controlled by thermoelectric cells. Thanks to a network of temperature and humidity sensors, a real-time software sets the optimal operating point of the SiPMs depending on external conditions and if necessary halts the system to avoid damage to the electronics. The system has been used in several muon radiography experiments.

A Textile Manufacturing Information System with Exponential Smoothing Method

The traditional textile industry is characterized by a discrete production pattern, because the manufacturing workshop and equipment are quite old, and the level of information construction is low. To assist textile enterprises in improving the construction of informatization, the utilization of production data, and production management efficiency, the textile manufacturing information system must strengthen data integration. In this paper, a textile manufacturing information system with the exponential smoothing method is proposed. The proposed textile manufacturing information system is to assist managers in making decisions, analyzing data, and providing a convenient platform for sharing information. It uses MySQL and MongoDB dual databases as data storage and uses Apache servers as web services. The front end uses Echarts technology to complete the data visualization. According to the shortcomings in its production management process, the following modules are designed around the needs of the enterprise: production management, equipment management, employee management, statistical information, and basic information maintenance. It also connects with the front-end data acquisition system and presents the data in a visual form to achieve real-time data monitoring of production. Furthermore, the proposed information system uses a single exponential smoothing method to predict production. From the experimental results, the single exponential smoothing method can well predict the trend of textile production output in a short term, and the results are more accurate than other approaches.

Smart Pre-Seeding Decision Support System for Agriculture

In recent years, the Internet of Things (IoT) brings a new dimension for establishing a precision network connectivity of sensors, especially in the agriculture and farming industry, medical, economic, and several sectors of modern society. Agriculture is an important area for the sustainability of mankind engulfing manufacturing, security, and resource management. Due to the exponential diminishing of the resources, innovative techniques to support the subsistence of agriculture and farming. IoT aims to extend the use of internet technology to a large number of distributed and connected devices by representing standard and interoperable communication protocols. This paper brings up a solution by IoT, presents the design and implementation of a smart pre-seeding decision support system for agricultural modernization. This project is accomplished by understanding the real-time circumstances in the agriculture field using wireless technology that highlighted the features including pH and temperature sensors, hardware, mobile application, system’s frontend, and backend analysis, and stores the extracted information in the cloud using IoT. The system is made up of frontend data acquisition, data transmission, data processing, and reception, and is also experimentally validated to find out all possible crops that can be cultivated in a specific land with the required amount of fertilizers as well as the overall crops distribution lists.

A Data-Driven Approach for Electric Energy Equipment Using Wireless Sensing Technology in the Context of Carbon Neutrality

In this paper, we use wireless sensing technology to conduct an in-depth study and analysis of data-driven power energy equipment in the context of carbon neutrality. For the high-order uncertainty of renewable energy power generation and the nonlinearity of the tidal equation, a set of orthogonal bases under arbitrary probability space can be constructed by itself using the high-order information of renewable energy power generation statistics, and then, polynomials fit the state variables such as voltage in the tidal equation using the orthogonal bases and calculate the fitting parameters using the stochastic Gallatin integration method. Based on the analysis of the online monitoring project of the main power equipment in the substation, a substation power equipment condition monitoring system is designed to realize the real-time monitoring of the temperature status of power equipment, substation smoke and temperature, and humidity environment, and the feasibility and advanced of the system are verified by elaborating the analysis. Using wireless transmission to send real-time temperature information to the monitoring background, the infrared thermal imaging online monitoring system is designed around the front-end data acquisition system, transmission network, background data processing, and display module. Saving-investment equilibrium means that total investment equals total savings; government budget balance can be achieved through government savings or deficits. When both supply chain approaches enter into the same environmental competition, the added value that consumers value the product because of the carbon-neutral approach becomes smaller in the coefficient constraint of green effort investment cost due to the competition between the two supply chains, which in turn increases the green investment cost of the supply chain with the green effort carbon-neutral approach, indicating that in the case of competition, consumers, when faced with two products produced by two supply chains, are interested in the product with the carbon-neutral approach has less value-added, and some of the demand is shifted to the product not produced with the carbon-neutral approach.

Design of Automatic Batch Calibration and Correction System for IMU

Thanks to its light weight, low power consumption, and low price, the inertial measurement units (IMUs) have been widely used in civil and military applications such as autopilot, robotics, and tactical weapons. The calibration is an essential procedure before the IMU is put in use, which is generally used to estimate the error parameters such as the bias, installation error, scale factor of the IMU. Currently, the manual one-by-one calibration is still the mostly used manner, which is low in efficiency, time-consuming, and easy to introduce mis-operation. Aiming at this issue, this paper designs an automatic batch calibration method for a set of IMUs. The designed automatic calibration master controller can control the turntable and the data acquisition system at the same time. Each data acquisition front-end can complete data acquisition of eight IMUs one time. And various scenarios of experimental tests have been carried out to validate the proposed design, such as the multi-position tests, the rate tests and swaying tests. The results illustrate the reliability of each function module and the feasibility automatic batch calibration. Compared with the traditional calibration method, the proposed design can reduce errors caused by the manual calibration and greatly improve the efficiency of IMU calibration.

Development and Initial Results of a Brain PET Insert for Simultaneous 7-Tesla PET/MRI Using an FPGA-Only Signal Digitization Method.

In study, we developed a positron emission tomography (PET) insert for simultaneous brain imaging within 7-Tesla (7T) magnetic resonance (MR) imaging scanners. The PET insert has 18 sectors, and each sector is assembled with two-layer depth-of-interaction (DOI)-capable high-resolution block detectors. The PET scanner features a 16.7-cm-long axial field-of-view (FOV) to provide entire human brain images without bed movement. The PET scanner early digitizes a large number of block detector signals at a front-end data acquisition (DAQ) board using a novel field-programmable gate array (FPGA)-only signal digitization method. All the digitized PET data from the front-end DAQ boards are transferred using gigabit transceivers via non-magnetic high-definition multimedia interface (HDMI) cables. A back-end DAQ system provides a common clock and synchronization signal for FPGAs over the HDMI cables. An active cooling system using copper heat pipes is applied for thermal regulation. All the 2.17-mm-pitch crystals with two-layer DOI information were clearly identified in the block detectors, exhibiting a system-level energy resolution of 12.6%. The PET scanner yielded clear hot-rod and Hoffman brain phantom images and demonstrated 3D PET imaging capability without bed movement. We also performed a pilot simultaneous PET/MR imaging study of a brain phantom. The PET scanner achieved a spatial resolution of 2.5 mm at the center FOV (NU 4) and a sensitivity of 18.9 kcps/MBq (NU 2) and 6.19% (NU 4) in accordance with the National Electrical Manufacturers Association (NEMA) standards.

Simultaneous Acquisition of Ultrasound and Gamma Signals with a Single-Channel Readout.

We propose an integrated front-end data acquisition circuit for a hybrid ultrasound (US)-gamma probe. The proposed circuit consists of three main parts: (1) a preamplifier for the gamma probe, (2) a preprocessing analog circuit for the US, and (3) a digitally controlled analog switch. By exploiting the long idle time of the US system, an analog switch can be used to acquire data of both systems using a single output channel simultaneously. On the nuclear medicine (NM) gamma probe side, energy resolutions of 18.4% and 17.5% were acquired with the standalone system and with the proposed switching circuit, respectively, when irradiated with a Co-57 radiation source. Similarly, signal-to-noise ratios of 14.89 and 13.12 dB were achieved when US echo signals were acquired with the standalone system and with the proposed switching circuit, respectively. Lastly, a combined US-gamma probe was used to scan a glass target and a sealed radiation source placed in a water tank. The results confirmed that, by using a hybrid US-gamma probe system, it is possible to distinguish between the two objects and acquire structural information (ultrasound) alongside molecular information (gamma radiation source).

用电信息采集前置性能提升关键技术研究与应用

用电信息采集前置性能提升关键技术研究与应用

Design and Implementation of Intelligent Medical System for Chronic Diseases

With the continuous improvement of human living conditions and the aggravation of global aging level, chronic diseases such as hypertension and diabetes continue to plague human health. Chronic diseases have long duration, difficulty in treatment and high cost. Research on an effective intelligent system to prevent, recognize and control this kind of disease becomes an effective means to fight against this kind of disease. This paper takes chronic diseases as the research object, and proposes a design of intelligent medical system for chronic diseases based on semantic matching by the adaptation of ZigBee technology in the front-end data acquisition. Through the ZigBee wireless sensor network, this system sends the physiological parameters collected by various medical sensors to the intelligent medical system, and innovatively proposes semantic matching algorithm to solve the queuing problem of data transmission, to ensure the accuracy of data transmission. This system employs the improved spatial vector model to process the data uploaded, and uses AES encryption algorithm in the process of data transmission to ensure the security of data transmission. The realization of the intelligent system provides a scientific means of disease management for chronic disease patients, and realizes the effective management of chronic disease, which meets the design requirements and receives great patients’ evaluation.

Intelligent Environment Monitoring System for University Laboratories

In recent years, the laboratory security of universities has become an important issue for students and devices. To solve this security issue, this paper proposes an intelligent monitoring system to realize environment detection in university laboratories. The main purpose of this system is to monitor the laboratory environment data in time and improve the laboratory inspection efficiency. The system consists of a single chip microcomputer, which is the core of this system, a sensor function module and GPRS wireless communication, realizing data monitoring and short message warning. Therefore, three features, front-end data acquisition, data wireless transmission and a security alarm, are achieved by the proposed system. The real experiments show that front-end data acquisition is effective, data transmission is reliable, and the alarm message is received in time. Furthermore, the system, with the modified function modules, can be used in other scenarios to detect environments, and thus has a significant applied value in other areas.

Study of implementing the FEC on SoC FPGA for digital quench detector

Generally, the front-end computer (FEC) in a digital quench detector always acts as a communication platform between front-end data acquisition system and upper monitoring computer. SoC FPGA is the optimal option for building system on chip. Aiming at developing a set of digital quench detectors with higher integration degree, lower cost and stronger portability that meets the needs of different kinds of superconducting magnets, it is essential to develop a universal FEC based on SoC FPGA. The development platform is Cyclone V SX SoC FPGA development board which has a FPGA integrated with an ARM processor. The hardware architecture of the FEC is built by using IP cores and developing custom function modules. On the other hand, the software design mainly consists of transplanting the embedded Linux and developing essential application program for communicating functions. The main function of FEC is reading quench detection data and transferring it to upper monitor computer through Ethernet; the test results indicate that the system design is reasonable and the function is complete. The implementing of FEC on SoC FPGA has set a proper platform for upgrading to support more function for digital quench detection, and it is feasible to integrate more discrete devices onto one piece of SoC FPGA.

Power efficient digital circuits for ECG front end data acquisition mobile system

The electrical motion of the heart is characterised by the ECG signal. ECG elucidation can be used to detect the heart syndrome. This technology has an efficient diagnostic tool, due to the high regard of portable electronic products, low power system has fascinated more consideration in recent years. This work presents digital ECG data acquisition system to diminish the power consumption. In the proposed work, analogue block is not used, they convert the input voltage into a digital code by delay lines. This digital architecture is capable of operating with a low supply voltage such as 0.3 V and 0.1 V. In this architecture, analogue blocks such as low-noise amplifier (LNA) and filters are not used. A digital feedback loop is employed to cancel the impact of the dc offset on the circuit, which eliminates the requirements for coupling capacitors. The circuit is implemented in 130 nm and 65 nm CMOS process. The simulation results illustrate that the front-end circuit of digital architecture for 130 nm consumes 18.9 pW and 65 nm consumes 109 pW of power.

Power efficient digital circuits for ECG front end data acquisition mobile system

The electrical motion of the heart is characterised by the ECG signal. ECG elucidation can be used to detect the heart syndrome. This technology has an efficient diagnostic tool, due to the high regard of portable electronic products, low power system has fascinated more consideration in recent years. This work presents digital ECG data acquisition system to diminish the power consumption. In the proposed work, analogue block is not used, they convert the input voltage into a digital code by delay lines. This digital architecture is capable of operating with a low supply voltage such as 0.3 V and 0.1 V. In this architecture, analogue blocks such as low-noise amplifier (LNA) and filters are not used. A digital feedback loop is employed to cancel the impact of the dc offset on the circuit, which eliminates the requirements for coupling capacitors. The circuit is implemented in 130 nm and 65 nm CMOS process. The simulation results illustrate that the front-end circuit of digital architecture for 130 nm consumes 18.9 pW and 65 nm consumes 109 pW of power.

IIOT-Based Intelligent Control and Management System for Motorcycle Endurance Test

The Industrial Internet of Things (IIOT) is a new generation intelligent system based on the real-time network and embedded system. It combines the global Internet with the new capabilities of direct control of the physical world to promote the rapid development of manufacturing industry and other industries. In this paper, a four-layer IIOT architecture, that is perception executive layer (data acquisition), cognitive layer (business logic, identification, classification), network layer (communication layer), and control layer (external participation), is proposed aiming to the design goal to realize the intelligent management and remote control of motorcycle ’s endurance test. This architecture has a good guiding role for the design and development of IIOT and service-oriented architecture. On this basis, the paper builds the new Internet of Thing test platform management system with the ability of digital intelligent control, intelligent perception and remote intensive management. The system includes a management platform and five sub-system: front-end data acquisition system, control feedback and processing system, data transmission system, database management system, and cloud management system. By improving the interface capability of external (detection) parameters and establishing protocol relationships, the system become an open system with easy management, upgrading, extension, and compatibility. Thus realized the remote monitoring and control management on the endurance test process, improved the ability of cloud services through the cloud monitoring and management platform, and achieved the test control and management systematic, modular, digital, and intelligent.

Remote measurement of low-energy radiation based on ARM board and ZigBee wireless communication

We propose a system for remote measurement of low-energy radiation, which is implemented using an ARM board and a ZigBee module. The ARM STM32F103 board employs a horizontal and vertical moving CMOS camera for front-end data acquisition. The camera can detect radiation over different coordinates given by latitude and longitude in a determined area. For image processing, we used the subtraction–summation algorithm based on gradient multiplication and edge detection. Compared to algorithms such as the max grayscale value, subtraction–summation, and whole summation, the improved subtraction–summation algorithm filters noise and removes the background grayscale value of the whole image to attain higher accuracy, stronger anti-interference ability, and better consistency to determine the radiation dose. We dedicated one port of the transmission module to send data through the STM32F103 board, whereas another port is connected to the ZigBee module for data reception. By employing this architecture, we achieved low power consumption and fast response in the remote data transmission. Overall, the proposed system performs the remote measurement of low-energy radiation with stability and reliability, which is required for critical scenarios such as the remote detection of nuclear radiation.

Distributed real‐time monitoring system for atmospheric particles

Haze occurs frequently in many cities, and becomes the authors' great common concern. A distributed real-time monitoring system for atmospheric particles has been designed, implemented and tested. The proposed system consists of a front-end data wireless acquisition network, an embedded web server system, a central server and remote monitoring terminals. The front-end data-acquisition network is made up of mobile data-acquisition nodes distributed in atmospheric particle monitoring areas which collect atmospheric particle data periodically. The data is transmitted by Jennet wireless network and sent to the Internet through the embedded web servers attached to the coordinator nodes via the serial ports. Only a common Internet browser is required for a remote user to check the atmospheric particle data. The central server is responsible for storing the pollution data for further usage of pollution analysis, evaluation and early warning. In this study, the PM1.0, PM2.5 and PM10 particle data were successfully collected, transmitted and checked by the monitoring system in Lanzhou, China. The results show that the designed system can meet the needs of functional requirements of atmospheric particle monitoring.