Data Acquisition Monitoring Research Articles

Application of New Energy Composites in Sports Facilities and Fitness Equipment

New energy composite is an advanced material that can replace the traditional single metal material, especially the newly developed or developed material with superior performance. At present, the material is widely used in automobile manufacturing and other fields, but there is a lack of development and application of the material in the field of sports. To solve these problems, this paper puts forward the application of new energy composites in sports facilities and fitness equipment. In this paper, the testing methods of new energy materials, including thermoelectric testing method and energy absorption testing method, can quantitatively evaluate the properties of a kind of new energy composites and point out the direction for the development of materials with high thermoelectric properties and high‐energy absorption and consumption properties. Then, through the preparation experiment of new energy materials, this paper studies the preparation process and self‐shrinkage test of carbon nanomaterials. Finally, it is proposed to use carbon nanomaterials in the sensor design of health monitoring data acquisition system. The experimental results show that when the water ash ratio is low, the self‐shrinkage value of carbon nanomaterial slurry is 74.68% lower than that under the original conditions. In the experimental study of omnidirectional monitoring characteristics, through the repeated tensile tests of rectangular sensor and omnidirectional sensor at different temperatures, it is found that the sensitivity coefficient of the sensor made of carbon nanomaterial is between 55.8 and 60.4, and the maximum fluctuation is only 5. This fully proves that the carbon nanotube omnidirectional sensor has omnidirectional detection ability.

Network monitoring and processing accuracy of big data acquisition based on mathematical model of fractional differential equation

Abstract Aiming at the lack of subjectivity of the network security situation assessment method and the complexity and non-linearity of data obtained through situational factors, a fuzzy neural network security situation which is optimised based on an improved gravitational search algorithm combined with fractional differential equation analysis, as an Evaluation model, is proposed. In order to quickly and accurately predict the situation value of the network security situation at that moment, a method for situation prediction of long-term and short-term memory networks based on an improved Nadam algorithm to optimise the online update mechanism is proposed. Note that the situation time series obtained from online assessment cannot be used in a better and efficient manner. The model can minimise the cost function and update the model more effectively by updating the model parameters online Prediction accuracy. In order to improve the problem of slow convergence speed during model network training, the Look-ahead method is used to improve Nesterov's adaptive gradient momentum estimation algorithm to accelerate the model's convergence. Finally, the simulation results analyse and compare the prediction model, which not only improves the convergence speed of the prediction model, but also greatly reduces the prediction error of the model.

A Supervisory Control Method for Neutron Scattering Superconducting Magnet

A supervisory control for neutron scattering superconducting magnet is proposed in this paper, which adopts hierarchical control strategy. In the field layer, programmable logic controller (PLC) based on monitoring control and data acquisition system is used for automatic control of various working conditions. PLC and upper monitoring computer are independent of each other in the equipment control layer, and independent operation is not dependent on the upper computer, which ensures the independence and safety of the process. The running parameters of superconducting magnet can be detected in real-time with the coverage of local area network (LAN), and the significant equipment of neutron scattering superconducting magnet can be controlled by using real-time control method in the mobile environment. In case of abnormal situation, the backfeed control will be used to realize remote alarm and other functions, which ensures the normal running of neutron scattering superconducting magnet safely and reliably.

Design and Implementation of Inverse Kinematics and Motion Monitoring System for 6DoF Platform

Six-axis motion platforms have a low contraction height and a high degree of freedom. First of all, the designed six-axis crank arm platform, including the motor, reducer, crank arm, link, platform support arm, and upper and lower platforms, can be designed for different bearing requirements. Secondly, it uses a coordinate transform and kinematics theory to derive each motor rotor angle. A set of platform data acquisition (DAQ) monitoring modules was established, and the LabVIEW programming language was used to write measurement software. The monitoring items include displacement, speed, and acceleration, which can be displayed on the screen and recorded by an industrial computer in real time and dynamically. Then, an RS-485 or RS-232 communication transmission interface was used to provide the control system with the related movement information. Finally, an industrial computer combined with a motion control card was used as a control kernel to realize the control algorithms, internet module function, I/O write and read signals, firmware integration, and human–machine interface message. The experimental results validate the appropriateness of the proposed method.

A Near-Zero Power Triboelectric Wake-Up System for Autonomous Beaufort Scale of Wind Force Monitoring

Beaufort scale of wind force monitoring is the basic content of meteorological monitoring, which is an important means to ensure the safety of production and life by timely warning of natural disasters. As there is a limited battery life for sensors, determining how to reduce power consumption and extend system life is still an urgent problem. In this work, a near-zero power triboelectric wake-up system for autonomous Beaufort scale of wind force monitoring is proposed, in which a rotary TENG is used to convert wind energy into a stored electric energy capacitor. When the capacitor voltage accumulates to the threshold voltage of a transistor, it turns on as an electronic switch and the system wakes up. In active mode, the Beaufort scale of wind force can be judged according to the electric energy and the signal is sent out wirelessly. In standby mode, when there is no wind, the power consumption of the system is only 14 nW. When the wind scale reaches or exceeds light air, the system can switch to active mode within one second and accurately judge the Beaufort scale of wind force within 10 s. This work provided a triboelectric sensor-based wake-up system with ultralow static power consumption, which has great prospects for unattended environmental monitoring, hurricane warning, and big data acquisition.

Additive Manufacturing of Large Coreless Filament Wound Composite Elements for Building Construction.

Digitization and automation are essential tools to increase productivity and close significant added-value deficits in the building industry. Additive manufacturing (AM) is a process that promises to impact all aspects of building construction profoundly. Of special interest in AM is an in-depth understanding of material systems based on their isotropic or anisotropic properties. The presented research focuses on fiber-reinforced polymers, with anisotropic mechanical properties ideally suited for AM applications that include tailored structural reinforcement. This article presents a cyber-physical manufacturing process that enhances existing robotic coreless Filament Winding (FW) methods for glass and carbon fiber-reinforced polymers. Our main contribution is the complete characterization of a feedback-based, sensor-informed application for process monitoring and fabrication data acquisition and analysis. The proposed AM method is verified through the fabrication of a large-scale demonstrator. The main finding is that implementing AM in construction through cyber-physical robotic coreless FW leads to more autonomous prefabrication processes and unlocks upscaling potential. Overall, we conclude that material-system-aware communication and control are essential for the efficient automation and design of fiber-reinforced polymers in future construction.

Radiofrequency Exposure Levels from Mobile Phone Base Stations in Outdoor Environments and an Underground Shopping Mall in Japan

Recent progress in wireless technologies has made human exposure to electromagnetic fields (EMFs) increasingly complex. The situation can increase public concerns related to possible health effects due to EMF exposure. Monitoring EMF exposure levels and characterizing them are indispensable for risk communications of human exposure to EMFs. From this background, a project on the acquisition, accumulation, and applications of EMF exposure monitoring data in Japan was started in 2019. One of the objectives of this project is to obtain a comprehensive picture of EMF exposure in actual daily lives. In 2019 and 2020, we measured the electric field (E-field) strength from mainly mobile phone base stations in the same areas as those in measurements conducted in 2006 and 2007 by the Ministry of Internal Affairs and Communications (MIC), Japan, and compared the data to investigate the time-course of the EMF environment. The number of measured points was 100 (10 × 10 grids) in an area of 1 km × 1 km in two urban and two suburban areas, and that in an underground shopping mall was 158. This large-scale study is the first in Japan. As a result, we found that the measured E-field strengths tended to be higher in 2019 and 2020 than those in 2006 and 2007, especially in the mall. However, the median ratios to the Japanese radio wave protection guideline values for urban areas and malls are lower than −40 dB.

Internet-of-things-based four-dimensional high-density electrical instrument for geophysical prospecting

Abstract. The high-density electrical method is a primary method used in shallow geophysical prospecting. Due to the rapid industrial development that has taken place in recent years, the function and performance of high-density electrical instruments have been considerably improved in several aspects. However, most of the electrical instruments currently available on the market still exhibit some shortcomings, such as being bulky, heavy, limited in their data acquisition accuracy, and difficult to connect to the Internet for remote monitoring. To address these problems, this study developed a new multifunctional four-dimensional (4D) high-density electrical instrument based on remote wireless communication technology. The system is small and lightweight, includes an integrated transceiver, has high data acquisition accuracy, and is capable of remote wireless real-time control. In this study, the hardware circuit was designed. The Arm all-in-one (AIO) LJD-eWinV5-ST7 with a 154.4 cm × 87 cm, 800 × 480 high-brightness wide-temperature-range display is used as the host computer, which has the advantages of small size, low power consumption, and abundant hardware resources. Internet of things (IoT) technology is incorporated in the system, and a 4G module is employed to provide a real-time remote control and data acquisition monitoring system based on the cloud platform. Tests showed that this instrument is stable and convenient to use and can meet the requirements for use in field prospecting.

Productivity monitoring in building construction projects: a systematic review

PurposeThe unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.Design/methodology/approachThis study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.FindingsA detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.Originality/valueThis review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.

Design of a Cabled Seafloor Observatory for Marine Ecological Environment Monitoring

Abstract Cabled seafloor in-situ observation systems have drawn much attention in recent years for their capability of facilitating long-term all-weather deep-sea data-intense marine observations. The Penglai in-situ seafloor observation system for ecological environment monitoring is proposed in this paper. The current system consists of an on-shore station, a primary node, and two secondary nodes, but more nodes can be hosted due to its scalability. A looped backbone network connects the on-shore station and primary nodes. Each primary node can host up to four secondary nodes, and each secondary node can host up to eight different sensors. Marine observation data and system work state data are collected and backed up by the on-shore station in a real-time manner. Users can access the ocean observation data via a web page interface. The proposed system has been deployed for more than half a year and will continue to work after that. The field experiment showed that the proposed system worked smoothly in system state monitoring and marine data acquisition. A large amount of oceanographic data with videos has been achieved for future studies.

A Wireless, Low-Power, and Miniaturized EIT System for Remote and Long-Term Monitoring of Lung Ventilation in the Isolation Ward of ICU

Individualized lung-protective ventilation strategy is essential for patients with COVID-19. In this study, a wireless, low-power, and miniaturized electrical impedance tomography (EIT) system was developed for remote and long-term monitoring of lung ventilation for patients with COVID-19 in the isolation ward of ICU. A new strategy of combining filtering and improved voltage-controlled current was employed to design the current source for a simplified system structure, and a new differential receiver circuit consisting of a buffer amplification and a differential amplification was proposed to design the voltage measurement unit for high precision. Moreover, a Bluetooth interface was adopted for wireless data transmission, and components characterized by low power consumption were selected to minimize the system power consumption. The proposed EIT system occupies a total size of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.5\times 4.5\times0.6$ </tex-math></inline-formula> cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> and can work stably within 25 m from the wireless terminal installed with host EIT software. The system has a signal-to-noise of 70 dB at 50 kHz, stability of 0.1% relative change, and power consumption of 114 mW, as tested with a resistor phantom. Furthermore, a comparison between the proposed system and a commercial ICU EIT device was conducted on nine healthy volunteers for ventilation monitoring. The correlation between lung volume and relative impedance changes was higher than 0.9 for both EIT systems ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$p &lt; 0.001$ </tex-math></inline-formula> ). The analysis of the corresponding EIT images revealed that both systems delivered comparable images in terms of linearity, repeatability, and regional ventilation distribution. The test and experimental results suggested that the proposed system could conveniently provide reliable data acquisition (DAQ) for remote and long-term lung ventilation monitoring.

Research on Intelligent Monitoring and Early Warning of Electric Power Safety Based on Artificial Intelligence Technology

In recent years, with the continuous improvement of the national economic development level, the scale of urban construction in China is also gradually expanding. Therefore, since the monitoring system plays an important role in various industries, the establishment of an intelligent automatic management system can determine the unstable factors in the monitoring management and improve the safety performance of the monitoring system, so that the normal operation of the monitoring platform can be maintained. The establishment and function of the intelligent monitoring and early warning system are analyzed and studied in the paper, which combines traditional video monitoring equipment and data acquisition equipment into one, and launches a monitoring and early warning solution.

Construction of Wireless Underground Footwork Mobile Training and Monitoring Sensor Network in Venues of Major Sports Events

At the Summer Olympics in Tokyo, technology was used extensively in major sports events. The level of foot movement ability greatly affects the performance of sports technology. Modern sports are developing in the direction of high speed, high skills, flexibility, and rapidity, and more and more reflect the important position of reasonable and accurate foot movement ability in sports. This article uses wireless sensor technology and wireless communication technology to design the overall architecture of the wireless underground footwork mobile training and monitoring network in venues of major sports events. According to the determined monitoring parameters and data transmission plan, a wireless remote monitoring data acquisition system is designed, and the hardware design, software design, and networking of the wireless monitoring node are completed, so as to realize the real‐time monitoring and remote transmission of the underlying data. This paper proposes a wireless sensor network management architecture and method based on multiagent cooperation and combines active and passive wireless underground footwork mobile training and monitoring for experimental verification. A multitask allocation strategy optimized for network working life is proposed. A genetic algorithm is used to model and optimize the task data report routing of cluster head nodes. The simulation experiment results show that the wireless sensor network management method based on multiagent cooperation can effectively coordinate different monitoring sensor nodes to complete the assigned monitoring tasks; the multitask assignment strategy based on a genetic algorithm can optimize the working life of the application network.

Research on Monitoring System of Building Slope Deformation Based on Internet of Things

A building slope deformation monitoring system based on the Internet of Things technology was studied in this paper. Through the powerful data acquisition, storage, calculation and analysis capabilities of new technologies such as sensors, cloud computing, big data communication and visualization, and a variety of monitoring data acquisition instruments, sensors, communication terminals, cloud platform and other software and hardware resources as the carrier, it can realize real-time online equipment, continuous data acquisition, real-time calculation, data analysis, emergency warning, and the whole process of deformation monitoring services. Our research solves the deficiency of traditional technical means and effectively improves the timeliness, reliability and information level of construction slope deformation monitoring.

An Integrated Framework of Drivetrain Degradation Assessment and Fault Localization for Offshore Wind Turbines

As wind energy proliferates in onshore and offshore applications, it has become significantly important to predict wind turbine downtime and maintain operation uptime to ensure maximal yield. Two types of data systems have been widely adopted for monitoring turbine health condition: supervisory control and data acquisition (SCADA) and condition monitoring system (CMS). Provided that research and development have focused on advancing analytical techniques based on these systems independently, an intelligent model that associates information from both systems is necessary and beneficial. In this paper, a systematic framework is designed to integrate CMS and SCADA data and assess drivetrain degradation over itslifecycle. Information reference and advanced feature extraction techniques are employed to procure heterogeneous health indicators. A pattern recognition algorithm is used to model baseline behavior and measure deviation of current behavior, where a Self-organizing Map (SOM) and minimum quantization error (MQE) method is selected to achieve degradation assessment. Eventually, the computation and ranking of component contribution to the detected degradation offers component-level fault localization. When validated and automated by various applications, the approach is able to incorporate diverse data resources and output actionable information to advise predictive maintenance with precise fault information. Theapproach is validated on a 3 MW offshore turbine, where an incipient fault is detected well before existing system shuts down the unit. A radar chart is used to illustrate the fault localization result.

IoT for Monitoring and Control of Water Quality Parameters

&lt;p class="0abstract"&gt;&lt;span lang="EN-US"&gt;This work presents an Internet of Things (IoT) solution to facilitate real time water quality monitoring by enabling the management of collected data from electronic sensors. Firstly, we present in detail problems encountered during the used data collection process. We discuss after the requirements from the water monitoring quality standpoint, data acquisition, cloud processing and data visualization to the end user. We designed a solution to minimize technicians’ visits to isolated water tower, we designed sensors achieving a lifespan of several years. The solution will be capable of scaling the processing and storage resources. This combination of technologies can cope with different types of environments. The system also provides a notification to a remote user, when there is a non-conformity of water quality parameters with the pre-defined set of standard values.&lt;/span&gt;&lt;/p&gt;

Structural condition monitoring system of steam/water piping in thermal power plant and its application

In view of the steam/water piping outside the boiler of thermal power unit, considering its spatial structure characteristics of long distance, large drop and the working conditions under high temperature, high pressure and flexible operation. On the base of the static and dynamic analysis of the structure, the key nodes and parameters of monitoring were selected, the method of sensor installation and debugging was put forward, which was easy to maintain and reliable. A distributed monitoring data acquisition and digital processing analysis system was developed. The monitoring results showed that the monitoring system ran stably and reliably, and the test data of each node could accurately reflect the structural state of the piping. The monitoring system has a strong engineering application value.

Successful implementations of a real-time and intelligent early warning system for loess landslides on the Heifangtai terrace, China

Real-time monitoring and intelligent early warning system are crucial and significant to take mitigation measures and reduce casualties and property losses related to landslides. It is difficult to obtain entire monitoring data in the accelerated deformation phase in a landslide event, and hard to issue early warning information using a traditional monitoring approach with fixed and low sampling frequency. Displacement increments of loess landslides induced by agriculture irrigation on the Heifangtai terrace could be sudden and extremely rapid. Typical landslide types include loess flowslides and loess falls. It is of practical significance to develop a self-adaptive data acquisition monitoring technique and establish a real-time landslide early warning system (LEWS) to meet the needs for risk mitigation of rapid sliding slopes on the Heifangtai terrace. The monitoring technique can wirelessly transmit displacement data and the LEWS was devised using the new artificial intelligence. The LEWS could automatically release the warning information in advance of the event once the early warning parameters exceed default thresholds. In this study, the early warning procedures, real-time monitoring approach, intelligent LEWS, a multiple criteria warning model, warning release and emergency mitigation measures, and performance are introduced in detail. Six loess landslides at Heifangtai and eight landslides in other regions of China have been successfully warned since its implementation in 2012. This study proposed an effective and practical solution for the early warning of loess landslides at Heifangtai. Two typical loess landslides that had successful early warnings at Heifangtai were presented. The successful implementation could serve as a reference for global rapid slope failure cases, considering the complex nature of landslide behaviors and failure mechanisms.

FIELD LOADING-TEST BASED SHM SYSTEM SAFETY STANDARD DETERMINATION

Structural health monitoring (SHM) allows for real-time structural response monitoring and online data acquisition of bridge structures. This data reflects the operational and environmental conditions of the bridge, which is important in identification of possible anomalous changes. In order to effortlessly determine the safety condition of the bridge directly through the transferred data without data analysis, a five-level safety standard system will be established for real-time safety warning in this paper. The threshold of each safety levels will be determined through field loading tests results on an external prestressing rehabilitated continuous rigid frame bridge, of which permanent structural health monitoring system was instrumented. After overall evaluation, we come to the conclusion that the rehabilitation is successful and that the bridge is under safe operating condition. A novel, simplified safety standard thresholding technique is proposed based on static loading test results as well as ultimate limit state of the bridge. This technique is simple yet very practical in daily bridge monitoring.

On VDES/ECDIS Integration

Recently, the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA) has developed VHF data exchange system (VDES). It is recognized as an efficient tool for the usage of the radio spectrum with applied new techniques in information transmission. The authors propose the possibilities of VDES to be integrated with Electronic Chart Display and Information system (ECDIS), performing as a single point for data acquisition and distribution for monitoring and processing in the ECDIS. VDES satellite link component is emphasized as a part which could extend the safety of navigation as well as possible VDES applications for future service. A completely new architecture is proposed to get efficient and reliable data path, especially in ship’s communications. VDES could become a key point in safe and secure communications with both terrestrial and satellite components, resulting in a new area of integration possibilities. The main role of VDES in ship communications could be in critical instances of the ship’s operation as well as distress situations.