Real-time Online Monitoring System Research Articles

An Online Digital Imaging Excitation Sensor for Wind Turbine Gearbox Wear Condition Monitoring Based on Adaptive Deep Learning Method.

This paper designed and developed an online digital imaging excitation sensor for wind power gearbox wear condition monitoring based on an adaptive deep learning method. A digital imaging excitation sensing image information collection architecture for magnetic particles in lubricating oil was established to characterize the wear condition of mechanical equipment, achieving the real-time online collection of wear particles in lubricating oil. On this basis, a mechanical equipment wear condition diagnosis method based on online wear particle images is proposed, obtaining data from an engineering test platform based on a wind power gearbox. Firstly, a foreground segmentation preprocessing method based on the U-Net network can effectively eliminate the interference of bubbles and dark fields in online wear particle images, providing high-quality segmentation results for subsequent image processing, A total of 1960 wear particle images were collected in the experiment, the average intersection union ratio of the validation set is 0.9299, and the accuracy of the validation set is 0.9799. Secondly, based on the foreground segmentation preprocessing of wear particle images, by using the watered algorithm to obtain the number of particles in each size segment, we obtained the number of magnetic particle grades in three different ranges: 4-38 µm, 39-70 µm, and >70 µm. Thirdly, we proposed a method named multidimensional transformer (MTF) network. Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) are used to obtain the error, and the maintenance strategy is formulated according to the predicted trend. The experimental results show that the predictive performance of our proposed model is better than that of LSTM and TCN. Finally, the online real-time monitoring system triggered three alarms, and at the same time, our offline sampling data analysis was conducted, the accuracy of online real-time monitoring alarms was verified, and the gearbox of the wind turbine was shut down for maintenance and repair.

Analysis and experimental research of transient temperature rise characteristics of high-speed cylindrical roller bearing

In this paper, on one hand, the time-varying characteristics of the heat source and thermal boundary conditions of the high-speed spindle system were analyzed considering the thermal-structural coupling effect. And a transient bearing temperature field prediction method combining the thermal network method and finite element method was proposed. Furthermore, the relationships between time step, calculation efficiency and calculation results were analyzed. On the other hand, a online real-time monitoring system of the transient temperature of the cylindrical roller bearing inner ring for maximum speed of 13,000 r/min was designed and implemented using fibre optic sensing technology. Comparing with the conventional static thermal analysis results, it is verified that the simulation method proposed in this paper has higher accuracy. This paper provides a new approach for analysing and testing the thermal characteristics of high-speed spindle system.

Floor heave mechanism for gob-side entry retaining with concrete blocks and control method: A case study

The issue of significant floor heave deformation in gob-side entry retaining has long been a challenging problem in the context of longwall mining. This paper studies the floor heave failure mechanism and control method for gob-side entry retaining with concrete blocks in Guizhou Faer Coal Mine in China. Based on Rankine’s earth pressure theory, the effective shear stress equation for the plastic slip of roadway floor is established. The deformation mechanism of floor heave in a retaining roadway with a block wall is revealed in this study. The new comprehensive control method is proposed, encompassing roof pre-splitting blasting for pressure relief, reinforcing cables for roof control, double directions control bolts for concrete block, and pliability cushion yielding pressure. FLAC3D numerical calculation model is established, which shows that the new method can effectively reduce the average vertical stress peak value of the entity coal floor by 34.6% and significantly reduce the pressure source causing the roadway floor heave. Besides, a multi-parameter real-time online monitoring system for mine pressure was designed, and field tests were carried out. The results show that the maximum value of roadway floor heave under the new method is 163 mm, reduced by 66.9%, and the roadway floor heave is effectively controlled. These research findings offer a fresh perspective and new ideas for controlling floor heave in mining operations.

Achieving a real-time online monitoring system for conservation culturomics.

Environmental monitoring is increasingly shifting toward a set of systems that describe changes in real time. In ecology specifically, a series of challenges have prevented the rollout of real-time monitoring for features such as biodiversity change or ecosystem service provision. Conservation culturomics, a field concerned with interactions between people and nature, is well placed to demonstrate how monitoring might move toward a network of real-time platforms, given its existence exclusively in the digital realm. We examined a set of considerations associated with the development of real-time monitoring platforms for conservation culturomics and introduce a near real-time platform for the Species Awareness Index, a global index of changing biodiversity awareness derived from the rate of change in page views for species on Wikipedia. This platform will update automatically each month, operating in near real time (https://joemillard.shinyapps.io/Real_time_SAI/). There are plans to make the underlying data queryable via an application programing interface independent of the platform. The real-time Species Awareness Index will represent the first real-time and entirely automated conservation culturomic platform and one of the first real-time platforms in the discipline of ecology. Real-time monitoring for culturomics can provide insight into human-nature interactions as they play out in the physical realm and provide a framework for the development of real-time monitoring in ecology. Real-time monitoring metrics can be processed on private virtual machines and hosted on publicly available cloud services. Conservation now needs an online, real-time observatory that can evolve with the structure of the web.

Construction and Application of On-Line Roof Separation Monitoring System Based on High-Precision FBG Indicator

Aiming at the existing problems of low efficiency, lagging monitoring results, and poor reliability and accuracy in the present roadway roof separation monitoring system, a high-precision Fiber Bragg Grating (FBG) separation indicator is designed through theoretical analysis, numerical simulation, and laboratory tests—according to the fiber grating sensing principle. Based on the Microsoft. Net platform, C# programming language, and VS2010 integrated development tools, the corresponding on-line monitoring software is developed. On this basis, a real-time on-line roof separation monitoring system is proposed. The high-precision FBG separator was calibrated and tested in the laboratory and results suggested that both the left and right arm demonstrate good sensitivity and linearity with linear fitting coefficient values of 0.9981 and 0.9979, respectively. The monitoring system was successfully applied to roof separation monitoring of the #14301 rail roadway in the Shaqu coal mine. The monitoring results showed that the on-line roof separation monitoring system based on the high-precision FBG separation indicator has the advantages of high precision, good stability, and long-distance signal transmission, which can achieve real-time dynamic monitoring and provides an effective method for long-term on-line monitoring of roadway roof separation.

A Study on The Wireless Remote Safety Measurement Device for Structures based on Multi-Waterproof Sensors

Recently, as the need for constant safety management increases due to collapse accidents caused by external displacement of buildings, it is necessary to manufacture a construction ground gradient meter and serial open information technology (IT) sensor that can be monitored wirelessly based on epoxy resins, polyvinyl chloride (PVC) pipes, and communication cables. In particular, waterproof performance is required for ground monitoring of underground spaces with water, and for this purpose, research was also conducted to double mold the inside of the incline system. Construction IT convergence's building slope measurement device technology can respond to safety accidents by checking the amount of change in building displacement through a real-time online monitoring system. In addition, it is an industry with various application markets by converging IT technology into the existing construction industry and can be used as a pre-quake detection monitoring system for structural collapse accidents caused by external displacement. Therefore, it is intended to secure a sustainable facility safety management system through research in the field of real-time measurement technology on various facilities and surrounding ground behavior.

Design of On-line Monitoring System for Photovoltaic Power Generation Power Quality Based on Stm32

Monitoring the quality of photovoltaic power generation in remote mountain areas is difficult, so this paper proposes a real-time online monitoring system to solve the problem by using AD7606 high-precision ADC chip and STM32 single-chip microcomputer. AD7606 realizes real-time acquisition and conversion of three-phase power data. STM32 performs wavelet transformation on the collected data to obtain power quality parameters. It stores the power quality parameters in the SD card and then uploads the power quality parameters to the host computer through Lora to display each power quality parameter in real time. Experiments show that the system can reliably realize on-line real-time monitoring of the power quality of photovoltaic power generation.

Design and Test of the Seedling Cavitation and Lodging Monitoring System for the Rape Blanket Seedling Transplanter

To realize the real-time monitoring of the lodging and cavitation state of the rape blanket seedling transplanter, a real-time online monitoring system set for cavitation and lodging based on machine vision was designed. The system was mainly composed of an image acquisition module, a height sensor, and an IPC (Industrial Personal Computer). When the system starts to work, the height of the lens from the ground and the collected images are saved in real time, and the operating status of the equipment is judged according to the height of the lens from the ground, and the actual corresponding size of the image pixels is corrected. We proposed a calculation method for judging the cavitation and lodging state of the seedlings based on the comparison between the actual planting position and the theoretical planting position of the seedlings. The processing and analysis software for the cavitation and lodging monitoring system of the rape blanket transplanter was compiled, and the monitoring system was developed. The dynamic test showed that the maximum absolute error of the cavitation recognition rate was 1.23%, and the maximum absolute error of the lodging recognition rate was 3.80%. The total time consumed of a 1 m image collected in real time from the collection, image processing and stitching, to seedling status recognition of the rape blanket seedling field was about 1 s. The accuracy and system processing time of the seedling cavitation and lodging state judgment can meet the accuracy and real-time requirements of cavitation and lodging state recognition for field transfer of rape blanket seedlings.

Research and Implementation of Mine Environment Online Real-time Monitoring System Based on Internet of Things

Research and Implementation of Mine Environment Online Real-time Monitoring System Based on Internet of Things

IoT Online Monitoring System on Pulp and Paper Industry Wastewater Treatment Plant

As one of the largest wastewater producers in the world, the pulp and paper industry need to monitor the waste that they generated. To carry out this monitoring process, the majority of the pulp and paper industry still uses conventional offline methods to measure parameters in their wastewater treatment plants. The monitoring procedure is carried out by taking samples from the factory wastewater treatment plant and testing these samples in the laboratory. This procedure is very prone to errors caused by human. This method also cannot detect any violation, problem, or disturbance of the wastewater parameters in real time. In addition, in 2018, the Indonesian Ministry of Environment and Forestry issued a regulation requiring the pulp and paper industry to use a real-time online monitoring system for its wastewater treatment plant.
 This paper presents an implementation of the system. There are several parameters that must be measured, two of them are pH and TSS (Total Suspended Solids). To measure these parameters, the regulation states that the online measurement system is carried out using the relevant electric probe sensor. Then the measurement results are displayed online on a specified platform hence that users can observe the results. This implementation uses a pH sensor to measure pH and a conductivity sensor to measure TSS. A conductivity sensor is used as a substitute due to the high cost of TSS sensor. This article analyses also the accuracy of the measurement.

IoT-based real-time online monitoring system for open ware FDM printers

3D Printing enables designers to create parts that were previously used to be too complex to produce economically. FDM amongst all 3D printing methods is the most widely used technology in additive manufacturing which uses thermoplastic material to build robust and complex parts. Now a days, open ware FDM Printers have become handy and being used everywhere. But certain drawbacks of open ware FDM Printers make them reluctant to be used such as material jamming, reliability of printing, insufficient material during printing etc. Therefore, to overcome such problems, IoT-based Real-Time Online Monitoring System is needed to be developed for open ware FDM printers. Such monitoring system should be remotely controllable and should detect material jamming, flow runout etc, so that user can decide whether to pause or stop printing from remote location. Raspberry Pi controller is used for providing web interface for remote control along with G-Code sending software such as Octoprint. Also, Rotary Encoder and load cell is used to detect the material flow and measurement of weight of available material respectively. This paper aims at methodology adopted in development of IoT based Real-Time Online Monitoring System for Open Ware FDM Printers.

Development and Application of Real-Time Online Monitoring System for Long Transportation of Large Power Transformer

A set of transportation process monitoring system for large power transformer transportation is developed, including transportation state intelligent acquisition terminal, monitoring system platform software and mobile app. The effectiveness of the system is verified in the actual transportation monitoring of converter transformer. It solves a series of problems existing in traditional methods, ensures the transportation safety of large electric power equipment and reduces the investment.

Research on Monitoring Method of Impulse Vibration in Large Transformer Transportation

The safety of long-distance transportation of large power transformers has become an important constraint factor for the EHV projects. In view of the problems existing in the Three-dimensional impact recorders and condition monitoring system of the long-distance transportation of large power transformers, this paper analyzes the amplitude frequency characteristics and influencing factors of the impact vibration during the transportation of transformer, adopts the fast Fourier transform to deal with the interference in the vibration signal, designs a monitoring terminal of the impact vibration based on the Internet of things which can accurately measure the vibration impact of the transformer, and develops a remote real-time online monitoring system to monitor the displacement and impact of transformers at anytime and anywhere. The monitoring terminal and monitoring system are applied in the actual transportation of converter transformer in an UHVDC project. Three monitoring terminals are installed in different positions of the transformer to monitor the transformer status and send the monitored information to the monitoring system. The reliability of the terminal and the superiority of the monitoring system are verified.

Transmission Tower Tilt Monitoring System Using Low-Power Wide-Area Network Technology

Since transmission towers are generally located in areas with complex geological environments, such as mountains and rivers, relying only on conduct regular personnel inspections wastes considerable human and material resources. At present, the existing monitoring system has also the problems of data transmission, parameter accuracy and transmission distance. Based on this premise, a novel transmission tower tilt monistoring system was proposed in this paper. This research adopted the latest Low-Power Wide-Area Network (LPWAN) technology. Among tehm, LoRa (Long Range) is a modulation technology that provides a longer communication distance. NB-IoT (Narrow Band-Internet of Things) technology is an emerging technology in the IoT field that supports the cellular data connection of low-power devices in a wide area network. The proposed system through the data transmission of a LoRa multinode network, the tilt parameters of tower were uploaded to an online real-time monitoring system through NB-IoT. Each subnode included MPU6050 tilt sensors and a wireless communication LoRa module. The main node contained an NB-IoT module. It can upload the tilt information to the cloud platform. After uploading the data, administrators can arrange timely targeted maintenance for transmission towers with faults according to the analysis results. The proposed approach covers a wide range, has high service quality, and supports many connections.

An Integrated Optofluidic Platform Enabling Total Phosphorus On-Chip Digestion and Online Real-Time Detection.

This paper presents a total phosphorus online real-time monitoring system integrated with on-chip digestion based on the merits of optofluidic technology. The integrated optofluidic device contains a hollow optical fiber employed for pretreatment and digestion of phosphorus solution samples, a polydimethylsiloxane (PDMS)-based micromixer with convergent–divergent walls designed to enable sufficient mixing and chromogenic reaction, and a couple of optical fiber collimators attached with a Z-shaped flow cell for optical detection. Details of system design and fabrication are introduced in this paper. In the experiment, on-chip digestion of four typical phosphates in aqueous solution including organophosphorus and inorganic phosphorus is investigated under different reaction conditions, such as digestion temperature, concentration of oxidant and pH value, and the optimal reaction parameters are explored under different conditions. Meanwhile, we demonstrate the online real-time monitoring function of the optofluidic device, and the digestion mechanisms of four different phosphates are analyzed and discussed. Compared with the national standard method, we find that the measurement accuracy and sensitivity are acceptable when the concentration of total phosphorus is between 0.005–0.9 mg/L (by weight of P) in aqueous solution, which covers the range defined in the national standard. The traditional digestion time of several hours is greatly reduced to less than 10 s, and the content of total phosphorus can be obtained in a few minutes. The integrated optofluidic device can significantly shorten the test time and reduce the sample amount, and also provides a versatile platform for the real-time detection and analysis of many biochemical samples.

Real-time online monitoring and protection control system for automobile generator based on artificial intelligence

This paper mainly introduces the shortcomings of the traditional automobile generator control system and the improvement of the defects of the traditional automobile generator control system. This article is divided into seven chapters to describe the design background, design ideas, implementation plans and test results of the intelligent detection and protection system for automotive generators. The first chapter mainly introduces the domestic and international research on the intelligent detection and protection system of automobile generators and the design significance of the intelligent detection and protection system of automobile generators. The second chapter briefly describes the overall design ideas and plans of the intelligent detection and protection system for automobile generators, and proposes the general design direction of the overall system. The third chapter puts forward the hardware implementation scheme of the intelligent detection and protection system of automobile generators. The fourth chapter mainly summarizes the design ideas and design methods of the main software of the system. The fifth chapter mainly sets the parameters of the intelligent detection and protection system of the automobile generator, and reduces the error to the allowable range. The sixth chapter is mainly about the experience and summary of this research topic.

Development and application of a goaf-safety monitoring system using multi-sensor information fusion

Rockfall geological disasters and shockwave-induced disasters in underground stopes are normally observed due to overburdened strata movement and surface subsidence of a goaf area, that is normally huge, and of complex shape, in underground mines. Safety monitoring is an effective approach for predicting such disasters before the goafs have been completed. A multi-sensor real-time on-line monitoring and warning system was established using computer technology, stress monitoring technology, and Zigbee wireless network communication technology. The proposed monitoring system consists of four main units: a stress monitoring unit, a data acquisition unit, a wireless communication unit, and a database management unit. A two-phase multi-source spatial-temporal information fusion model was proposed, which uses continuous data series context from sensors to evaluate changing the corresponding stress around the goaf areas. Meanwhile, the proposed method also uses redundant information from different sensors to derive spatial connections, and allow data fusion, therewith. To demonstrate the proposed methodology, the proposed system was applied to Mine A, which has many goafs, and effective data were acquired after two years of continuous monitoring. Furthermore, monitored data were fused using the proposed two-phase spatial-temporal fusion model. A three-dimensional stress contour map of the goafs was drawn, which made the stress changes more intuitive and accurate. More importantly, it can provide short-time warning information about stability and can serve as a scientific basis for predicting geological disasters caused by goafs.

Framework and Application of a Big Data Monitoring System for Mining with a Pillar-Free Self-Forming Roadway

The construction of a self-formed roadway without coal pillars is a new mining technology based on short-arm beam formation through roof cutting. With it, mining, tunneling and retaining roadway construction can be accomplished in a ‘three-in-one’ process that removes the need to dig in advance at the working face and to leave behind coal pillars. In order to realize real-time monitoring and warnings regarding rock pressure during this process, a big data monitoring system was developed based on quasi-distributed fiber Bragg grating (FBG) sensing technology and cloud technology. Firstly, real-time monitoring data on the stress and strain of the underground surrounding rock-support system are obtained by FBG sensor and transmitted to the main computer of the above-ground monitoring and early warning system by using an underground industrial ring network. These data are then sent to a big data remote online real-time monitoring system. Through the deployment of a cloud server, authorized users can observe changes in force and movement in the rock surrounding the supporting system during coal mining and roadway formation from anywhere and at any time. The successful application of the system in the S1201-II working face of the Ning Tiaota Mine shows that this remote real-time monitoring system can enable timely and accurate field data acquisition, feedback real-time production information and achieve good monitoring performance. This study thus provides a scientific basis for ensuring safe mining with the coal pillar-free self-forming roadway method.

Development of Endangered Animals’ Surveillance System

In Tanzania, the real-time endangered animal health monitoring system has been a challenge and there has been speculation that many wild animals are dying because of not being attended in time when they get sick. The matter is even worse to younger elephants. In recent years various bio-sensors for animal health management have been invented and developed and some of them are ready for commercialization, among others antibiotic detection, microfluidics, fluoresce resonance energy transfer (FRET), quantum dots, surface Plasmon resonance technology (SPR) and hybrid technology are widely used. However, there is a need for integrating all the available sensors and create an efficient online monitoring system so that animal health status can be monitored in real-time without delay. To furnish this research and integrate components to create a real-time online monitoring system we used both qualitative and quantitative research design, questionnaires with a closed-ended question were used for data collection and finally SPSS was applied when analyzing data to present findings. The research ended with the development of a prototype which may help gamekeeper to online monitor health parameters and elephants’ location whenever there is an abnormal situation.

Leak detection in low-pressure gas distribution networks by probabilistic methods

The presence of leaks is a prevalent issue for aging gas distribution systems across the globe. These events, if not detected in time, may bring about environmental and health hazards, besides economic losses. Therefore, the development of efficient detection, quantification, and localization methods is crucial to all gas companies worldwide. In this paper, we present a leak monitoring system, called Leak Analytics System (LAS) using a probabilistic approach to determine the location and the rate (severity) of leakage in low-pressure gas distribution networks. This work aims to develop a robust, cost-effective, and real-time online monitoring system for low-pressure gas distribution networks. The leakage events are estimated using pressure and flow data obtained from steady-state modeling of the gas network. The robustness of the methodology is illustrated by analyzing gas networks in the presence of measurement errors, which account for unavoidable sensor noise in flow and pressure data. The feasibility of the proposed method is demonstrated on a small artificial gas network. Moreover, the method is applied to a section of the Singapore gas distribution network for a single as well as multiple leak scenarios. It is also experimentally shown that the severity of the leak and the location for a single leak scenario can be determined within an accuracy of 95% and 80% respectively, even in the presence of strong noise.