On-line Monitoring Technology Research Articles

Online cognitive monitoring technology for people with Parkinson’s disease and REM sleep behavioural disorder

Automated online cognitive assessments are set to revolutionise clinical research and healthcare. However, their applicability for Parkinson’s Disease (PD) and REM Sleep Behavioural Disorder (RBD), a strong PD precursor, is underexplored. Here, we developed an online battery to measure early cognitive changes in PD and RBD. Evaluating 19 candidate tasks showed significant global accuracy deficits in PD (0.65 SD, p = 0.003) and RBD (0.45 SD, p = 0.027), driven by memory, language, attention and executive underperformance, and global reaction time deficits in PD (0.61 SD, p = 0.001). We identified a brief 20-min battery that had sensitivity to deficits across these cognitive domains while being robust to the device used. This battery was more sensitive to early-stage and prodromal deficits than the supervised neuropsychological scales. It also diverged from those scales, capturing additional cognitive factors sensitive to PD and RBD. This technology offers an economical and scalable method for assessing these populations that can complement standard supervised practices.

Research on Online Monitoring Technology and Filtration Process of Inclusions in Aluminum Melt.

Online monitoring and real-time feedback on inclusions in molten metal are essential for metal quality control. However, existing methods for detecting aluminum melt inclusions face challenges, including interference, prolonged processing times, and latency. This paper presents the design and development of an online monitoring system for molten metal inclusions. Initially, the system facilitates real-time adjustment of signal acquisition parameters through a multiplexer. Subsequently, it employs a detection algorithm capable of swiftly extracting pulse peaks, with this task integrated into our proprietary host computer software to ensure timely detection and data visualization. Ultimately, we developed a monitoring device integrated with this online monitoring system, enabling the online monitoring of the aluminum alloy filtration process. Our findings indicate that the system can accurately measure the size and concentration of inclusions during the filtration process in real time, offering enhanced detection speed and stability compared to the industrial LiMCA CM (liquid metal cleanliness analyzer continuous monitoring) standard. Furthermore, our evaluation of the filtration process demonstrates that the effectiveness of filtration significantly improves with the increase in inclusion sizes, and the synergistic effect of combining CFF (ceramic foam filter) and MCF (metallics cartridge filter) filtration methods exceeds the performance of the CFF method alone. This system thus provides valuable technical support for optimizing filtration processes and controlling inclusion quality.

An Improved Analytical Thermal Rating Method for Cable Joints

To improve the utilization rate of cable lines while retaining sufficient security, the accurate thermal assessment of cable is significant for cable operation condition evaluation. The thermal rating for a cable joint, which is regarded as a hot spot of cable lines, is not covered by the scope of IEC 60287. While the existing publications for cable joint thermal evaluation also have some limitations. In this paper, the quasi-three-dimensional thermal model of the cable joint was established and the iterative solution method for the model is presented. Based on the model, an improved thermal rating method for the cable joint was proposed, which was implemented with monitored surface temperature and load data. The improved method was verified by the finite element method and the results showed an error of less than 5%. The superiority of the improved method was conducted by the comparison between the previously published method and the improved method. The improved method showed a better accuracy than the previously published method. The proposed method in this paper can be complementary to the IEC method, and is easy to use for the operating evaluation of cable joints in the field with the on-line condition monitoring technology.

Residual subsidence time series model in mountain area caused by underground mining based on GNSS online monitoring

The residual subsidence caused by underground mining in mountain area has a long subsidence duration time and great potential harm, which seriously threatens the safety of people's production and life in the mining area. Therefore, it is necessary to use appropriate monitoring methods and mathematical models to effectively monitor and predict the residual subsidence caused by underground mining. Compared with traditional level survey and InSAR (Interferometric Synthetic Aperture Radar) technology, GNSS (Global Navigation Satellite System) online monitoring technology has the advantages of long-term monitoring, high precision and more flexible monitoring methods. The empirical equation method of residual subsidence in mining subsidence is effectively combined with the rock creep equation, which can not only describe the residual subsidence process from the mechanism, but also predict the residual subsidence. Therefore, based on GNSS online monitoring technology, combined with the mining subsidence model of mountain area and adding the correlation coefficient of the compaction degree of caving broken rock and the Kelvin model of rock mechanics, this paper constructs the residual subsidence time series model of arbitrary point on the ground in mountain area. Through the example, the predicted results of the model in the inversion parameter phase and the dynamic prediction phase are compared with the measured data sequence. The results show that the model can carry out effective numerical calculation according to the GNSS monitoring data of any point on the ground, and the model prediction effect is good, which provides a new method for the prediction of residual subsidence in mountain mining.

Identification of corrosion factors in blast furnace gas pipe network with corrosion big data online monitoring technology

To mitigate the accelerated corrosion of blast furnace gas pipelines induced by severe environmental conditions, this study has established an extensive high-throughput sensor system in the field. It leverages corrosion big data technology to investigate the corrosion factors affecting industrial gas pipelines and to precisely analyze the influence of related variables. The results indicated that temperature reduction is the driving factor that causes increased pipeline corrosion. On one hand, temperature fluctuations impact the evaporation and condensation of moisture in the tube. On the other hand, temperature fluctuations, in conjunction with corrosive gases, exhibit significant coupling effects, resulting in more severe corrosion. In addition, critical points for relative humidity and temperature are evident. When humidity exceeds 50%, corrosion in the pipe begins to increase, reaching its peak at 70%. The increase in temperature has a slowing effect on pipeline corrosion, reaching a peak value at 40°C. The response of corrosion rate to the concentration of corrosive gases follows a linear pattern. Based on these observations, we propose an effective corrosion control scheme.

Analysis of Water Pollution in The Musi River Due to Community and Industrial Activities Using Onlimo

The Musi River is a natural resource which is one of the main trade routes and the largest air supplier for the people of South Sumatra. However, the condition of the Mus River has undergone changes due to dense settlements and industry. Water quality is an important factor in the sustainability of an ecosystem. Ecosystem damage can start from declining air quality which results in industrial waste that pollutes the Musi River. Water quality measurement parameters include measurements of oxygen, TSS, COD, BOD. Observation station sampling was carried out using Onlimo telemetry technology. Onlimo is a remote, online and real-time air quality monitoring technology developed by BPPT. Sampling was carried out during the transition season on the Musi River which was divided into station 1 located in the Musi River (PDAM Tirta Randik area, Balui Air Unit, Sanga Desa District). On May 10, 2023 there was a pollution index of 7.32 with moderate contamination with the critical parameters Chemical Oxygen Demand (COD) and Biological Oxygen Demand (BOD). There was an increase in the Pollution index of 7.51 due to an increase in Nitrate from 16 May 2023 to 17 May 2023 due to input from anthropogenic waste caused by differences in sampling time, besides that season and rainfall are reported to play an important role in dissolving a number of components in the waters. For this reason, to prevent and improve the function of the Musi River, namely the government must act decisively on violations committed by factories or companies or the public who dispose of waste carelessly

Simulation and experimental research on vibration response of microcracked compressor blades under variable working conditions

Compressor blades play a crucial role in aero-engines, experiencing complex alternating loads under variable working conditions (VWC). Resonance is inevitable under these conditions, leading to the development of blade crack faults. To understand and analyze this phenomenon, a finite element (FE) model of a microcracked blade was created using ANSYS. The model's accuracy was verified through a hammering experiment. Additionally, a resonance fatigue test was used to accurately obtain dynamic characteristics for prefabricated breathing cracks. The experiment demonstrated that cracked blades exhibit smaller responses in the time domain compared to intact blades, while showing super-harmonics in the frequency domain, thus validating the effectiveness of numerical simulation. The effects of VWC on the nonlinear vibration characteristics (VC) of the blade with a breathing microcrack were investigated. These VWC included variable speed, the amplitude of the exciting force (F0), depth of the microcrack (D), and length of the microcrack (L). The results revealed significant increases in the frequency domain response amplitude of the blade at super-harmonics with the increase of F0, D, and L at variable speeds. Furthermore, the breathing behavior of microcracked blades diminished with increasing rotating speed (N), D, and L. The observed decrease in frequency and the emergence of super-harmonic serves as indicators of the presence and severity of blade cracks. These findings are of great significance for the development of online monitoring technology for blade faults.

Modeling for on-line monitoring of carbon burnout coefficient in boiler under partial load

Combustion stability of boiler deteriorates under low load, making carbon burnout coefficient decrease, further reducing boiler thermal efficiency. The online monitoring methods of carbon burnout coefficient and boiler thermal efficiency can track energy efficiency levels of boiler in real-time under low loads. It is of great practical significance to optimize and adjust combustion conditions of boilers and upgrade boiler real-time energy efficiency. Nevertheless, extremely difficult challenge for online monitoring technology of carbon burnout coefficient seriously restricts the online monitoring of boiler thermal efficiency.In this background, an innovative theoretical model between excess air coefficient and carbon burnout coefficient is derived according to incomplete combustion equation inside furnace. Calculation method of excess air coefficient is proposed with a brand new perspective on energy balance of economizer. Subsequently, on-line monitoring model of carbon burnout coefficient and boiler thermal efficiency is constructed and verified.The online monitoring results of a 600 MW unit indicate, lower carbon burnout coefficient magnifies the degree of virtual height of calculation results and calculation error from traditional methods of national standard for calculating excess air coefficient. This operating mode results in a significant shortage of actual air flow into boiler under partial load.Carbon burnout coefficient, showing an upward trend with unit load increasing, is as high as 0.99 with unit load of 489 MW. As unit load decreases to 161 MW, carbon burnout coefficient decreases to 0.80. Additionally, combustion conditions fluctuation is greatly influenced by changing in coal quality. Under partial load, volatility in carbon burnout coefficient increases with electrical load below 300 MW. Combustion stability and combustion efficiency of boiler under low load significantly decrease. The variation in exhaust flue gas heat loss of boiler with unit load changes is relatively small due to opposite effect by exhaust gas temperature and excess air coefficient. Actually, changing trends and fluctuation degree of boiler thermal efficiency are mainly influenced by carbon burnout coefficient with a variation in load. Overall, boiler thermal efficiency, affected by heat loss of incomplete solid on combustion, fluctuates greatly at low loads. The implementation of online monitoring for carbon burnout coefficient provides a quantitative basis for improving boiler energy efficiency under low load conditions.

Research on online monitoring and anti-dance technology of transmission line dance based on wide-area information transmission

Abstract This paper diagnoses the transmission line dancing situation based on the wide-area traveling wave information transmission and dancing mechanism. The characteristics of the wide-area initial traveling wave propagation are analyzed, and the traveling wave information of transmission line dancing is analyzed using wavelet transform. Measure the voltage traveling wave energy distribution for online monitoring and diagnosis of transmission lines. To study the dancing amplitude of transmission lines, a finite element analysis model is created. The detuned pendulum anti-dancing device is designed, the detuned pendulum dynamics equation is constructed, and the critical wind speed leading to transmission line dancing is investigated by the theoretical equation method and the stability theory method. Through the empirical analysis method, the transmission line dance monitoring and the anti-dance effect are analyzed. The experiments show that when the transmission line dances at a slower speed, the online monitoring method based on wide-area information monitors the motion of the target spacer bar between two neighboring frames between [1,3], and the processing speed is 138.2 frames per second faster than the other techniques, which is successful in tracking the dancing target of the transmission line. In the anti-dance test, before the anti-dancer was added, the transmission line amplitude reached 12,12m/s from the beginning at a wind speed of 18m/s and 14m/s to provoke dance. After the installation of the anti-dancer, the amplitude is maintained between [0,1] in most cases, and the anti-dancer has a good anti-dance effect.

Automated Monitoring of the Uniform Demagnetization Faults in Permanent-Magnet Synchronous Motors: Practical Methods and Challenges

Due to its high power, high efficiency, low pollution, and compact size, permanent-magnet synchronous motors (PMSMs) have been widely used in a variety of fields, including electric vehicles, aerospace, wind turbines, and marine devices, which are used in renewable, sustainable, and environmentally friendly energy resources. However, in these practical scenarios, the motor operating conditions are complex and variable. Under high-temperature and high-current conditions, PMSMs may experience demagnetization failures, not only leading to performance degradation but also inducing unexpected failures of the motors. To reduce the risk of unexpected losses caused by demagnetization faults and improve the safety and reliability of motor systems, it is necessary to apply automated monitoring of the magnet flux of the motor’s permanent magnets and achieve real-time diagnosis of early demagnetization faults, ensuring the safe operation of the motor. This review article tries to summarize the current detection methods of the automated monitoring of demagnetization faults in PMSMs. The main online monitoring technologies from both practical and academic perspectives are summarized and their benefits and challenges are reviewed. Finally, the research trends and suggestions for future improvements are provided. This review article not only sheds light on the origins of the automated monitoring of demagnetization faults but also helps to design highly effective and sustainable permanent-magnet synchronous motors.

Research on Vibration Analysis and Online Monitoring Technology of Transmission Tower Near Railway

Research on Vibration Analysis and Online Monitoring Technology of Transmission Tower Near Railway

Research on online monitoring technology for transmission tower bolt looseness

Minor damages such as tower bolt looseness are difficult to detect through manual inspections. Operational modal analysis plays an important role in the online monitoring of transmission tower structure safety. However, the traditional analysis methods select feature parameters manually, and the deviation generated will directly affect the estimation accuracy of structural modal parameters. This article proposes a method for diagnosing tower bolt looseness without human intervention. This method can reduce the influence of background noise greatly through data cleaning and data fusion. Besides, the intelligent feature recognition of vibration acceleration time-domain signals based on an improved 1DCNN algorithm can improve the monitoring accuracy and speed significantly. The effectiveness of the method has been validated by conducting dynamic response tests on a 110KV transmission tower under different bolt loosening conditions. In the end, an online monitoring technology for transmission towers bolt looseness has been developed and successfully applied to the Guangdong power grid. The results show that this method has high identification accuracy and provides a new approach for online monitoring of tower bolt looseness.

Fault Diagnosis of Medium Voltage Circuit Breakers Based on Vibration Signal Envelope Analysis.

In modern power systems or new energy power stations, the medium voltage circuit breakers (MVCBs) are becoming more crucial and the operation reliability of the MVCBs could be greatly improved by online monitoring technology. The purpose of this research is to put forward a fault diagnosis approach based on vibration signal envelope analysis, including offline fault feature training and online fault diagnosis. During offline fault feature training, the envelope of the vibration signal is extracted from the historic operation data of the MVCB, and then the typical fault feature vector M is built by using the wavelet packet-energy spectrum. In the online fault diagnosis process, the fault feature vector T is built based on the extracted envelope of the real-time vibration signal, and the MVCB states are assessed by using the distance between the feature vectors T and M. The proposed method only needs to handle the envelope of the vibration signal, which dramatically reduces the signal bandwidth, and then the cost of the processing hardware and software could be cut down.

Smart asset management system for power transformers coupled with online and offline monitoring technologies

Predictive maintenance strategies have gained popularity in recent years due to the advantages they provide over traditional maintenance strategies. Online monitoring technologies are critical for implementing predictive maintenance strategies. However, in some cases, the information generated by online systems may not be accurate and may need to be verified with offline monitoring technologies. In this study, a fault-sensitive matrix-based smart asset management system that is compatible with both online and offline technologies has been developed for power transformers. The developed system has the ability to assess multi-input parameters simultaneously and holistically. Because of the system's matrix structure, having a large number of input parameters or expanding them later is not an issue. Furthermore, the algorithms that will evaluate the input parameters are independent and distinct from one another. Because of its compatibility with the data acquisition card and its design options for the user interface, LabVIEW has been chosen for the system's development. The functionality of the system has been tested by deliberately generating faults in a test cell. While the high-resolution sensor data obtained and the calculated results are displayed on the interface, the failure probabilities are evaluated and displayed in a separate window. Intentionally generated faults have been diagnosed with high accuracy after going through the online monitoring and offline verification processes.

Real-time online monitoring technology for sweeping frequency ultrasound (SFU) assisted extraction of amur grape (Vitis amurensis) seed oil

Sweeping frequency ultrasound (SFU) was used to assist extraction of amur grape (Vitis amurensis) seed (AGS) oil. Extraction conditions and physicochemical properties were optimized and analyzed under different extraction methods. Meanwhile, frequency and time domains were online monitored during SFU assisted extraction of AGS oil. PVDF piezoelectric sensor was used in time domain, and the hydrophone in frequency domain, so as to obtain the time–voltage waveform, signal power, spectrum distribution and other visual models. Physical models of the spatial peak acoustic intensity, charge quantity and work done by electric field force under different ultrasonic conditions were derived. The mathematical model between the work done by electric field force and the spatial peak acoustic intensity under the working state of PVDF piezoelectric sensor was constructed. Results show that the content of AGS oil by SFU assisted extraction was higher than that by organic extraction. Furthermore, the optimal single-frequency was 40 kHz and dual-frequency was 28/33 kHz, and SFU extraction time of 30 min was suitable with higher oil yield of 16.70 % and 16.94 %, respectively. In addition, the selection and combination of SFU also affected the oil oxidation degree. The peak voltage, spatial peak acoustic intensity, signal power and work of electric field force at 28/33 kHz were all higher than those at 40 kHz.

Evolution and interpretation of LIBS signals based on laser selective layered paint removal from aircraft composite tail

The reliability and controllability of laser selective layered paint removal depend on effective online monitoring technology. In the process of laser cleaning the surface paint layer of the aircraft composite tail, this paper studied the evolution and interpretation of laser induced breakdown spectroscopy (LIBS) signals. The laser power is adjusted to achieve different depths of the laser cleaned composite surface paint layer to compare the Pearson linear correlation between the LIBS online spectrum and the reference spectrum and decode the characteristic peak signal of the LIBS spectrum. The linear correlation of the LIBS spectra and the evolution of the characteristic peaks of the LIBS spectra are mutually verified to establish the intrinsic correlation between the controllability of layered paint removal and the variation of the LIBS spectra, which demonstrates the feasibility of the LIBS technology for online monitoring and feedback of laser paint removal. The results show that the Pearson correlation coefficient r was 0.87–0.89 for the laser cleaning depth range of 44.79–51.50 μm, the layered boundary of laser cleaning the topcoat without damaging the primer is reached, it is proved that the Pearson correlation coefficient r can determine the laser paint removal process. This research compared the different LIBS spectra with cleaning depths at 44.79 and 51.50 μm. It was found that the characteristic peak of strontium element Sr I at wavelength 460.66 nm could characterize the delamination boundary of laser paint removal from aircraft composite tail.

Analysis of quantitative management of online intelligent monitoring of tailing ponds based on the perspective of safety prevention and control

Abstract China’s tailing pond online monitoring technology started late, and the tailing pond is located in a harsh working environment, for the limitations of traditional manual monitoring of tailing pond, combined with the actual situation of Zhenhua Mining tailing pond. This paper constructs a risk monitoring index system and online monitoring early warning model based on (Language Model - Back Propagation, LM-BP) neural network to quantitatively assess tailing pond safety risks and analyze and judge safety risk trends. We extracted common indicators of regional tailing ponds, combined with meteorological data to establish a regional safety risk assessment model, integrated vulnerability of disaster-bearing bodies, environmental sensitivity and other influencing factors, realized regional risk coupling analysis, and dynamically built a risk cloud map. Based on the perspective of safety risk prevention and control, the integrity and accuracy of monitoring data are analyzed, the causes of early warning are inverted, alarm disposal mechanisms are established, and closed-loop management of early warning is realized to provide scientific auxiliary decision-making support for tailing pond safety supervisors.

Sewage system diagnosis based on online monitoring technology

ABSTRACT External water (such as rainwater, mountain water and groundwater) will decrease the inflow contaminant concentration in urban sewage plants, and pose challenges in improving the wastewater treatment quality and efficiency. Therefore, removing the external water is vital for this target. A sewage plant in Zhuhai, China, was considered as an example. By performing online flow monitoring, water quality testing, on-site survey and data analysis, the rainfall-derived inflow and infiltration of the sewage system were quantitatively analysed through the pollutant balance method. By proposing key emphases of severe problems, the presented findings will aid in sewage system maintenance and pipeline network renovation.

Research of On-Line Monitoring Technology Based on Laser Triangulation for Surface Morphology of Extreme High-Speed Laser Cladding Coating

This work aims to develop a novel method for on-line monitoring of coating quality during the Extreme High-speed Laser Cladding (EHLA) process. JG-11 coating was prepared by EHLA, and microstructure, microhardness, corrosion performance, and scratch resistance were investigated. To analyze the influences of fluctuations in processing parameters on coating quality, a single-factor experiment scheme was designed and an on-line monitoring system based on laser triangulation was built. Furthermore, a new forming method for the surface profile of EHLA coating was proposed, and a new comprehensive evaluation index of surface morphology was accordingly designed. Benefitting from the extremely high cooling rate, EHLA JG-11 coating had fine grains, high hardness, and better corrosion resistance and scratch resistance than those of Electroplating Hard Chromium (EHC). The results revealed that the surface morphologies presented different characteristics due to the fluctuations of process parameters, such as high surface flatness, deep pits, small peaks, poor directionality, etc. The comprehensive evaluation index composed of Sa, Ssk, and Str could effectively characterize the surface morphology of EHLA coating, which proved that the monitoring system and evaluation method could realize on-line monitoring of the process parameters during the EHLA process.

Design of a Shield Tail Clearance Measuring Sensor for a Shield Machine

To improve the measurement accuracy and judge the distance between shield segments and shield tail accurately, the online monitoring technology of shield tail clearance was studied. Firstly, a sensor that can be used for shield tail clearance measurement was designed, and its key parts were selected. Secondly, the characteristics of the key parts were simulated to verify their feasibility. Finally, the monitoring principle was analyzed