Icing Monitoring System Research Articles

Experimental study on ice monitoring method for 10 kV transmission line with tangent tower in alpine landform

AbstractIce monitoring methods were applied for 110 kV and above transmission lines with tangent towers. However, the change in the vertical span is not considered, and a significant difference lies in the tower‐conductor structure of 10 kV transmission lines. For this reason, a proposal is made about the ice monitoring method for the 10 kV transmission line with tangent tower in alpine landform, which includes the ice monitoring system based on pressure measurement and corresponding equivalent ice thickness calculating methods. Different methods calculate the vertical span under different height difference coefficients. A finite element simulation model and a simulated ice load experiment system are established based on real conductors and insulators. Experiments and simulations under four simulated terrains are conducted within 2.5–20 mm ice thickness range. The comparison is made between this method and the method without considering the change in vertical span. The results show that the two methods are consistent and the relative errors are lower than ±4% in simulation and ±10% in experiment when the height difference coefficient is 0. When it is not 0, the relative errors of this method fall between +0.38% and +6.78% in simulation and −6.40% to +6.60% in experiment, while the relative errors of the method without considering the change in vertical span ranges between −11.13% and −20.23% in simulation and −11.65% to −23.20% in experiment.

Function design and realization of transmission line icing monitoring and early warning system combined with micro-meteorology and micro-topography in Guizhou

The icing of transmission lines is one of the main causes of transmission line accidents and power outages, which poses a great threat to the safe and stable operation of transmission lines. Therefore, it is of great significance to establish a set of icing monitoring and early warning system to predict possible icing situations in advance, take corresponding measures, and ensure the normal operation of transmission lines. According to the characteristics of micro-meteorology and micro-topography in Guizhou, this paper designs and implements a set of transmission line icing monitoring and early warning system based on micro-meteorology and micro-topography. Through the experimental analysis of the system, it is proved that the system can effectively monitor and warn the icing of the transmission line, and improve the safety and stability of the transmission line.

Ice-Covered Warning System and Terminal Application Based on Beidou Technology

Disaster prevention and mitigation are one of the most prominent industrial applications of Beidou. Through the Beidou system’s short message and location reporting functions, it can realize disaster early warning, disaster rescue command and dispatch, and rapid emergency communication, which can greatly improve the speed of disaster emergency rescue response and decision-making ability. Based on the existing ice monitoring system of power grids and terminal in communication, positioning, and time synchronization problems such as the status quo analysis, based on the use of Beidou communication technology to modify ice monitoring system and terminals, and through system alignment, information coding and check, based on Beidou communication technology is verified in ice monitoring, especially the important role of disaster prevention and mitigation, it has important national strategic significance and multiple meanings such as industry 2025, new infrastructure and digital power grid.

Analysis of the Variability and Influencing Factors of Ice Thickness during the Ablation Period in Qinghai Lake Using the GPR Ice Monitoring System

As a reliable indicator of regional climate change, the growth and decline of lake ice thickness affect the regional intra–annual heat and energy balance. In this study, a ground-penetrating radar (GPR) ice monitoring system, located approximately 1.7 km west of Bird Island in Qinghai Lake, in the territory of Qinghai Province and located in northwest China, was designed to carry out continuous fixed–point observations of local ice thickness and meteorological elements from 7 to 24 March 2021. The characteristics of continuous daily changes in ice thickness during the ablation period of Qinghai Lake and their relationship with meteorological elements were analyzed. The results showed that the average daily ice thickness of Qinghai Lake increased and then decreased during the observation period, with an average ice thickness of 42.83 cm, an average daily ice thickness range of 39.35~46.15 cm, and a growth rate of 0.54 cm/day during 8–13 March 2021, with an ice melting rate of −0.61 cm/day during 14–24 March 2021. The daily ice thickness variations were divided into two phases, which were relatively stable before dawn and followed a decreasing, increasing, and then decreasing trend during 8–13 March 2021 and a decreasing, increasing (for several hours), and then decreasing trend during 14–24 March 2021. There was a significant positive correlation (R = 0.745, p < 0.01) between near-surface air temperature and ice surface temperature during the observation period, but a significant negative correlation (R = −0.93, p < 0.05) between the average daily ice thickness and cumulative temperature of the ice surface. Temperature was the dominant factor affecting lake ice thickness, as compared to near-surface air humidity, wind speed, and illuminance. However, a sudden increase in wind speed have also played an important role at certain periods. A large number of cracks appeared on the ice surface on 26 March 2021, which, combined with the forces of wind speed, wind direction, and temperature, contributed to the rapid melt of the lake ice. This study filled the gap in situ measurement data on the continuous ice thickness variability during the ablation period in Qinghai Lake. It provided scientific support for the further study of lake ice on the Qinghai–Tibet Plateau (QTP).

River ice monitoring of the Danube and Tisza rivers using Sentinel-1 radar data

Due to extreme weather, occasionally Hungary's main rivers and lakes grow an ice cover causing severe damage to infrastructure and increased flood hazard. During cold periods in 2017 and 2022, a dangerous layer of ice developed on the main rivers in the country. Since river ice is rare in this region, no permanent ice monitoring system is in operation. Due to their all weather capabilities, active remote sensing instruments provide a good opportunity to monitor ice coverage. ESA's Sentinel-1 radar satellites acquire data with a relatively high spatial and temporal resolution. A method was developed to provide ice coverage information at a regular interval; depending on the satellite revisit, at least once every 5 days, but often also on a daily basis. In 2017, maps were created for sections along the Danube and in 2022 for another section of the Tisza river. The ice coverage was calculated with a spatial resolution of 10 metre and visualised with a spatial density of 100 metre along the rivers. The mapping procedure provides visual information to give a fast overview of the spatial extent of ice coverage and quantitative , tabular information for operational activities to mitigate the damage due to ice packs and ice jams.

Distributed Transmission Line Ice-Coating Recognition System Based on BOTDR Temperature Monitoring

An optical fiber composite overhead ground wire (OPGW) distributed ice-coating monitoring scheme based on Brillouin optical time domain reflectometer (BOTDR) temperature measurement is proposed and demonstrated. The thermodynamic factors affecting the temperature of the OPGW cable are analyzed, and the temperature variation characteristics of the icing and non-icing sections of the OPGW cable with different icing thicknesses are analyzed via finite-element analysis. The results of an OPGW icing experiment indicate that when the ambient temperature changes, there is an obvious hysteresis characteristic between the temperature changes of the icing and non-icing sections of the OPGW cable, which is related to the thickness of the ice. Thus, we propose a distributed OPGW cable icing monitoring system based on BOTDR temperature monitoring.

Research on A New On-line Monitoring System of Transmission Line Icing Based on RF433 Technology

In view of the disadvantages of the current transmission line icing online monitoring terminal data transmission through wire and large power consumption, This paper uses RF433?WIFI and low-power design technology, realize the low-power wireless transmission function of each sensor data, and through the communication protocol between the front-end wireless sensor and the main controller, achieve the purpose of improving the efficiency of the sensor. Finally, the terminal efficiency designed in this paper is verified by actual test. After 72 hours of test, the packet loss rate of each sensor is 0%, which indicates that the system can run stably. At the same time, the maximum power consumption of the main control board in one day is 0.11W, which is far lower than the power consumption of the online monitoring terminal of the cable icing over 1W. In this paper, the design of low-power wireless icing monitoring system for transmission lines can correctly guide the work of anti-icing and anti-icing, which is of great significance for the safe operation of transmission lines.

Icing-EdgeNet: A Pruning Lightweight Edge Intelligent Method of Discriminative Driving Channel for Ice Thickness of Transmission Lines

The icing monitoring of transmission lines is of great significance to prevent freezing disasters of transmission lines and ensure the security and stability of power system. Measurement methods based on image recognition is gradually applied for icing monitoring but fails to distinguish the icing thickness under the extreme meteorological conditions. Therefore, this article built an ice monitoring system based on edge intelligence to achieve the ice thickness identification at the icing monitoring terminal and proposed a lightweight vision identification method based on discriminative-driven channel pruning for icing monitoring terminals with limited computing resources. In this method, the lightweight convolutional neural network (CNN) MobileNetV3 is utilized for feature extraction, and the multiscale target detection network SSD is used to extract the high-dimensional feature information for ice monitoring. Then, the channel pruning driven by discrimination is used to further compress model, so as to obtain a lightweight identification method suitable for ice monitoring terminals with limited resources. The effectiveness and superiority of the proposed method are verified in comparison with other CNN-based target detection methods and traditional ice monitoring methods. The experimental results showed that the proposed method has 74.5% recognition accuracy for the ice images collected under extreme meteorological conditions. Moreover, the model size is only 11 MB, which can be deployed in ice thickness monitoring terminals with limited computing resources.

LAKE ICE DETECTION FROM SENTINEL-1 SAR WITH DEEP LEARNING

Abstract. Lake ice, as part of the Essential Climate Variable (ECV) lakes, is an important indicator to monitor climate change and global warming. The spatio-temporal extent of lake ice cover, along with the timings of key phenological events such as freeze-up and break-up, provide important cues about the local and global climate. We present a lake ice monitoring system based on the automatic analysis of Sentinel-1 Synthetic Aperture Radar (SAR) data with a deep neural network. In previous studies that used optical satellite imagery for lake ice monitoring, frequent cloud cover was a main limiting factor, which we overcome thanks to the ability of microwave sensors to penetrate clouds and observe the lakes regardless of the weather and illumination conditions. We cast ice detection as a two class (frozen, non-frozen) semantic segmentation problem and solve it using a state-of-the-art deep convolutional network (CNN).We report results on two winters (2016–17 and 2017–18) and three alpine lakes in Switzerland. The proposed model reaches mean Intersection-over-Union (mIoU) scores >90% on average, and >84% even for the most difficult lake. Additionally, we perform cross-validation tests and show that our algorithm generalises well across unseen lakes and winters.

A Classification Method for Transmission Line Icing Process Curve Based on Hierarchical K-Means Clustering

Icing forecasting for transmission lines is of great significance for anti-icing strategies in power grids, but existing prediction models have some disadvantages such as application limitations, weak generalization, and lack of global prediction ability. To overcome these shortcomings, this paper suggests a new conception about a segmental icing prediction model for transmission lines in which the classification of icing process plays a crucial role. In order to obtain the classification, a hierarchical K-means clustering method is utilized and 11 characteristic parameters are proposed. Based on this method, 97 icing processes derived from the Icing Monitoring System in China Southern Power Grid are clustered into six categories according to their curve shape and the abstracted icing evolution curves are drawn based on the clustering centroid. Results show that the processes of ice events are probably different and the icing process can be considered as a combination of several segments and nodes, which reinforce the suggested conception of the segmental icing prediction model. Based on monitoring data and clustering, the obtained types of icing evolution are more comprehensive and specific, and the work lays the foundation for the model construction and contributes to other fields.

Phase Discrimination in Marine Icing Using a Coplanar Capacitive Array

This paper describes the development of an array of coplanar capacitive sensors applied to marine icing. Current atmospheric icing monitoring systems consider single phase conditions in their operation. Marine icing conditions present a unique environment where the liquid water phase effects cannot be neglected and require a novel approach. We have conducted an initial proof of concept and propose a new icing monitoring system which can distinguish between the individual phases. A numerical model confirmed our initial hypothesis of the system’s ability to discriminate the multiphase domains based on the array of geometrically dissimilar capacitive sensors. In addition, we also developed a novel experimental technique based on a comparative study under constant conditions to eliminate the need for an independent ice accretion monitoring system normally required in sensor development. The new approach promises a better characteristic in marine icing monitoring systems or in similar applications where multiphase dielectric is present.

The Research on the Ice Thickness Detection System Based On Capacitance Sensor

A transmission line remote monitoring system combined with wireless sensor technology was designed, through the single-chip computer control to complete the system data from the collection to send all aspects of data processing work. The icing monitoring system uses capacitive thickness detection sensors to collect data from multiple capacitance values and send the collected data to the control center processor through the serial port. The processor then processes the data and stores it on the SD card. in. Through the single-chip computer control to complete the system data from collection to send all aspects of data processing. The processor finishes the data transmission and connects with the GPRS communication module through the RS232 serial port. The automatic detection of ice thickness using the difference in resistance characteristics of air and ice, it is a new type of object surface ice coating thickness detection method. The utility model can be applied to real-time continuous automatic monitoring engineering application fields of high-pressure transmission lines and fixed towers, buildings or various equipment surfaces, suspension brackets, forest branches, and the like.

Fabrication of anisotropic PTFE superhydrophobic surfaces using laser microprocessing and their self-cleaning and anti-icing behavior

Due to excellent stability and intrinsic low surface energy, polytetrafluoroethylene(PTFE) is widely utilized to fabricate biomimetic superhydrophobic surfaces. We proposed a facile and rapid method to obtain outstanding superhydrophobic surfaces by CO2 laser microprocessing PTFE plate. Scanning electron microscope(SEM) and contact angle measuring instrument were employed to characterize the structure and wettability. The effects of different micro channels spacing, different processing times and different processing power on wettability and morphology were studied. The self-cleaning and anti-icing properties of the prepared PTFE superhydrophobic surface were investigated. It was demonstrated that the maximum static contact angle was up to 168.36°. The degree of anisotropy could be controlled by adjusting the micro channels spacing. The as-prepared PTFE superhydrophobic surfaces exhibited self-cleaning properties, and water droplets were easy to take away dusts attached to the surfaces. Especially, it was found using the self-made icing monitoring system that as-prepared PTFE superhydrophobic surface showed an outstanding dynamic anti-icing performance even if the surface temperature was as low as −25°C and surrounded by ice and frost. The present study therefore suggests that CO2 laser microprocessing could be applied to large-scale preparation of superhydrophobic surface for practical applications in different fields of self-cleaning, anti-icing, microfluidic devices, lab-on-chips system, directional water harvesting, drag reduction and other fields.

SVM-based prediction method for icing process of overhead power lines

The icing of overhead transmission lines is a serious problem for the safety of power grid. A method based on support vector machine (SVM) is presented here to predict the icing load of power transmission line, which utilises the history meteorology data from the icing monitoring system, and takes account of time effects of meteorology factors. According to the results of simulation, the prediction of icing load on the power lines in Northeast of Yunnan province is close to the actual value and the ability of generalisation is better than the model based on BPNN.

New Method of Overhead Line Icing Online Monitoring

Present icing monitoring system mainly depends on detecting the meteorological parameters and dynamic characteristics of the structure of the overhead icing line. However, all these systems need additional equipments for data collection. This paper provides a new method based on voltage and current of both ends of the line and discriminates the icing region and its severity via the change of active power and reactive power. It requires the voltage and current serving as signal source which is provided by the data collecting device on the both ends of lines. In this way it can accomplish the Monitoring task of icing transmission.

Application of Fiber Bragg Grating Device in Icing Monitoring System of Transmission Lines

Ice accretion has been a huge threat for the stable operation of transmission line. Icing monitoring devices used presently are active sensors with low working stability. Signals are transmitted in the electrical form, which are easily affected by the electromagnetic interference. In this paper, an online icing monitoring device of transmission line based on fiber bragg grating (FBG) sensor is designed, and is operated as a pilot unit on the 44# tower of 110kV Zhenzou line. Experimental results show that the online icing monitoring device operates stably, and the designed fiber bragg grating sensor has high linearity, good sensitivity and high accuracy.

A New Wire Icing Automatic Monitoring System Based on Wireless Communication Platform

In view of the wire icing field monitoring in the process of the field data acquisition is difficult in the southwest mountainous area in Guizhou, the first generation of the present situation of the system operation reliability is not high, a new generation of automatic field wire icing monitoring system has been developed. The new generation of the system adopts ARM/Linux platform, Ice data can be sent via wireless transmission. With the digital acquisition mode of the System sensor, new system can monitor wire icing state stably, continuously. Data collected by GPS can be sent to the remote server of meteorological department which can provide data support for wire icing forecast. From November 2010 to March 2013, the new generation of wire icing monitoring system was carried out three times field test in Meihuashan,Weining field site test points, Kaiyang weather service stations and Wanshan SAR weather service stations in Guizhou. Results show that the system meets requirement of field site test and have further promotion value in the wire icing test requirements area.

New Methodology of On-Line Monitoring for High Voltage Overhead Transmission Line Icing

In recent years,transmission lines icing leads to failure and accidents,such as large area ice flashover, fittings damaged, line dancing, pole (tower) failure, lines breakage even large-scale power outage, causing serious threat to grid. Nowadays, icing monitoring system mainly relies on detecting the meteorological parameters and the changes of dynamic characteristics for early warning, but the methodologies need additional equipment for data collection. In order to ensure the security and reliability of the grid, a safe, effective and economical methodology of monitoring transmission lines icing has great significance. The project proposed a Transmission Line Icing monitoring principle and algorithm, the method based only on the voltage and current from both ends of transmission lines can be generated dynamically monitoring criterion line icing. According to the criterion maximum, line icing center area, extent and severity can be recognized. The criterion of the method is used as a mathematical scanner, swept from one end of the line to the other end, comprehensive judgments are made on the basis of comprehensive criteria for integrated maximum value, thus the method has a high diagnostic accuracy and reliability. The methodology proposed in this paper is different from the current monitoring methodology; additional hardware devices are not required, and the methodology is simple and practical, has strong operability and enormous economic benefits, adapting to the requirements of the development of the smart grid.

A New Monitoring and Early-Warning System on Large Range Road Using IPv6 Network

According to the actual situation of large range road disasters in seasonal frozen area, the road safety can reflect by the slope stability, the subgrade stability, the bridge safety and the ice(snow) on the road.The objective of this paper is to present a new monitoring and early-warning system, which can be used on the large range road in seasonal frozen area. The system consists of four parts, which are slope monitoring system, subgrade monitoring system, bridge monitoring system and ice(snow) monitoring system. In this system, the small world theory is used to build an IPv6 p2p network structure and semi-structured data is used to store any type of early-warning data. In addition, a bridge in western Changchun City in Jilin Province was selected as the case study example. Monitoring and early-warning results show that the system is stable and efficient , also can improve the scalability and reduce the dependence on central server in IPv6 network.

A novel optical load cell used in icing monitoring on overhead transmission lines

A novel optical load cell based on Fiber Bragg Grating sensing technique was proposed for icing monitoring on high-voltage overhead transmission lines. Compared to the conventional strain gauge load cell, the developed optical load cell has several unique advantages such as unnecessary power supply on site, excellent ability for avoiding electromagnetic interference, and long lifespan. In the load cell design, coupled dual-beam (‘S’ beam) structure was adopted to achieve an accurate measurement, and the part of FBG bonding was carefully chosen to withstand equal and opposite strain, which solved the problem of cross-sensitivity between strain and temperature of FBG sensing. A mixed WDM/TDM (Wave-Division Multiplexing/Time-Division Multiplexing) optical fiber network is proposed to construct an icing monitoring system containing hundreds of FBGs. Result from the tension experiment indicates that the load cell is sensitive to tension, and the sensitivity and resolution of the load cell is 0.04903 pm/N and 20.4 N. The temperature effect on the tension measurement, evaluated by putting the load cell in a temperature-controlled cabinet, is less than ± 0.175%. Furthermore, in order to investigate the reliability of the load cell in icing environment, an experiment was carried out in a climatic chamber, and the results prove that the load cell can work properly in harsh environment.