Staged icing forecasting of power transmission lines based on icing cycle and improved extreme learning machine

Sun, Wei; Wang, Caifei

doi:10.1016/j.jclepro.2018.10.197

Cited by 40 publications

(14 citation statements)

References 10 publications

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“…EEMD can separate intrinsic time trend and frequency components from a signal sequence, especially nonlinear and nonstationary signal sequences [25,27]. Therefore, EEMD, as an innovative statistical tool, has been widely used to determine the time series trend in variables across various fields, such as signal and image processing, economics, health, environment, and climate determinations [28][29][30][31]. Recently, EEMD has been applied to the remote sensing field [32,33].…”

Section: Introductionmentioning

confidence: 99%

Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method

Xue

Zhang

et al. 2019

Remote Sensing

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Vegetation is the major component of the terrestrial ecosystem. Understanding both climate change and anthropogenically induced vegetation variation is essential for ecosystem management. In this study, we used an ensemble empirical mode decomposition (EEMD) method and a linear regression model to investigate spatiotemporal variations in the normalized difference vegetation index (NDVI) over the agropastoral ecotone of northern China (APENC) during the 1982–2015 period. A quantitative approach was proposed based on the residual trend (RESTREND) method to distinguish the effects of climatic (i.e., temperature (TEM), precipitation (PRE), total downward solar radiation (RAD), and near surface wind speed (SWS)) and anthropogenic effects on vegetation variations. The results showed that the NDVI exhibited a significant greening trend of 0.002 year−1 over the entire study period of 1982–2015 and that areas with monotonous greening dominated the entire APENC, occupying 40.97% of the region. A browning trend was also found in the central and northern parts of the APENC. PRE presented the highest spatial correlation with the NDVI and climate factors, suggesting that PRE was the most important factor affecting NDVI changes in the study area. In addition, the RESTREND results indicated that anthropogenic contributions dominated the vegetation variations in the APENC. Therefore, reusing farmland for grass and tree planting made a positive contribution to vegetation restoration, while deforestation, overgrazing, and the reclamation of grasslands were the opposite. In addition, with the continuous implementation of national ecological engineering programs such as the Grain to Green Program, positive human activity contributions to vegetation greening significantly increased. These results will support decision- and policy-making in the assessment and rehabilitation of ecosystems in the study region.

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Section: Introductionmentioning

confidence: 99%

Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method

Xue

Zhang

et al. 2019

Remote Sensing

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“…[1][2][3] For example, ice accumulation on wind turbine blades and power transmission lines results in aerodynamic losses and tower collapse. [4,5] It has been reported that the production of wind turbines can be decreased by up to 50% owing to surface icing. [4] Besides, icing-induced safety hazard is also a worldwide concern.…”

Section: Introductionmentioning

confidence: 99%

An Extreme‐Environment‐Resistant Self‐Healing Anti‐Icing Coating

Tian

et al. 2022

Small

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Traditional anti-icing strategies, including mechanical, electrothermal, and chemical deicing, are commonly used on outdoor infrastructures and transportations. [7] However, these methods are inefficient, energy-consuming, and/or unfriendly to the environment. [8] More efficient and environment-friendly antiicing coatings can inhibit ice nucleation and decrease ice adhesion without human intervention, having attracted more attention in recent years. [9] Up to date, there have been many types of advanced antiicing coatings including superhydrophobic surfaces, [10,11] slippery liquid-infused porous surfaces, [12,13] and other ice-phobic surfaces. [14][15][16] They have presented high efficiency to prevent icing based on different mechanisms. However, artificial surface-based coatings are commonly difficult to work well in outdoor environments, especially in extreme weather events (such as freezing weather or acid rain). Once mechanical damage induced by surroundings or icing/deicing cycles on coating surface, ice nucleation and ice-substrate interlocking would be evoked, resulting in icing promotion and stronger ice adhesion. Therefore, it is highly desired to develop an anti-icing coating that possesses excellent durability in resistance to universal conditions.Inspired by biological tissues, self-healing materials can be employed to enhance durability in a variety of applications such as flexible electronics and energy storage devices. [17,18] Self-healing ability can repair potential defects to avoid frequent maintenance of devices and significantly prolong the service lifetime. It can thus be proposed that autonomously self-healing anti-icing coatings can effectively inhibit defect-induced icing and ensure coating durability. [19,20] However, there are few reports with respect to autonomously self-healing anti-icing under extreme conditions. The challenge is mainly owing to two aspects: 1) There is a tradeoff between anti-icing performance and self-healing property. Because self-healing commonly relies on dynamic bonding interactions (such as dynamic H-bonds) that can promote ice adhesion on the material surface. [21,22] 2) Underwater or in freezing conditions, the healing efficiency of materials would be significantly decreased because the dynamic bond reconnection would be inhibited by water molecules, and the mobility of polymer chains is decreased in low temperature to prevent healing. [23] Anti-icing coatings on outdoor infrastructures and transportations inevitably suffer from surface injuries, especially in extreme weather events (e.g., freezing weather or acid rain). The coating surface damage can result in anti-icing performance loss or even icing promotion. The development of anti-icing coatings that enables self-healing in extreme conditions is highly desired but still challenging. Herein, an extreme-environment-resistant selfhealing anti-icing coating is developed by integrating fluorinated graphene (FG) into a supramolecular polymeric matrix. The coating exhibits both antiicing and deicing performa...

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“…[ 4,5 ] Occasionally, ice accumulation can threaten the safety of aircraft flights, [ 6 ] cause the collapse of power transmission lines, communication base stations and damage to buildings. [ 7,8 ] This creates unpredictable economic consequences. The traditional de‐icing methods such as mechanical de‐icing, [ 9 ] electro‐thermal de‐icing, [ 10 ] manual de‐icing, [ 11 ] and microwaves de‐icing [ 12 ] typically exhibit inefficiency and energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Superhydrophobic and Photothermal PVDF/CNTs Durable Composite Coatings for Passive Anti‐Icing/Active De‐Icing

Jiang

Liu

2021

Adv Materials Inter

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The formation and accumulation of ice on the surfaces of external facilities and instrumentation can often cause irreparable damage and disaster. It is significant to develop an easily used technology with a passive anti‐icing property to improve the de‐icing/anti‐icing efficiency. In this work, polyvinylidene fluoride (PVDF) and carbon nanotubes (CNTs) are combined to modulate a hierarchical coating structure. The coating surface is treated by 1H,1H,2H,2H‐perfluorodecyltrimethoxysilane vapor with a lower surface energy. The resultant coating has excellent anti‐icing properties with a water contact angle of 163°, icing delay time up to 584 s, and low ice adhesion of 13.2 kPa (easily removed by a natural wind), which is a result of the multilayered structure (provided by the micro‐size PVDF particles and nano‐size CNTs). The excellent anti‐icing properties are kept even after mechanical abrasion and chemical attacking. The robustness of the coating is from the continuous network formed by PVDF melt in the heating process. The efficient photothermal conversion of CNTs can generate additional heat at low temperatures under the light illumination, which makes the coating achieve a photothermal de‐icing performance. This multifunctional photothermal de‐icing coating will have a wide range of applications in the outside environment.

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Staged icing forecasting of power transmission lines based on icing cycle and improved extreme learning machine

Cited by 40 publications

References 10 publications

Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method

Detecting Vegetation Variations and Main Drivers over the Agropastoral Ecotone of Northern China through the Ensemble Empirical Mode Decomposition Method

An Extreme‐Environment‐Resistant Self‐Healing Anti‐Icing Coating

Superhydrophobic and Photothermal PVDF/CNTs Durable Composite Coatings for Passive Anti‐Icing/Active De‐Icing

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