CN-122020535-A - Power grid microclimate data calibration method, device, equipment and storage medium

CN122020535ACN 122020535 ACN122020535 ACN 122020535ACN-122020535-A

Abstract

The application discloses a method, a device, equipment and a storage medium for calibrating micro-meteorological data of a power grid, and belongs to the technical field of intelligent monitoring of power equipment. The method comprises the steps of obtaining image data of the surface of power grid equipment and microclimate sensor data of an area where the power grid equipment is located, carrying out space-time alignment and fusion on the image data and the microclimate sensor data to form an associated data set, carrying out layered denoising processing on the image data in the associated data set to obtain a preprocessed image, extracting and quantifying morphological state characteristics of a coating on the surface of the power grid equipment based on the preprocessed image and the microclimate sensor data, dynamically generating parameterization rules for calibrating the microclimate sensor data based on the quantified morphological state characteristics, calibrating the microclimate sensor data by applying the parameterization rules, and outputting calibrated data. The embodiment of the application can improve the accuracy of microclimate monitoring data.

Inventors

WANG LINGZI
WU HUIJUN
WANG HAOHUAI
SU HUAYING
DENG LIYUAN
SHEN HAIBO
HUANG WEIZHI
DENG WEISI
LIU JIALE

Assignees

中国南方电网有限责任公司

Dates

Publication Date: 20260512
Application Date: 20260127

Claims (10)

1. A method for calibrating microclimate data of a power grid, comprising the steps of: acquiring image data of the surface of power grid equipment and microclimate sensor data of an area where the power grid equipment is located, and performing space-time alignment and fusion on the image data and the microclimate sensor data to form an associated data set; carrying out layering denoising treatment on the image data in the associated data set to obtain a preprocessed image; extracting and quantifying morphological state features of the grid device surface coating based on the pre-processed image and the microclimate sensor data; Dynamically generating parameterization rules for calibrating the microclimate sensor data based on the quantified morphological state features; And calibrating the microclimate sensor data by applying the parameterization rule, and outputting the calibrated data.
2. The method of claim 1, wherein the acquiring the image data of the surface of the power grid device and the microclimate sensor data of the area where the power grid device is located, and performing space-time alignment and fusion on the image data and the microclimate sensor data to form the association data set, comprises: Constructing a space coordinate system of the surface of the power grid equipment; acquiring image data of the surface of the power grid equipment, wherein the image data comprises a high-resolution image and an infrared temperature distribution map; Synchronously collecting microclimate sensor data at corresponding position points of the space coordinate system, wherein the microclimate sensor data comprises at least one of sand and dust particle density, sand and dust particle size distribution, rainfall humidity distribution, mud film surface roughness and mud film surface adhesion; And based on the time stamp and the space coordinates, fusing the microclimate sensor data serving as an environment label with the high-resolution image and the infrared temperature distribution map to obtain the associated data set.
3. The method of claim 1, wherein performing hierarchical denoising processing on the image data in the associated dataset to obtain a preprocessed image comprises: Identifying and filtering low-frequency background noise formed by uniform sediment of sand dust in the image data; removing high-frequency stripe noise caused by rainfall flushing in the image data by adopting an edge-preserving filter; Texture and spectral features in the image data that are related to coating moisture content or adhesion are preserved and emphasized by feature enhancement transformations.
4. The method of claim 1, wherein the grid device surface coating is a fouling mud film or an ice coating and the morphological state features are cracking state features.
5. The method of claim 4, wherein the crack status features include at least one of crack density, width, depth, morphology classification, and network connectivity, wherein the extracting and quantifying morphology status features of the grid plant surface coating based on the pre-processed image and the microclimate sensor data comprises: extracting edge contours of the cracks from the preprocessed images, and calculating crack widths; Estimating the relative depth of the crack by combining the particle size data of the sand particles in the microclimate sensor data; and counting the number of cracks and branching conditions in a unit area, and determining the crack density and the crack morphology classification.
6. The method of claim 5, wherein dynamically generating parameterized rules for calibrating the microclimate sensor data based on the quantified morphological state features comprises: Establishing a correlation model between the cracking state characteristics and the data errors of the microclimate sensor, wherein the correlation model is a statistical model or a graph model constructed based on the cracking network connectivity characteristics and the near-surface humidity gradient data; And calculating the sensor data error compensation coefficient through the association model according to the cracking state characteristics at the current moment to obtain the error compensation coefficient forming the parameterization rule.
7. The method of claim 5, wherein after said extracting and quantifying morphological state features of the grid plant surface coating, the method further comprises: and dynamically adjusting the acquisition frequency of the image data or the microclimate sensor data according to the quantized morphological state characteristics or the change rate thereof.
8. A power grid microclimate data calibration device, comprising: The fusion module is used for acquiring image data of the surface of the power grid equipment and microclimate sensor data of an area where the power grid equipment is located, and carrying out space-time alignment and fusion on the image data and the microclimate sensor data to form a correlation data set; the denoising module is used for carrying out layered denoising processing on the image data in the associated data set to obtain a preprocessed image; The quantization module is used for extracting and quantizing morphological state characteristics of the surface coating of the power grid equipment based on the preprocessed image and the microclimate sensor data; The generation module is used for dynamically generating a parameterization rule for calibrating the microclimate sensor data based on the quantized morphological state characteristics; And the calibration module is used for calibrating the microclimate sensor data by applying the parameterization rule and outputting the calibrated data.
9. An electronic device comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the grid microclimate data calibration method according to any one of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the grid microclimate data calibration method according to any one of claims 1 to 7.

Description

Power grid microclimate data calibration method, device, equipment and storage medium Technical Field The application relates to the technical field of intelligent monitoring of power equipment, in particular to a method, a device, equipment and a storage medium for calibrating microclimate data of a power grid. Background The micro-meteorological data of the power grid refers to local and real-time environmental data which directly influence the safe operation of power grid equipment (such as a power transmission line and an insulator). Currently, related monitoring mainly relies on sensor networks deployed in towers or substations, such as anemometers, humidity sensors, image monitoring devices, etc., and common methods include calibration techniques based on multi-sensor data fusion, with the objective of improving the data reliability of single-point sensors through algorithmic processing. However, in practical application, the method has obvious limitation that most data fusion algorithms excessively depend on mathematical statistical relations among sensor readings, and cannot fully combine the microclimate environment where equipment is actually located and the physical state change thereof, so that a calibration result often deviates from a real insulation degradation process, and the actual running risk of the equipment cannot be accurately reflected. Disclosure of Invention The embodiment of the application aims to provide a method, a device, equipment and a storage medium for calibrating micro-meteorological data of a power grid, which can effectively improve the accuracy of micro-meteorological monitoring data. To achieve the above object, a first aspect of an embodiment of the present application provides a method for calibrating micro meteorological data of a power grid, including: acquiring image data of the surface of power grid equipment and microclimate sensor data of an area where the power grid equipment is located, and performing space-time alignment and fusion on the image data and the microclimate sensor data to form an associated data set; carrying out layering denoising treatment on the image data in the associated data set to obtain a preprocessed image; extracting and quantifying morphological state features of the grid device surface coating based on the pre-processed image and the microclimate sensor data; Dynamically generating parameterization rules for calibrating the microclimate sensor data based on the quantified morphological state features; And calibrating the microclimate sensor data by applying the parameterization rule, and outputting the calibrated data. Compared with the prior art, the calibration method for the micro-meteorological data of the power grid has the advantages that the calibration method for the micro-meteorological data of the power grid synchronously acquires surface image data of the power grid equipment and micro-meteorological sensor data of the area where the surface image data of the power grid equipment are located, performs space-time alignment and fusion, builds a correlation mapping basis of the surface state of the equipment and environmental meteorological data, effectively avoids calibration deviation caused by single type data information, guarantees the integrity and accuracy of relevant effective information of a surface coating of the equipment in the image data through layering denoising processing of the image data, provides high-quality data support for accurate extraction of follow-up morphological state features, establishes internal correlation of the physical state of the coating and the meteorological sensor data based on the preprocessed image and the micro-meteorological sensor data, dynamically generates parameterization rules adapting to the current coating state, breaks through the limitation of the complex and changeable coating environment of a fixed calibration mode, finally achieves targeted calibration of the micro-meteorological sensor data through the parameterization rules, remarkably improves the measurement accuracy and reliability of the micro-meteorological data, and provides more accurate assessment for the meteorological data of power grid running state and fault early warning conditions. In some embodiments, the acquiring image data of a surface of the power grid device and micro-weather sensor data of an area where the power grid device is located, and performing space-time alignment and fusion on the image data and the micro-weather sensor data to form an associated data set includes: Constructing a space coordinate system of the surface of the power grid equipment; acquiring image data of the surface of the power grid equipment, wherein the image data comprises a high-resolution image and an infrared temperature distribution map; Synchronously collecting microclimate sensor data at corresponding position points of the space coordinate system, wherein the microclimate sensor data comprises at least one of