# Accurate Ranging Based on Transmission Line Channel Monitoring Image and Point Cloud Data Mapping

Authors: Yongdong Dai; Maofei Wang; Feng Mao; Jianguang Yao; Shenyu Wang
Journal: Security and Communication Networks
 (2022)

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## Abstract

Three-dimensional (3D) mapping of power lines is essential for power line inspection. Many remotely sensed data products like light detection and ranging (LiDAR) have been examined for power line surveys. More and more data are being obtained via photogrammetric measurements. This increases the need for the implementation of advanced processing techniques. In recent years, there has been a significant advancement in visualization techniques for power lines using unmanned aerial vehicle (UAV) platform photography. The most advanced of such imaging systems can create dense point clouds. However, the accuracy is very often unstable and dependent on the radiometric quality of images and the efficiency of the image processing technique. In this study, the two-dimensional information is obtained by photographing the real-time panorama of the transmission line channel using a 3D camera, and the three-dimensional information is acquired using laser radar technology. The three-dimensional point orientation of the target object and the transmission line is determined using the mapping relationship between two and three dimensions, the obtained data are calculated, and the calculation results are produced. The proposed method can solve the problem of the image sensor being unable to map spatial distance and can provide broad coverage of the transmission line channel and 24-hours accurate real-time remote monitoring.


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## Body

## 1. Introduction

The power system is an industry closely related to industrial production and people’s life. Electricity is becoming increasingly important as the economy develops. It is an essential infrastructure supply system for the lives of residents and industrial output. The power transmission section is the limb of the entire power system that is responsible for power transmission [1]. To address the imbalance between economies and electricity supply and demand, the state has increased power grid infrastructure construction. The increase in transmission line mileage also increases the risk of patrol inspection. Because power lines usually walk overhead in the natural environment, the invisible risk of normal power transmission is enhanced by irresistible forces such as geography and natural climate [2].The application of laser point cloud technology provides an artificial intelligence means for the construction of power lines [3]. The application of laser radar three-dimensional imaging technology to measure the spatial distance of transmission line corridors can not only accurately and quickly convert data into three-dimensional data, reducing human error, improving accuracy and work efficiency but also run well in some areas with poor natural environments. LiDAR can receive a huge amount of spatial point cloud information in real-time, as well as generate point clouds by combining point cloud and imaging data. Agriculture, exploration, and geology are among the fields where it is gradually being employed [4].Photogrammetric mapping of power lines with the use of photogrammetry is currently a topic of great importance to engineering researchers. If proper data acquisition conditions are not maintained, rendering the three-dimensional (3D) reconstruction of power lines may be challenging [5]. Several remotely-sensed data products, such as thermal sensors, synthetic aperture radar (SAR), LiDAR, land-based mobile mapping data, and UAVs have been considered for power line surveys, safety monitoring, and other geo-survey applications [6]. Most research papers have focused on the extraction of power lines from aerial laser scanning (ALS) data. Gong et al. [7] has proposed the application of remote control technology in many fields, especially in the surveying and mapping of power lines. The remote control technology can be used to identify ground conditions, buildings, roads, and other places. Based on the advantages of machine learning in imaging technology, it can also be applied to the intelligent extraction of transmission line road landmarks. Jie and Zhengyu [8] reported that with the continuous expansion of the scale of the State Grid, the construction of transmission lines also increases and the cleaning of channels has become the main difficulty of transmission line construction. Wang et al. [9] used machine learning algorithms such as random forest (RF) and artificial neural network (ANN) for power line classification in suburban and urban areas. Recently, compact and lightweight UAV-LiDAR sensors were presented on the market, although their performance is limited in terms of scan speed and measurement rate [10]. Ax et al. [11] employed the use of laser scanner data from a UAV Helicopter for vegetation control at high-voltage transmission lines. The 3D reconstruction of power lines from point clouds derived from several UAV pictures has received very little attention. For example, in [12, 13], point clouds from UAV data were analyzed for inspecting power lines and were used to detect cable collisions with terrain obstacles. Several researchers have proposed improving the radiometry at the preliminary image processing stage to improve the accuracy of extracting power lines from UAV images [14]. Fryskowska [15] presented the wavelet-based approach to processing data acquired with a low-cost UAV camera. This method involved the application of algorithms for coarse filtration and precise filtering. Moreover, a new way of calculating the recommended flight height was proposed. Jingzhiet al. [16] proposed a method using UAV images to monitor corridor clearance. To maintain the optimum accuracy of the relative position of wires with respect to surrounding obstacles, the same data were used both to rebuild a point cloud representation of a digital surface model (DSM) and a 3D power line. The method was effective in detecting power lines in a series of images using decorrelation stretch for initial image processing, the modified Prewitt filter for edge improvement, random sample consensus (RANSAC) with added parameters for line fitting, and epipolar geometry for 3D reconstruction.Since the safety of the power transmission line is an important part of the safe operation of the power grid. The distance mapping between the transmission line itself and the ground markers in the surrounding environment is an important method to analyze and predict the hidden risks of the power transmission line [17, 18]. Although the online monitoring equipment can monitor the transmission line in all weather conditions, it is unable to precisely determine the distance of landmarks around the transmission line due to image sensor technology limitations.This study proposes the application of UAV equipped with radar facilities to detect the distance of landmarks around the transmission line, and prospectively applies data fusion mapping technology and a large number of point cloud data to solve the lack of spatial information in visual measurement. The proposed method can perform remote visual monitoring, control the influencing factors of surrounding targets and other transmission line obstacles in real-time, and intervene in time to improve the transmission line’s safety, allowing it to monitor the line all day, in real-time, and accurately.The rest of the manuscript is organized into four sections. Section2 illustrates the proposed design sachem and explains the characteristics of transmission lines. In Section 3, the technological innovation of the proposed study is highlighted. Section 4 illustrates different test results and the conclusion is presented in Section 5.


## 2. Design Scheme

### 2.1. Transmission Line Detection Path

This study is based on the 3D point cloud data processing technology. In the safe operation of power system transmission lines, it is necessary to detect the entire power line. First, the initial information data are obtained through image acquisition and processing techniques [19], and the geographic information and point cloud mapping are obtained. The point cloud data included spatial three-dimensional information data, as well as the color distribution after imaging, which makes the obtained data more specific.Moreover, comprehensive and intuitively reflect accurate real-time information. It is helpful for the follow-up image ranging real-time feedback to obtain more accurate results. The detection path of the transmission line is shown in Figure1. The real-time panorama of the transmission line channel is photographed through the 3D camera to obtain two-dimensional information data. In addition, laser radar technology is employed to obtain the three-dimensional information data of the real-time panorama of the transmission line channel. The relevant mapping relationship is established in the three-dimensional space between the internal orientation elements of the camera and the two-dimensional image. Through the mapping relationship between two-dimensional and three-dimensional, the three-dimensional point orientation of the target and the transmission line is determined. The obtained data is processed to generate the results.Figure 1
Transmission line detection path diagram.


### 2.2. Space Distance Measurement Method of the UAV Transmission Line Corridor and Laser

#### 2.2.1. Point Cloud

The emergence of UAVs has brought convenience to many fields, especially in the harsh geographical environment, replacing human operation has become the research direction of various industries [20]. The principle of using UAVs equipped with laser facilities to detect the space of transmission lines is based on the integration of measurement technology and computer vision techniques. Through high-tech information collection of the measured space, relevant two-dimensional imaging images are extracted, and the two-dimensional images are processed to obtain the measurement data in three-dimensional space. Vision measurement is based on the three-point imaging model of space point, imaging point, and camera center point. Based on this process, the space intersection is carried out to obtain the corresponding three-dimensional coordinate orientation. The specific expression is shown in Figure 2.Figure 2
Visual diagram of space distance measurement method for UAV patrol inspection of transmission line corridor and laser point cloud.In the power system, the use of UAV Patrol has become a technical means [21]. The UAV is equipped with radar equipment to detect the transmission line corridor in real-time in a certain regional space, obtain the point cloud of useful transmission lines and markers, and classify and save the obtained information, such as electric poles and accessories [22]. Through the tracking of transmission line corridors by online monitoring facilities, the risk factors in the image can be identified and the coordinate position of the risk factors can be anchored. The detection of transmission lines through unmanned airborne radar facilities only requires imaging equipment and a camera positioning system. Its small size, convenience, and real-time characteristics are widely used in various fields [23].


## 2.1. Transmission Line Detection Path

This study is based on the 3D point cloud data processing technology. In the safe operation of power system transmission lines, it is necessary to detect the entire power line. First, the initial information data are obtained through image acquisition and processing techniques [19], and the geographic information and point cloud mapping are obtained. The point cloud data included spatial three-dimensional information data, as well as the color distribution after imaging, which makes the obtained data more specific.Moreover, comprehensive and intuitively reflect accurate real-time information. It is helpful for the follow-up image ranging real-time feedback to obtain more accurate results. The detection path of the transmission line is shown in Figure1. The real-time panorama of the transmission line channel is photographed through the 3D camera to obtain two-dimensional information data. In addition, laser radar technology is employed to obtain the three-dimensional information data of the real-time panorama of the transmission line channel. The relevant mapping relationship is established in the three-dimensional space between the internal orientation elements of the camera and the two-dimensional image. Through the mapping relationship between two-dimensional and three-dimensional, the three-dimensional point orientation of the target and the transmission line is determined. The obtained data is processed to generate the results.Figure 1
Transmission line detection path diagram.


## 2.2. Space Distance Measurement Method of the UAV Transmission Line Corridor and Laser

### 2.2.1. Point Cloud

The emergence of UAVs has brought convenience to many fields, especially in the harsh geographical environment, replacing human operation has become the research direction of various industries [20]. The principle of using UAVs equipped with laser facilities to detect the space of transmission lines is based on the integration of measurement technology and computer vision techniques. Through high-tech information collection of the measured space, relevant two-dimensional imaging images are extracted, and the two-dimensional images are processed to obtain the measurement data in three-dimensional space. Vision measurement is based on the three-point imaging model of space point, imaging point, and camera center point. Based on this process, the space intersection is carried out to obtain the corresponding three-dimensional coordinate orientation. The specific expression is shown in Figure 2.Figure 2
Visual diagram of space distance measurement method for UAV patrol inspection of transmission line corridor and laser point cloud.In the power system, the use of UAV Patrol has become a technical means [21]. The UAV is equipped with radar equipment to detect the transmission line corridor in real-time in a certain regional space, obtain the point cloud of useful transmission lines and markers, and classify and save the obtained information, such as electric poles and accessories [22]. Through the tracking of transmission line corridors by online monitoring facilities, the risk factors in the image can be identified and the coordinate position of the risk factors can be anchored. The detection of transmission lines through unmanned airborne radar facilities only requires imaging equipment and a camera positioning system. Its small size, convenience, and real-time characteristics are widely used in various fields [23].


## 2.2.1. Point Cloud

The emergence of UAVs has brought convenience to many fields, especially in the harsh geographical environment, replacing human operation has become the research direction of various industries [20]. The principle of using UAVs equipped with laser facilities to detect the space of transmission lines is based on the integration of measurement technology and computer vision techniques. Through high-tech information collection of the measured space, relevant two-dimensional imaging images are extracted, and the two-dimensional images are processed to obtain the measurement data in three-dimensional space. Vision measurement is based on the three-point imaging model of space point, imaging point, and camera center point. Based on this process, the space intersection is carried out to obtain the corresponding three-dimensional coordinate orientation. The specific expression is shown in Figure 2.Figure 2
Visual diagram of space distance measurement method for UAV patrol inspection of transmission line corridor and laser point cloud.In the power system, the use of UAV Patrol has become a technical means [21]. The UAV is equipped with radar equipment to detect the transmission line corridor in real-time in a certain regional space, obtain the point cloud of useful transmission lines and markers, and classify and save the obtained information, such as electric poles and accessories [22]. Through the tracking of transmission line corridors by online monitoring facilities, the risk factors in the image can be identified and the coordinate position of the risk factors can be anchored. The detection of transmission lines through unmanned airborne radar facilities only requires imaging equipment and a camera positioning system. Its small size, convenience, and real-time characteristics are widely used in various fields [23].


## 3. Technological Innovation

Although the online monitoring device used in a power transmission line can realize real-time monitoring and automatic early warning of the transmission line. However, it is impossible to image and collect the geographical environment around the transmission line in a real-time panorama, to achieve the range of hazard sources, landmarks, and other obstacles, which is the spatial ranging function that the sensor cannot achieve [24]. Aiming at the limitations of the traditional transmission line online monitoring device, this study proposes to use the UAV equipped with radar facilities to detect the distance of landmarks around the transmission line, prospectively applies the data fusion mapping technology and a large number of point cloud data, solves the lack of spatial information in visual measurement, and accurately predict the risk factors in the transmission line channel and the safe distance of the line. In addition, it can monitor the line all day, in real-time and accurately, find, feedback, and solve problems in time.The proposed method can monitor lines with different voltage levels in different natural environments without being affected by geographical characteristics. It has technology leadership and originality. The research has the following innovations:(i)
The two-dimensional spatial information data and three-dimensional spatial information data in the place are fused to obtain different data. The transformation relationship between two-dimensional pixel coordinates and three-dimensional spatial coordinates is used to solve the problem that the imaging sensor cannot realize spatial ranging.(ii)
The calibration technology of interior orientation elements and distortion parameters of multiview camera is proposed, and the accuracy of interior orientation elements reaches the sub-pixel level. Combined with the target distribution and its geometric attributes, a deep learning framework for transmission line feature extraction is constructed, to improve the accuracy of data fusion and achieve the measurement accuracy of landmarks in the transmission line channel to the sub-meter level.(iii)
Realize the millisecond loading of massive coordinate information, solve the problem of data loading, support more than one million concurrent alarms per day, automatically compare the threshold and effectively dispatch orders more than 1000 times, and realize the comprehensive coverage of transmission line channels and 24-hour accurate real-time remote monitoring.


## 4. Test Results

Several typical transmission line channels are selected as the test verification basis to verify the test accuracy and accuracy of accurate ranging based on transmission line channel monitoring image and point cloud data mapping. The various test results are illustrated in the following section.


### 4.1. 500 kV Jianggang 5245 Line #111 Large Side Transmission Line

In this experiment, characteristics of 500 kV Jianggang 5245 line #111 large side transmission line are examined. The distance of the video monitoring pole of the transmission line channel is tested and different information is obtained for analysis as shown in Table1.Table 1
Test results of #111 large side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)LiDAR data (m)Absolute error1Video monitoring rod18.8616.673.44\4.392.19It can be seen that the #111 large side video monitoring pole has a single eye clearance of 18.86 m, an actual clearance of 16.67 m, a single eye measured distance of 3.44 m, a LiDAR data of 4.39 m, and a length measurement error of 2.19 m respectively. Figure3 shows the coincidence between the point cloud and the image.Figure 3
#111 coincidence degree diagram of point cloud and image.It is clear that the coincidence degree between the point cloud and the image in the transmission line channel is still very high, which also shows that the ranging accuracy is high.


### 4.2. 500 kV Jianggang 5245 Line #117 Large Side Transmission Line

According to #117 the characteristics of the transmission line channel on the large side, the distance between the power signs, roadside guardrails, and light poles of the transmission line channel is tested and various information are obtained as shown in Table2.Table 2
Test results of #117 large side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)LiDAR data (m)Absolute error1Power sign24.87——1.434——2Guiding kerb25.3525.470.920.9160.829−0.123The lower part of the lamp pole24.624.661.861.766—−0.06The single eye clearance distances of power signs, roadside guardrails, and the lower part of light poles are 24.87 m, 25.35 m, and 24.60 m, respectively. The actual clearance distances of the roadside guardrail and the lower part of the lamp pole are 25.47 m and 24.66 m, respectively. This shows that for #117 large side transmission lines, the ranging error is very small. Figure4 shows the coincidence between the point cloud and the image of the transmission line channel.Figure 4
#117 coincidence degree of point cloud and image.It is obvious that the point cloud in the #117 transmission line almost completely coincides with the image, which confirms that the ranging accuracy in the transmission line channel is very high.


### 4.3. 500 kV Jianggang 5245 Line #151 Small Side Transmission Line

Based on the characteristics of the #151 transmission line channel on the trumpet side, the distances of each part under the street lamp pole, billboard, and small tree of the transmission line channel were tested and various information was obtained. The obtained results are shown in Table3.Table 3
Test results of #151 small side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)Lidar data (m)Absolute error1The lower part of the street lamp post25.424.281.611.6091.5081.122The lower part of street lamp post II28.8321.171.411.4971.737.663Billboard14.9913.264.614.835.931.734Small tree22.75—1.511.775——5The third lower part of a street lamp17.0518.661.531.069—−1.61Table3 shows that absolute errors of other parts are within the range, except that the data difference between the monocular clearance distance and the actual clearance distance of the lower part of the second street lamp post is a little large. This also shows that the intelligent monitoring image of the transmission line and LiDAR point cloud in this study can not only realize the mapping between the two-dimensional image and three-dimensional point cloud but also accurately and quickly measure the effective distance between the transmission line and nearby targets. Figure 5 shows the coincidence between the point cloud and the image of the transmission line channel in this section.Figure 5
#151 coincidence degree of point cloud and image.The combination of point cloud and image in the transmission line channel is also very close to the actual situation, which also shows that the three-dimensional ranging warning based on LiDAR point cloud based on image recognition warning can effectively identify risk points and reduce the operation risk of the transmission line.


### 4.4. 500 kV Jianggang5245 Line #163 Small Side Transmission Line

We also tested the distances between the transmission line channel and the warning board and the cement pole. Table4 illustrates the obtained results. The single eye clearance distance between the transmission line and the warning board and the cement pole is 22.34 m and 19 m respectively. Due to the environment or some other unfavorable reasons, the actual clearance distance of the warning board is not measurable. Therefore, it is difficult to obtain such data; however, the actual clearance distance of the cement pole is 20.52 m.Table 4
Test results of #163 small side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)Absolute error1Warning sign22.34—1.761.647—2Cement pole1920.528.095.857−1.52Figure6 shows the combination of point cloud and image of the #163 transmission line channel on the trumpet side.Figure 6
#163 coincidence degree diagram of point cloud and image.The combination of point cloud and image for accurate ranging based on transmission line channel monitoring image and point cloud data mapping is very close to the actual situation, which also shows that the proposed method can be used to solve the faults or safety risks caused by human or irresistible factors in remote areas in time and solve them in time.


## 4.1. 500 kV Jianggang 5245 Line #111 Large Side Transmission Line

In this experiment, characteristics of 500 kV Jianggang 5245 line #111 large side transmission line are examined. The distance of the video monitoring pole of the transmission line channel is tested and different information is obtained for analysis as shown in Table1.Table 1
Test results of #111 large side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)LiDAR data (m)Absolute error1Video monitoring rod18.8616.673.44\4.392.19It can be seen that the #111 large side video monitoring pole has a single eye clearance of 18.86 m, an actual clearance of 16.67 m, a single eye measured distance of 3.44 m, a LiDAR data of 4.39 m, and a length measurement error of 2.19 m respectively. Figure3 shows the coincidence between the point cloud and the image.Figure 3
#111 coincidence degree diagram of point cloud and image.It is clear that the coincidence degree between the point cloud and the image in the transmission line channel is still very high, which also shows that the ranging accuracy is high.


## 4.2. 500 kV Jianggang 5245 Line #117 Large Side Transmission Line

According to #117 the characteristics of the transmission line channel on the large side, the distance between the power signs, roadside guardrails, and light poles of the transmission line channel is tested and various information are obtained as shown in Table2.Table 2
Test results of #117 large side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)LiDAR data (m)Absolute error1Power sign24.87——1.434——2Guiding kerb25.3525.470.920.9160.829−0.123The lower part of the lamp pole24.624.661.861.766—−0.06The single eye clearance distances of power signs, roadside guardrails, and the lower part of light poles are 24.87 m, 25.35 m, and 24.60 m, respectively. The actual clearance distances of the roadside guardrail and the lower part of the lamp pole are 25.47 m and 24.66 m, respectively. This shows that for #117 large side transmission lines, the ranging error is very small. Figure4 shows the coincidence between the point cloud and the image of the transmission line channel.Figure 4
#117 coincidence degree of point cloud and image.It is obvious that the point cloud in the #117 transmission line almost completely coincides with the image, which confirms that the ranging accuracy in the transmission line channel is very high.


## 4.3. 500 kV Jianggang 5245 Line #151 Small Side Transmission Line

Based on the characteristics of the #151 transmission line channel on the trumpet side, the distances of each part under the street lamp pole, billboard, and small tree of the transmission line channel were tested and various information was obtained. The obtained results are shown in Table3.Table 3
Test results of #151 small side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)Lidar data (m)Absolute error1The lower part of the street lamp post25.424.281.611.6091.5081.122The lower part of street lamp post II28.8321.171.411.4971.737.663Billboard14.9913.264.614.835.931.734Small tree22.75—1.511.775——5The third lower part of a street lamp17.0518.661.531.069—−1.61Table3 shows that absolute errors of other parts are within the range, except that the data difference between the monocular clearance distance and the actual clearance distance of the lower part of the second street lamp post is a little large. This also shows that the intelligent monitoring image of the transmission line and LiDAR point cloud in this study can not only realize the mapping between the two-dimensional image and three-dimensional point cloud but also accurately and quickly measure the effective distance between the transmission line and nearby targets. Figure 5 shows the coincidence between the point cloud and the image of the transmission line channel in this section.Figure 5
#151 coincidence degree of point cloud and image.The combination of point cloud and image in the transmission line channel is also very close to the actual situation, which also shows that the three-dimensional ranging warning based on LiDAR point cloud based on image recognition warning can effectively identify risk points and reduce the operation risk of the transmission line.


## 4.4. 500 kV Jianggang5245 Line #163 Small Side Transmission Line

We also tested the distances between the transmission line channel and the warning board and the cement pole. Table4 illustrates the obtained results. The single eye clearance distance between the transmission line and the warning board and the cement pole is 22.34 m and 19 m respectively. Due to the environment or some other unfavorable reasons, the actual clearance distance of the warning board is not measurable. Therefore, it is difficult to obtain such data; however, the actual clearance distance of the cement pole is 20.52 m.Table 4
Test results of #163 small side transmission line channel.
Serial numberObjectSingle eye clearance distance (m)Actual clearance distance (m)Monocular measurement (m)Laser rangefinder (m)Absolute error1Warning sign22.34—1.761.647—2Cement pole1920.528.095.857−1.52Figure6 shows the combination of point cloud and image of the #163 transmission line channel on the trumpet side.Figure 6
#163 coincidence degree diagram of point cloud and image.The combination of point cloud and image for accurate ranging based on transmission line channel monitoring image and point cloud data mapping is very close to the actual situation, which also shows that the proposed method can be used to solve the faults or safety risks caused by human or irresistible factors in remote areas in time and solve them in time.


## 5. Conclusion

The development of productivity depends more and more on electricity. The safety of transmission lines ensures the stability of residential and industrial power consumption. The traditional transmission line through manual inspection not only causes missing and wrong inspection of human factors but also increases the risk of personnel safety due to the influence of other factors. Although the online monitoring equipment can monitor the transmission line in all weather conditions, due to the limitations of image sensor technology, it is unable to accurately measure the distance of landmarks around the transmission line. This study proposed the application of UAVs equipped with radar facilities to detect the distance of landmarks around the transmission line. Data fusion mapping technology is applied and a large number of point cloud data is collected to solve the lack of spatial information in visual measurement. It can perform well in real-time remote visual monitoring and regulates the affecting factors of nearby targets and other transmission line impediments. In addition, the method improves the safety of the transmission line, monitors the line all day, in real-time and accurately, and finds, feedback and solves problems in time. Although the proposed method can effectively solve the safety and operation of transmission lines, there are still many factors affecting the inspection of transmission lines, and the problems that can be solved by scientific and technological means need to be further explored to provide support for residents and industrial power supply.



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*Source: 2505620-2022-05-21.xml*