A sensor access method and system for internet of things

Abstract

The application relates to a sensor access method and system of an Internet of Things, and relates to the technical field of sensors, which comprises the following steps: collecting detection specifications and sensor specifications; calling partial discharge detection positions from the detection specifications; generating partial discharge detection paths through the partial discharge detection positions; collecting reference signal ranges based on the partial discharge detection paths; obtaining marking positions through the detection specifications and the sensor specifications; obtaining deviation positions and deviation distances according to the falling conditions of the marking positions and the reference signal ranges; calling transfer numbers according to the deviation distances, and controlling preset transfer unmanned aerial vehicles to fly to the transfer numbers and the deviation positions. The application has the effect of improving the accuracy of sensor detection.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and in particular to a sensor access method and system for the Internet of Things. Background Technology

[0002] A sensor is a device that can sense or detect specific physical, chemical, biological, or other signals in the external environment and convert them into electrical signals (or other forms of signals) that can be processed, transmitted, or stored.

[0003] When a drone equipped with a partial discharge sensor detects partial discharge phenomena on a power transmission line, the drone needs to maintain a certain distance from the power transmission line and fly along it. At this time, the partial discharge sensor detects the parameters of the power transmission line and its components to analyze whether partial discharge phenomena occur on the power transmission line and its components.

[0004] When a drone equipped with a partial discharge sensor detects partial discharge phenomena, if the parameters of the power transmission line and its components are located in a region with weak signal, the drone's signal output will deviate, affecting the accuracy of the sensor detection. Summary of the Invention

[0005] To improve the accuracy of sensor detection, this invention provides a sensor access method and system for the Internet of Things.

[0006] In a first aspect, the present invention provides a sensor access method for the Internet of Things, employing the following technical solution:

[0007] A sensor access method for the Internet of Things (IoT) includes:

[0008] S10: Data acquisition and detection specifications and sensor specifications;

[0009] S11: Retrieve the partial discharge detection location from the detection specifications;

[0010] S12: Generate a partial discharge detection path based on the partial discharge detection location;

[0011] S13: Acquire reference signal range based on partial discharge detection path;

[0012] S14: Obtain the marked position by checking the detection specifications and sensor specifications;

[0013] S15: Obtain the deviation position and deviation distance based on the overlap between the mark position and the reference signal range;

[0014] S16: Retrieve the transit number based on the deviation distance, and control the preset transit drone to fly with the transit number and deviation position.

[0015] By adopting the above technical solution, the marking position and reference signal range are obtained by analyzing the detection specifications and sensor specifications. Based on the falling within the marking position and reference signal range, the deviation position and relay number are obtained. The relay drone with the relay number is controlled to fly at the deviation position, thereby enabling data relay transmission to drones equipped with partial discharge sensors outside the signal range, reducing the probability of signal output deviation in drones and improving the accuracy of sensor detection.

[0016] Optionally, methods for controlling the transit drone to fly with the transit number and offset position include:

[0017] S20: Obtain the transfer path by using the deviation position and the partial discharge detection path;

[0018] S21: Collect image detection information of the transit path;

[0019] S22: Update the transit path based on image detection information;

[0020] S23: Obtain the avoidance path based on the transit path before and after the update;

[0021] S24: Retrieve the avoidance distance and avoidance time from the avoidance path;

[0022] S25: Based on the avoidance distance, sensor specifications, and image detection information, a correction value is obtained, and when the relay drone is controlled to fly along the relay path, the correction value is output at the avoidance time point.

[0023] By adopting the above technical solution, the image detection information in the transit path of the transit drone is analyzed to obtain a new transit path. The transit paths before and after the update are compared to obtain the correction value and avoidance time point. When the transit drone flies along the transit path, the correction value is output at the avoidance time point. Thus, when the transit drone avoids, the data that has errors caused by the position deviation of the transit drone is corrected, thereby improving the accuracy of sensor detection.

[0024] Optional methods for updating transit paths include:

[0025] S30: Collect information about the surrounding environment of the transit route;

[0026] S31: Obtain transit specifications through transit number;

[0027] S32: Retrieve the baseline safety range from the transit specifications;

[0028] S33: Combine image detection information, surrounding environment information, and baseline safety range to obtain the obstacle range;

[0029] S34: Obtain the minimum lateral movement distance based on the transit path and obstacle range;

[0030] S35: Obtain the marked lateral position based on the lateral distance and the transit path;

[0031] S36: Based on whether the marker's lateral movement position falls within the reference signal range, select to update the relay path or update the lateral movement distance;

[0032] S37: Update the transit path using the updated lateral distance.

[0033] Optional methods for determining the obstacle range include:

[0034] S40: Retrieve historical image information and current image information from image detection information, and retrieve historical environmental information and current environmental information from surrounding environmental information;

[0035] S41: Identify the type of obstacle tree using current image information;

[0036] S42: Retrieve obstacle tree parameters based on obstacle tree type and historical image information;

[0037] S43: Obtain swaying control parameters based on obstacle tree parameters and historical environmental information;

[0038] S44: Based on the current environmental information and swaying comparison parameters, obtain the current swaying range and define the current swaying range as the obstacle range.

[0039] Optional methods for determining the swaying control parameters include:

[0040] S50: Obtain labeled control parameters by combining obstacle tree parameters with historical environmental information;

[0041] S51: Obtain historical time periods based on historical image information;

[0042] S52: Retrieve baseline sway parameters from marker control parameters using historical time periods and historical environmental information;

[0043] S53: Combine historical time periods and historical image information to obtain historical swaying parameters;

[0044] S54: Compare historical sway parameters with baseline sway parameters to obtain deviation sway parameters and deviation time periods;

[0045] S55: Obtain the interval duration based on the current image information and the deviation time period;

[0046] S56: The degree of damage is obtained by using the interval duration, deviation swaying parameters, and historical environmental information;

[0047] S57: Based on the degree of damage and the labeled control parameters, the swaying control parameters are obtained.

[0048] By adopting the above technical solution and analyzing the degree of damage to trees to obtain swaying control parameters, it is possible to further understand the range of swaying of obstacle trees, improve the accuracy of relay drone avoidance, and enhance the safety of relay drone operations.

[0049] Optional methods for updating correction values ​​include:

[0050] S60: Obtain the avoidance sway parameters by comparing the avoidance time point with the swaying comparison parameters;

[0051] S61: Obtain the occlusion parameters within the avoidance distance based on the avoidance swaying parameters and obstacle tree parameters;

[0052] S62: Obtain the occlusion correction coefficient through the occlusion parameters;

[0053] S63: The correction value is obtained based on the clearance distance, sensor specifications, and occlusion correction coefficient.

[0054] Optionally, methods for controlling the relay drone after it has taken flight include:

[0055] S70: Collects the detection power of relay drones and preset partial discharge drones;

[0056] S71: Obtain the operating power based on the transfer path and partial discharge detection path;

[0057] S72: Compare the detected power level with the operating power level to determine if the power level exceeds the limit, and select between the transfer path and the partial discharge detection path to obtain an auxiliary charging path;

[0058] S73: Control the preset charging device to assist the operation of the charging path.

[0059] Optionally, methods for controlling the operation of the auxiliary charging path include:

[0060] S80: Collects information on the charging location, charging time, and corresponding detection environment of the charging device;

[0061] S81: Combine the charging location and charging time to retrieve solar irradiance information from the detection environment information;

[0062] S82: The shadow range is obtained by combining solar illumination information with environmental detection information;

[0063] S83: Update the shadow range based on solar illumination information, relay path, and partial discharge detection path;

[0064] S84: Compare the shadow range with the preset charge range to obtain the shadow occlusion range;

[0065] S85: Reflection parameters are obtained based on the shadow occlusion range and solar illumination information;

[0066] S86: Update reflection parameters by shadow range and reflect the sun with reflection parameters.

[0067] Optional methods for verifying reflection parameters include:

[0068] S90: Acquires image information of the surrounding area at the charging location;

[0069] S91: Obtain the operating range through reflection parameters;

[0070] S92: Identify the range of marked obstacles within the operating area from surrounding image information;

[0071] S93: Update reflection parameters by marking obstacle ranges.

[0072] Secondly, this application provides a sensor access system for the Internet of Things, which adopts the following technical solution:

[0073] A sensor access system for the Internet of Things (IoT) includes:

[0074] The acquisition module is used to acquire detection specifications, sensor specifications, and reference signal range.

[0075] A memory used to store a program for a sensor access method in the Internet of Things;

[0076] The processor is used to load and execute programs stored in memory.

[0077] In summary, this application includes at least one of the following beneficial technical effects:

[0078] 1. By analyzing the detection specifications and sensor specifications, the mark position and reference signal range are obtained. Based on the fall of the mark position and reference signal range, the deviation position and relay number are obtained. The relay drone with the relay number is controlled to fly at the deviation position, thereby enabling data relay transmission to drones equipped with partial discharge sensors outside the signal range, reducing the probability of deviation in the drone's signal output and improving the accuracy of sensor detection.

[0079] 2. By analyzing the image detection information in the transit path of the transit drone, a new transit path is obtained. The transit paths before and after the update are compared to obtain the correction value and avoidance time point. When the transit drone flies along the transit path, the correction value is output at the avoidance time point. Thus, when the transit drone avoids, the data that has errors caused by the position deviation of the transit drone is corrected, thereby improving the accuracy of sensor detection.

[0080] 3. By analyzing the degree of damage to trees to obtain swaying control parameters, the range of swaying of obstacle trees can be further understood, improving the accuracy of relay drone avoidance and enhancing the safety of relay drone operations. Attached Figure Description

[0081] Figure 1 This is a flowchart of a sensor access method for the Internet of Things according to an embodiment of the present invention;

[0082] Figure 2 This is a flowchart of a method for controlling a relay drone to fly according to a relay number and a deviation position, according to an embodiment of the present invention.

[0083] Figure 3 This is a flowchart of the method for determining the swaying control parameters according to an embodiment of the present invention. Detailed Implementation

[0084] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0085] Reference Figure 1 This application discloses a sensor access method for the Internet of Things, including the following steps:

[0086] S10: Data acquisition and detection specifications and sensor specifications.

[0087] The testing specifications refer to the specifications of components that need to be tested for partial discharge. These components include power transmission lines. The testing specifications can be obtained by pre-entering the information by the operator.

[0088] Partial discharge drones refer to drones equipped with partial discharge sensors.

[0089] Sensor specifications refer to the parameter specifications of the sensors installed on the drone for detecting partial discharge phenomena, which can be obtained through pre-input by the operator.

[0090] S11: Retrieve the partial discharge detection location from the detection specifications.

[0091] Partial discharge detection location refers to the location of the component that needs to be tested for partial discharge. The partial discharge detection location is obtained by retrieving it from the test specifications.

[0092] S12: Generate a partial discharge detection path based on the partial discharge detection location.

[0093] Partial discharge detection path refers to the flight path of an UAV during partial discharge detection. The partial discharge detection path is obtained by analyzing each partial discharge detection location. The analysis method for partial discharge detection path is common knowledge to those skilled in the art and will not be elaborated upon here.

[0094] S13: Acquire reference signal range based on partial discharge detection path.

[0095] The reference signal range refers to the range of signals that can be received around the partial discharge detection path. The reference signal range is obtained by the system from the signal range generated by the signal sources around the partial discharge detection path.

[0096] S14: Obtain the marked position by checking the detection specifications and sensor specifications.

[0097] The marked position refers to the location where the partial discharge UAV inspects the component. The marked position is obtained by analyzing the inspection specifications and sensor specifications. In this embodiment, a threshold is set for the distance between the sensor and the component for detection. This threshold is preset by the operator and will not be elaborated upon here.

[0098] S15: Obtain the deviation position and deviation distance based on the alignment of the marker position with the reference signal range.

[0099] Deviation position refers to the mark position that does not fall within the reference signal range, and deviation distance refers to the distance between the deviation position and the reference signal range. By analyzing the fall of the mark position and the reference signal range, the mark position that does not fall within the reference signal range is defined as the deviation position, and the distance between the deviation position and the nearest reference signal range is calculated as the deviation distance.

[0100] S16: Retrieve the transit number based on the deviation distance, and control the preset transit drone to fly with the transit number and deviation position.

[0101] A relay drone refers to a drone used to relay data from a partial discharge drone before further transmission. A relay number is the unique identifier for the relay drone; different numbers correspond to different models of relay drones, and different models have different transmission distances. Therefore, the relay number is selected from those drones with a transmission distance greater than the deviation distance, and the relay drone with that number is controlled to synchronously fly to the deviation location to relay the data.

[0102] Reference Figure 2 Methods for controlling relay drones to fly according to relay number and deviation position include:

[0103] S20: Obtain the transfer path by using the deviation position and the partial discharge detection path.

[0104] The relay path refers to the flight path of the relay drone. By analyzing the partial discharge detection path, multiple paths parallel to the partial discharge detection path are obtained, and the path that passes through the deviation position is selected from each path as the relay path.

[0105] S21: Collect image detection information of the transit path.

[0106] Image detection information is obtained from images captured by the camera on the relay drone as it flies along the relay path.

[0107] S22: Update the transit path based on image detection information.

[0108] A new transit path is obtained by analyzing the image detection information.

[0109] S23: Obtain the avoidance path based on the transit path before and after the update.

[0110] The avoidance path refers to the path taken by a transit drone when avoiding obstacles. The avoidance path is the path corresponding to the difference between the updated transit path and the new transit path.

[0111] S24: Retrieve the avoidance distance and avoidance time from the avoidance path.

[0112] The avoidance distance refers to the straight-line distance between a relay drone and a partial discharge drone within the avoidance path segment. The avoidance time point refers to the time point within the avoidance path segment where the avoidance distance occurs. The avoidance distance and avoidance time point are retrieved from the avoidance path.

[0113] S25: Based on the avoidance distance, sensor specifications, and image detection information, a correction value is obtained, and when the relay drone is controlled to fly along the relay path, the correction value is output at the avoidance time point.

[0114] The correction value refers to the coefficient value used to correct the signal deviation caused by the avoidance distance. The correction value is obtained by analyzing the avoidance distance, sensor specifications, and image detection information. When the relay drone flies along the relay path, the correction value is output at the avoidance time point to correct the signal transmitted by the partial discharge drone at the avoidance time point.

[0115] Methods for updating transit routes include:

[0116] S30: Collect information about the surrounding environment of the transit route.

[0117] Surrounding environment information refers to the environmental information around the transit path. This information includes the altitude and azimuth of the sun's illumination. The information obtained by detecting the environment around the transit path using corresponding sensors and devices can be used as surrounding environment information.

[0118] S31: Obtain transit specifications through transit number.

[0119] The transit specifications refer to the parameter specifications of the transit drone with the transit number. The transit specifications are obtained by analyzing the transit number. Different transit numbers have different transit specifications, which will not be elaborated here.

[0120] S32: Retrieve the baseline safety range from the transit specifications.

[0121] The baseline safety range refers to the area that a relay-specification drone traverses during flight. It is determined by taking the maximum cross-sectional area corresponding to the direction the relay drone takes towards the relay path from the relay specifications.

[0122] S33: Combine image detection information, surrounding environment information, and baseline safety range to obtain the obstacle range.

[0123] Obstacle range refers to the range of obstacles that the transit drone needs to avoid. The obstacle range is obtained by analyzing image detection information, surrounding environment information, and baseline safety range.

[0124] S34: Obtain the minimum lateral movement distance based on the transit path and obstacle range.

[0125] Lateral movement distance refers to the distance that a relay drone needs to move laterally to avoid an obstacle. It is calculated by comparing the distances that the relay drone needs to move away from or closer to the partial-discharge drone when avoiding an obstacle, based on the relay path, and taking the minimum distance as the lateral movement distance. The method for analyzing lateral movement distance is common knowledge to those skilled in the art and will not be elaborated here.

[0126] S35: Obtain the marked lateral position based on the lateral distance and the transit path.

[0127] The marked lateral movement position refers to the position of the relay drone after lateral movement. The position point offset by the lateral movement distance in combination with the relay path is used as the marked lateral movement position.

[0128] S36: Based on whether the marker's lateral movement position falls within the range of the reference signal, select to update the relay path or update the lateral movement distance.

[0129] By analyzing the lateral movement position of the marker and the reference signal range, when the lateral movement position of the marker falls within the reference signal range, it indicates that the relay drone will not exceed the signal transmission range when it approaches the partial discharge drone to avoid obstacles. Therefore, a new relay path is obtained by combining the lateral movement distance and the relay path.

[0130] When the marked lateral movement position does not fall within the reference signal range, it indicates that the relay drone is moving closer to the partial discharge drone to avoid the obstacle, which exceeds the signal transmission range. In this case, the lateral movement distance corresponding to the range where the relay drone moves away from the partial discharge drone to avoid the obstacle is taken as the new lateral movement distance.

[0131] S37: Update the transit path using the updated lateral distance.

[0132] A new transit path is obtained by combining the updated lateral distance with the transit path. The method for updating the transit path is common knowledge to those skilled in the art and will not be elaborated here.

[0133] Methods for determining the extent of obstacles include:

[0134] S40: Retrieve historical image information and current image information from image detection information, and retrieve historical environmental information and current environmental information from surrounding environmental information.

[0135] Historical image information refers to image detection information prior to the current time period, while current image information refers to image detection information for the current time period. This is achieved by retrieving historical image information and current image information from the image detection information.

[0136] Historical environmental information refers to the surrounding environment information prior to the current time period, while current environmental information refers to the surrounding environment information during the current time period. This is achieved by retrieving historical and current environmental information from the surrounding environmental information.

[0137] S41: Identify the type of obstacle tree using current image information.

[0138] Obstacle tree type refers to the type of tree that hinders the transit drone from flying along the transit path. This is determined by identifying images of trees within a baseline safety range from the current image information and matching these images to determine the tree type as the obstacle tree type. The method for matching obstacle tree types is common knowledge to those skilled in the art and will not be elaborated upon here.

[0139] S42: Retrieve obstacle tree parameters based on obstacle tree type and historical image information.

[0140] Obstacle tree parameters refer to the static growth parameters and historical swaying parameters of obstacle trees. The basic dimensions of the obstacle tree type are extracted from historical image information as static growth parameters, and the amplitude, radius, and range of swaying of the obstacle tree type are extracted as historical swaying parameters. The combination of historical swaying parameters and static growth parameters constitutes the obstacle tree parameters.

[0141] S43: Obtain swaying control parameters based on obstacle tree parameters and historical environmental information.

[0142] Swaying control parameters refer to the baseline model parameters that reflect the swaying radius of obstacle trees under environmental influences. Swaying control parameters are obtained by analyzing obstacle tree parameters and historical environmental information.

[0143] S44: Based on the current environmental information and swaying comparison parameters, obtain the current swaying range and define the current swaying range as the obstacle range.

[0144] The current swaying range refers to the range of swaying of the obstacle trees under the influence of the current environmental information during the current time period. The current swaying range is matched from the swaying comparison parameters by the current environmental information and defined as the obstacle range.

[0145] Reference Figure 3 The methods for determining the swaying control parameters include:

[0146] S50: Obtain the label control parameters by combining obstacle tree parameters with historical environmental information.

[0147] Labeled control parameters refer to the comparative data formed by associating obstacle tree parameters with historical environmental information according to time. Labeled control parameters contain the correspondence between obstacle tree parameters and historical environmental information. For example, under a certain wind speed in the historical environmental information of the same time period, the parameter of the swaying of the obstacle tree in the static growth of the same time period.

[0148] S51: Obtain historical time periods based on historical image information.

[0149] Historical time periods refer to the time periods during which historical image information was collected. Historical time periods are retrieved by extracting the timestamps from the historical image information.

[0150] S52: Retrieve the baseline sway parameters from the marker comparison parameters using historical time periods and historical environmental information.

[0151] The baseline sway parameter refers to the swaying parameter of obstacle data under historical environmental information during a historical period. The baseline sway parameter is obtained by matching the historical period and historical environmental information from the labeled control parameters.

[0152] S53: Combine historical time periods and historical image information to obtain historical swaying parameters.

[0153] Historical swaying parameters refer to the parameters of the actual swaying of obstacle trees in historical image information during historical periods. These parameters are identified by analyzing historical image information from historical periods.

[0154] S54: Compare historical sway parameters with baseline sway parameters to obtain deviation sway parameters and deviation time periods.

[0155] Deviation sway parameter refers to the parameter that deviates from the corresponding data between historical sway parameter and benchmark sway parameter. When a tree is damaged, the range of swaying may increase. By comparing the corresponding data in historical sway parameter and benchmark sway parameter, the data in historical sway parameter that exceeds the corresponding data in benchmark sway parameter is defined as deviation sway parameter.

[0156] The deviation period refers to the time period during which the deviation sway parameter occurs. The deviation period is defined as the historical time period during which the deviation sway parameter occurs.

[0157] S55: Obtain the interval duration based on the current image information and the deviation period.

[0158] The interval duration refers to the length of time between the current image information time period and the deviation time period. The interval duration is obtained by analyzing the current image information time period and the deviation time period. The method of interval duration analysis is common knowledge to those skilled in the art and will not be elaborated here.

[0159] S56: The degree of damage is obtained by using the interval duration, deviation swaying parameters, and historical environmental information.

[0160] The degree of damage refers to the extent of damage to the obstacle trees. The degree of damage is determined by matching the deviation swaying parameters, interval duration, and historical environmental information from a preset tree reference table.

[0161] The tree reference table stores the degree of damage corresponding to different deviation sway parameters, interval durations, and historical environmental information. The larger the deviation sway parameter, the greater the degree of damage to the obstacle tree during the initial shooting. The longer the interval duration, the greater the degree of damage to the obstacle tree under the influence of historical environmental information. The parameters in the tree reference table are set in advance by those skilled in the art based on actual conditions through experiments, and will not be elaborated here.

[0162] S57: Based on the degree of damage and the labeled control parameters, the swaying control parameters are obtained.

[0163] A new swaying parameter is obtained by matching the degree of damage with the swaying parameter in the marked control parameter, and the marked control parameter is updated with the new swaying parameter. The updated marked control parameter is then used as the swaying control parameter.

[0164] The tree reference table also stores new swaying parameters corresponding to different degrees of damage. Assuming the tree remains unchanged, the greater the degree of damage, the greater the swaying parameter, which will not be elaborated here.

[0165] The methods for updating correction values ​​include:

[0166] S60: Obtain the avoidance sway parameters by comparing the avoidance time point with the swaying comparison parameters.

[0167] The avoidance swaying parameter refers to the parameter that the obstacle tree sways at the avoidance time point. The avoidance swaying parameter is matched from the swaying reference parameter by the avoidance time point.

[0168] S61: Obtain the occlusion parameters within the avoidance distance based on the avoidance sway parameters and obstacle tree parameters.

[0169] The occlusion parameter refers to the parameter that the obstacle tree blocks the signal transmission between the relay drone and the partial discharge drone within the avoidance distance. By simulating and analyzing the avoidance swaying parameter and the obstacle tree parameter, the amount of tree leaves and the thickness of the tree within the signal transmission range between the relay drone and the partial discharge drone are used as the occlusion parameter.

[0170] S62: Obtain the occlusion correction coefficient through the occlusion parameters.

[0171] The occlusion correction factor is a coefficient that measures the degree of influence of occlusion parameters on signal attenuation. The occlusion correction factor is matched to the tree lookup table using the occlusion parameters. The tree lookup table also stores occlusion correction factors corresponding to different occlusion parameters; the larger the occlusion parameter, the larger the occlusion correction factor, which will not be elaborated upon here.

[0172] S63: The correction value is obtained based on the clearance distance, sensor specifications, and occlusion correction coefficient.

[0173] The initial correction value is obtained by matching the avoidance distance and sensor specifications from a preset transmission lookup table, and then the product of the initial correction value and the occlusion correction coefficient is calculated as the correction value.

[0174] The transmission reference table stores the initial correction values ​​corresponding to different clearance distances and sensor specifications. When the sensor specifications remain unchanged, the larger the clearance distance, the larger the initial correction value. The parameters in the transmission reference table are set in advance by those skilled in the art based on actual conditions, and will not be elaborated here.

[0175] Methods for controlling relay drones after they have commenced flight include:

[0176] S70: Collects the detection power of relay drones and preset partial discharge drones.

[0177] The detected battery level refers to the battery level of a relay drone or a partial discharge drone, which is obtained by retrieving the detected battery level from the battery system of the relay drone or the partial discharge drone.

[0178] S71: The operating power is obtained based on the transfer path and the partial discharge detection path.

[0179] Operating power refers to the amount of electricity required to complete the flight tests of the transfer path and the partial discharge detection path. The operating power is obtained by analyzing the transfer path and the partial discharge detection path. The method of operating power analysis is common knowledge to those skilled in the art and will not be elaborated here.

[0180] S72: Compare the detected power level with the operating power level to determine if the power level exceeds the limit, and select between the transfer path and the partial discharge detection path to obtain an auxiliary charging path.

[0181] A charging device is a vehicle equipped with a battery. The charging device includes a battery, a solar panel, a reflector, and a robotic arm for controlling the angle and position of the reflector.

[0182] The auxiliary charging path refers to the path along which the charging device follows the drone. By analyzing the difference between the detected power and the operating power, if the detected power exceeds the operating power, it means that both the relay drone and the partial discharge drone can complete the flight detection operation, and the charging device will not be dispatched.

[0183] If the detected battery level does not exceed the operating battery level, it indicates that the relay drone or partial discharge drone cannot complete the flight detection operation. In this case, an auxiliary charging path is obtained by analyzing the relay path and the partial discharge detection path. The analysis method for the auxiliary charging path is common knowledge to those skilled in the art and will not be elaborated here.

[0184] S73: Control the preset charging device to assist the operation of the charging path.

[0185] The control charging device assists in the operation of the charging path when the partial discharge UAV is conducting flight testing.

[0186] Methods for controlling the operation of the charging path include:

[0187] S80: Collects information on the charging location, charging time, and corresponding environmental information of the charging device.

[0188] The charging position refers to the real-time position of the charging device, which is determined by the parameters detected by the position sensor on the charging device.

[0189] The charging time point refers to the real-time operating time point of the charging device. When the charging device is running, the charging time point corresponding to different charging devices is recorded as the charging time point.

[0190] Environmental information refers to the surrounding environment of the charging location. This information is obtained by detecting the environment at the charging location using corresponding sensors and devices. Environmental information includes details about surrounding buildings, trees, and the sun's influence.

[0191] S81: Combine the charging location and charging time to retrieve solar irradiance information from the detection environment information.

[0192] Solar illumination information refers to parameters such as the solar altitude angle and azimuth angle at the charging location and charging time. This information is obtained by retrieving the solar altitude angle and azimuth angle corresponding to the charging location and charging time from the detection environment information.

[0193] S82: Obtain the shadow range by combining solar illumination information with environmental detection information.

[0194] The shadow range refers to the range of shadows cast by the detection environment information under sunlight. The shadow range is obtained by analyzing the sunlight information and the detection environment information. The method of shadow range analysis is common knowledge to those skilled in the art and will not be elaborated here.

[0195] S83: Update the shadow range based on solar illumination information, relay path, and partial discharge detection path.

[0196] A new shadow range is obtained by adding the shadows of the relay drones and partial discharge drones corresponding to the relay path and partial discharge detection path under the sun to the shadow range.

[0197] S84: Compare the shadow range with the preset charge range to obtain the shadow occlusion range.

[0198] The charging range is the area of ​​the solar panels on the charging device as defined by the technicians. The shading range refers to the area of ​​the solar panels that are shaded. The overlapping area between the shading range and the charging range is used as the shading range.

[0199] S85: The reflection parameters are obtained based on the shadow occlusion range and solar illumination information.

[0200] Reflection parameters refer to the position and angle of the reflector when sunlight is reflected into the shaded area. These parameters are obtained by analyzing the shaded area and solar illumination information. The methods for analyzing reflection parameters are common knowledge to those skilled in the art and will not be elaborated upon here.

[0201] S86: Update reflection parameters by shadow range and reflect the sun with reflection parameters.

[0202] The new reflection parameter is selected from the various reflection parameters that are not obscured by the shadow range and consume the least energy to control the reflection plate. The reflection plate on the charging device is then controlled to operate with the new reflection parameter to refract the sun into the shadow range.

[0203] In this embodiment, if a reflector cannot completely illuminate the shaded area with the reflected sunlight, the reflector parameter that can reflect the largest area within the shaded area and consumes the least energy to control the reflector is selected from the various reflector parameters as the new reflector parameter.

[0204] Methods for verifying reflection parameters include:

[0205] S90: Acquires image information of the surrounding area at the charging location.

[0206] The surrounding image information is obtained by capturing images of the area around the charging location using a camera pre-installed on the charging device.

[0207] S91: Obtain the operating range through reflection parameters.

[0208] The operating range refers to the space occupied by the reflector and the robotic arm when the reflector is running at the reflective parameters. The operating range is obtained by analyzing the reflective parameters. Different reflective parameters have different operating ranges. The method for analyzing the operating range is common knowledge to those skilled in the art and will not be elaborated here.

[0209] S92: Identify the range of marked obstacles within the operating range from surrounding image information.

[0210] The marked obstacle range refers to the spatial range occupied by obstacles within the operating range. Obstacles within the operating range are identified by analyzing surrounding image information, and the spatial area of ​​the obstacles within the operating range is used as the marked obstacle range.

[0211] S93: Update reflection parameters by marking obstacle ranges.

[0212] The new reflection parameter is selected from the operating range of the reflection parameters, and the one that does not overlap with the range of the marked obstacle and consumes the least energy to control the change of the reflector is selected as the new reflection parameter.

[0213] Based on the same inventive concept, embodiments of the present invention provide a sensor access system for the Internet of Things, comprising:

[0214] The acquisition module is used to acquire detection specifications, sensor specifications, reference signal range, image detection information, surrounding environment information, detection power, charging location, charging time point, detection environment information, and surrounding image information.

[0215] A memory for storing the program of the sensor access method for the Internet of Things;

[0216] The processor is used to load and execute programs stored in memory.

[0217] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0218] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A sensor access method of Internet of Things, characterized in that, The method comprises the following steps: S10: collecting a detection specification and a sensor specification; S11: calling a partial discharge detection position from the detection specification; S12: generating a partial discharge detection path through the partial discharge detection position; S13: collecting a reference signal range based on the partial discharge detection path; S14: obtaining a marking position through the detection specification and the sensor specification; S15: obtaining a deviation position and a deviation distance according to whether the marking position falls within the reference signal range; S16: calling a transfer number according to the deviation distance, and controlling a preset transfer unmanned aerial vehicle to fly to the transfer number and the deviation position. The method before controlling the transfer unmanned aerial vehicle to fly to the transfer number and the deviation position comprises the following steps: S20: obtaining a transfer path through the deviation position and the partial discharge detection path; S21: collecting image detection information of the transfer path; S22: updating the transfer path based on the image detection information; S23: obtaining an avoidance path according to the transfer path before and after the update; S24: calling an avoidance distance and an avoidance time point from the avoidance path; S25: obtaining a correction value according to the avoidance distance, the sensor specification and the image detection information, and outputting the correction value at the avoidance time point when the transfer unmanned aerial vehicle flies along the transfer path. 2.The sensor access method of Internet of Things according to claim 1, characterized in that, The method for updating the transfer path comprises the following steps: S30: collecting surrounding environment information of the transfer path; S31: obtaining a transfer specification through the transfer number; S32: calling a reference safety range from the transfer specification; S33: obtaining an obstacle range by combining the image detection information, the surrounding environment information and the reference safety range; S34: obtaining a minimum lateral distance according to the transfer path and the obstacle range; S35: obtaining a marking lateral position based on the lateral distance and the transfer path; S36: selecting to update the transfer path or to update the lateral distance according to whether the marking lateral position falls within the reference signal range; S37: updating the transfer path through the updated lateral distance. 3.The sensor access method of Internet of Things according to claim 2, wherein, The method for determining the obstacle range comprises the following steps: S40: calling historical image information and current image information from the image detection information, and calling historical environment information and current environment information from the surrounding environment information; S41: identifying an obstacle tree type through the current image information; S42: calling an obstacle tree parameter according to the obstacle tree type and the historical image information; S43: obtaining a swaying contrast parameter according to the obstacle tree parameter and the historical environment information; S44: obtaining a current swaying range based on the current environment information and the swaying contrast parameter, and defining the current swaying range as the obstacle range.

4. The sensor access method of an Internet of Things according to claim 3, wherein, The method for determining the swaying contrast parameter comprises the following steps: S50: obtaining a marking contrast parameter through the obstacle tree parameter and the historical environment information; S51: obtaining a historical time period based on the historical image information; S52: calling a reference swaying parameter from the marking contrast parameter through the historical time period and the historical environment information; S53: obtaining a historical swaying parameter by combining the historical time period and the historical image information; S54: comparing the historical swaying parameter and the reference swaying parameter to obtain a deviation swaying parameter and a deviation time period; S55: obtaining an interval length according to the current image information and the deviation time period. S56: obtaining the damage degree by the interval duration, the deviation sway parameter and the historical environment information; S57: obtaining the sway control parameter based on the damage degree and the marker control parameter.

5. The sensor access method of an Internet of Things according to claim 4, wherein, The updating method of the correction value comprises: S60: obtaining the avoidance sway parameter by the avoidance time point and the sway control parameter; S61: obtaining the shelter parameter in the avoidance distance based on the avoidance sway parameter and the obstacle tree parameter; S62: obtaining the shelter correction coefficient by the shelter parameter; S63: obtaining the correction value according to the avoidance distance, the sensor specification and the shelter correction coefficient.

6. The sensor access method of an Internet of Things according to claim 5, wherein, The method for controlling the transfer unmanned aerial vehicle to fly after comprises: S70: obtaining the detection power of the transfer unmanned aerial vehicle and the preset local placement unmanned aerial vehicle; S71: obtaining the running power according to the transfer path and the local placement detection path; S72: comparing the exceeding condition of the detection power and the running power to select the auxiliary charging path through the transfer path and the local placement detection path; S73: controlling the preset charging device to run in the auxiliary charging path.

7. The sensor access method of an Internet of Things according to claim 6, wherein, The method for controlling the auxiliary charging path to run comprises: S80: collecting the charging position, the charging time point and the detection environment information corresponding to the charging position of the charging device; S81: combining the charging position and the charging time point to retrieve the solar radiation information from the detection environment information; S82: obtaining the shadow range by the solar radiation information and the detection environment information; S83: updating the shadow range based on the solar radiation information, the transfer path and the local placement detection path; S84: comparing the shadow range with the preset charging range to obtain the shadow shelter range; S85: obtaining the reflection parameter according to the shadow shelter range and the solar radiation information; S86: updating the reflection parameter by the shadow range, and reflecting the sun by the reflection parameter.

8. The sensor access method of an Internet of Things according to claim 7, wherein, The verification method of the reflection parameter comprises: S90: collecting the surrounding image information of the charging position; S91: obtaining the running range by the reflection parameter; S92: identifying the marker obstacle range in the running range from the surrounding image information; S93: updating the reflection parameter by the marker obstacle range.

9. A sensor access system for the Internet of Things, characterized in that The method comprises: The acquisition module is configured to acquire the detection specification, the sensor specification and the reference signal range; The memory is configured to store a program for implementing the sensor access method of the Internet of Things according to any one of claims 1 to 8; The processor is configured to load and execute the program stored in the memory.

Images