Intelligent height sensing device
Through the intelligent height sensing device, the height sensor and gyroscope are used to monitor and adjust the height and inclination angle of the ground wire in real time, solving the problem of unreliable connection of the ground wire in the substation and ensuring the safety of staff.
Patent Information
- Application Number
- CN202411290149.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-14
- Publication Date
- 2024-12-13
AI Technical Summary
In the substation room, it is difficult for the existing technology to realize real-time monitoring and adjustment of the height and inclination angle of the ground wire hooking, resulting in unreliable hooking, which may cause the ground wire to fail in storm weather, threatening the safety of staff.
Design an intelligent height sensing device, including a height sensor, gyroscope and microcontroller, automatically calculates the height and inclination angle of the ground wire, and performs posture correction when the inclination angle exceeds the preset value, using Kalman filtering algorithm or Complementary filtering algorithm improves calculation accuracy and stability, ensuring the level of the ground wire and the initial plane.
Accurate monitoring and adjustment of the height and inclination angle of the ground wire are achieved, ensuring the reliability of the ground wire connection and the safety of staff.
Smart Images
Figure CN119124101A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of intelligent sensing, and in particular relates to an intelligent height sensing device. Background Art
[0002] Power operation safety is the foundation and focus of daily work. In order to ensure the safety of construction operations and avoid safety accidents such as going to the wrong interval, it is urgent to perform sub-meter positioning of operators and equipment. The indoor environment of the substation is complex, and the distribution cabinets and substation equipment are all made of metal. There is serious multipath interference. At the same time, the power supply safety inside the substation requires that the mounting technology has high security. However, the existing mounting technology is difficult to achieve positioning accuracy and data security that meet the operational requirements in this environment.
[0003] Among them, real-time monitoring of the height and inclination angle of the grounding wire is particularly important. However, the existing technology rarely involves real-time monitoring and adjustment of the height and inclination angle. Once the inclination angle of the grounding wire is too large, the grounding wire will not be securely hung. In stormy weather, the grounding wire may fail to hang, posing a threat to the safety of the staff. Summary of the invention
[0004] In view of the defects existing in the prior art, the purpose of the present invention is to provide an intelligent height sensing device, which uses a height sensor and a gyroscope to locate the current height and inclination angle of the grounding wire, ensure the initial plane level of the grounding wire, ensure the successful hanging of the grounding wire, and ensure the safety of the staff.
[0005] To achieve the above purpose, the technical solution adopted by the present invention is: an intelligent height sensing device, which is arranged on the grounding wire of the intelligent short-circuit grounding device. When the grounding wire is hung on the electric wire, the device automatically calculates the height and inclination angle of the current position of the grounding wire, and corrects the posture of the grounding wire when the inclination angle exceeds a preset value. The device includes a height sensor, a gyroscope, a microcontroller and a data sensor. The height sensor is used to detect the height of the grounding wire, the gyroscope is used to detect the inclination angle of the grounding wire relative to an initial plane, the data sensor is used to collect detection data output by the height sensor and the gyroscope, and transmit the collected detection data to the microcontroller. The microcontroller processes the detection data transmitted by the data sensor and transmits the processing results back to the host.
[0006] Furthermore, the altitude sensor is a differential pressure sensor, which measures the change in atmospheric pressure and calculates the altitude of the grounding line in combination with the standard atmospheric pressure at sea level.
[0007] Furthermore, the device also includes a collar and a control panel, the collar is connected to a ground wire, and the height sensor, the gyroscope, the microcontroller and the data sensor are all arranged on the control panel.
[0008] Furthermore, the gyroscope uses a Kalman filter algorithm or a complementary filter algorithm to calculate the ground wire posture.
[0009] Furthermore, the specific steps of the gyroscope using the Kalman filter algorithm to calculate the grounding line posture include:
[0010] S1. Perform initialization settings, set the initial state and error covariance matrix. The initial state includes the initial position and initial velocity parameters of the gyroscope, and the error covariance matrix describes the uncertainty of the initial estimate;
[0011] S2, predicting the state at the next moment according to the physical model, updating the error covariance matrix to predict the error covariance matrix, and the predicted error covariance matrix represents the uncertainty of the prediction;
[0012] S3, integrate detection data and update observations;
[0013] S4. Repeat steps S2 and S3, continue to process the data at each moment, and continuously optimize the system state estimation.
[0014] Furthermore, the physical model in step S2 is constructed based on the internal state and known system dynamics, and the state at the next moment includes the position and speed parameters at the next moment.
[0015] Further, in step S2, the following formula is used to predict the state at the next moment:
[0016]
[0017] in is the state prediction at time k, F k is the state transition matrix, is the optimal state estimate of the previous time k-1, B k is the control input matrix, μ k is the control input.
[0018] Further, in step S2, the following formula is used to predict the error covariance matrix:
[0019]
[0020] P k / k-1 is the prediction error covariance, P k-1 / k-1 is the optimal error covariance at the previous time, Q k is the process noise covariance matrix,
[0021] Further, step S3 includes obtaining observations by obtaining pressure difference data from the altitude sensor and obtaining current attitude and direction data from the gyroscope; updating observations by comparing the observed data with the predicted state and calculating the residual; calculating the Kalman gain by calculating the Kalman gain based on the prediction error covariance matrix and the observation noise; updating the state estimate by using the Kalman gain and adjusting the predicted state in combination with the residual to generate a current state estimate; and updating the error covariance by adjusting the error covariance.
[0022] Furthermore, when the device is started, the gyroscope collects initial angular velocity data, and the data is averaged within a short period of time to determine the initial plane of the device.
[0023] The beneficial technical effect of the present invention is that an intelligent height sensing device disclosed in the present invention detects the current height and inclination angle of the grounding wire through a gyroscope and a height sensor, transmits the data back and analyzes it through a microprocessor, and simultaneously corrects the posture of the grounding wire, thereby ensuring the accuracy of the data and the personal safety of the staff. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] Figure 1 is a structural schematic diagram of an intelligent height sensing device disclosed in an embodiment of the present invention;
[0025] Figure 2 is a structural schematic diagram of a control panel in an intelligent height sensing device disclosed in an embodiment of the present invention;
[0026] Wherein: 1-ring, 2-control panel, 21-first display light, 22-second display light; 23-gyroscope, 24-altitude sensor, 25-microcontroller. DETAILED DESCRIPTION
[0027] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments.
[0028] Embodiment 1
[0029] like Figure 1 As shown, an embodiment of the present invention provides an intelligent height sensing device, which is arranged on the grounding wire of an intelligent short-circuit grounding device. When the grounding wire on the intelligent short-circuit grounding device is hooked on the electric wire, the intelligent height sensing device automatically calculates the height and inclination angle of the current position of the grounding wire of the intelligent short-circuit grounding device, and corrects the posture of the grounding wire when the inclination angle exceeds a preset value.
[0030] The device comprises a collar 1 and a control panel 2. The collar 1 is installed on the grounding wire of the intelligent short-circuit grounding device. Figure 2As shown, a height sensor 24, a gyroscope 23, a microcontroller 25 and a data sensor are arranged on the control panel 2. Among them, the height sensor 24 is a differential pressure sensor, which calculates the height of the grounding wire by measuring the change of atmospheric pressure. The gyroscope 23 is used to detect the inclination angle of the grounding wire to determine the initial plane, and the data sensor is used to collect the data detected by the height sensor 24 and the gyroscope 23 and transmit it back to the host.
[0031] The altitude sensor 4 measures the current atmospheric pressure and calculates the current relative altitude of the grounding line in combination with the standard atmospheric pressure at sea level (1013.25 hPa).
[0032] The gyroscope 3 uses a three-axis gyroscope. During operation, the gyroscope 3 continuously collects three-axis angular velocity data, and uses the three-axis angular velocity data collected by the gyroscope to perform attitude calculation to ensure that the measurement direction of the device is consistent with the initial plane. At the same time, compensation can be performed in combination with the data of the accelerometer inside the gyroscope to ensure the accuracy of the tilt angle.
[0033] The gyroscope 3 uses a Kalman filter algorithm or a complementary filter algorithm to improve the accuracy and stability of the ground wire posture calculation.
[0034] The specific steps of using the Kalman filter algorithm to calculate the ground line posture of the gyroscope 3 include:
[0035] S1. Perform initialization settings.
[0036] Set the initial state and error covariance matrix. The initial state includes parameters such as the initial position and initial velocity of the gyroscope 3, and the error covariance matrix describes the uncertainty of the initial estimate.
[0037] S2, predicted states and error covariance.
[0038] Among them, the predicted state is the state (such as position and speed) predicted at the next moment based on the physical model. This step does not consider external observations and is only based on internal states and known system dynamics; the prediction error covariance is the update error covariance, which represents the uncertainty of the prediction.
[0039] The predicted state is calculated using the following formula:
[0040]
[0041] in is the state prediction at time k, F k is the state transition matrix, is the optimal state estimate of the previous time k-1, B k is the control input matrix, μ k is the control input.
[0042] The forecast error covariance is given by the following formula:
[0043]
[0044] P k / k-1 is the prediction error covariance, P k-1 / k-1 is the optimal error covariance at the previous time, Q k is the process noise covariance matrix.
[0045] S3: Fuse sensor data and update observations.
[0046] Among them, obtaining observations means obtaining pressure difference data from the pressure difference sensor and obtaining the current attitude and direction from the gyroscope. Observation update means comparing the observed data with the predicted state and calculating the residual. Kalman gain calculation means calculating the Kalman gain based on the prediction error covariance and observation noise. This value is used to determine the weight between the observed data and the model prediction. Updating the state estimate means using the Kalman gain and adjusting the predicted state in combination with the residual to generate a more accurate estimate of the current state. Updating the error covariance means adjusting the error covariance to reduce the uncertainty caused by the observation.
[0047] The Kalman gain is calculated using the following formula:
[0048]
[0049] K k is the Kalman gain, used to update the estimated accuracy, H k is the observation matrix, R k is the observation noise covariance.
[0050] The following formula is used to update the status:
[0051]
[0052] z k is the actual measured value at time k.
[0053] The error covariance is updated using the following formula:
[0054] P k / k =(IK k H k ) k / k-1
[0055] I is the identity matrix, which has the same size as the dimension of the state vector.
[0056] S4. Repeat steps S2 and S3, continue to process the data at each moment, and continuously optimize the system state estimation.
[0057] Several display lights are provided on the device, and the display lights are used to indicate the working state of the power supply and the connection state of the microcontroller 5. Specifically, a first display light 21 and a second display light 22 are provided on the control panel 2. The first display light 21 is used to indicate whether the power supply of the device is working normally, and the second display light 22 is used to indicate whether the microcontroller 25 on the control panel 2 is connected to the background host normally.
[0058] When the power is turned on and works normally, the first display light 21 lights up normally and remains on. When the microcontroller 25 is connected to the background host normally, the second display light 22 lights up normally and remains on.
[0059] When the indicator light on the height sensor 24 is on, the device starts, and firstly collects the initial three-axis angular velocity data through the gyroscope 23, averages the data in a short time, and determines the initial plane of the device.
[0060] The height sensor 24 and the gyroscope 23 transmit the detection data back to the microcontroller 25 through the data sensor, and the microcontroller 25 processes the detection data transmitted by the data sensor.
[0061] The microcontroller 25 records and transmits the detection data in real time, and transmits the detection data to the host computer for further analysis.
[0062] The host displays the grounding line height information in real time, and the staff corrects the grounding line attitude according to the detection data output by the gyroscope 23.
[0063] When in use, the ring 21 is installed on the grounding wire used, the control panel 2 is opened, and the grounding wire is hung on the electric wire. Then, the height sensor 24 and the three-axis gyroscope 23 on the control panel 2 collect data and correct the posture of the grounding wire.
[0064] When the power of the control panel 2 is turned on and working normally, the first display light 21 lights up normally and remains on. When the microcontroller 25 on the control panel 2 is connected to the background host normally, the second display light 22 lights up normally and remains on. After the grounding wire is successfully connected, the three-axis gyroscope 23 and the height sensor 24 in the control panel 2 start to work normally and detect data. The three-axis gyroscope 23 can rotate and tilt in three dimensions, further collect initial three-axis angular velocity data, average the data in a short time, and determine the initial plane of the device. The detection data of the three-axis gyroscope 23 can be improved in accuracy and stability by Kalman filtering or complementary filtering algorithm. The height sensor 24 measures the current atmospheric pressure and combines the standard atmospheric pressure at sea level (1013.25hPa) to calculate the relative height of the grounding wire. After the data detection is completed, the device can perform attitude correction. During operation, the gyroscope 23 continuously collects three-axis angular velocity data, and uses the data of the gyroscope 23 to perform attitude calculation to ensure that the measurement direction is consistent with the initial plane. The detected data is further processed by the microcontroller 25 and transmitted to a host computer for further analysis.
[0065] It can be seen from the above embodiments that the intelligent height sensing device disclosed in the present invention locates the current height and inclination angle of the grounding wire through a height sensor and a gyroscope, and adjusts the grounding wire according to the detection result to ensure that the grounding wire is level with the initial plane, laying the foundation for the successful hanging of the grounding wire, ensuring the reliability of the hanging of the grounding wire, and ensuring the safety of the staff.
[0066] The device described in the present invention is not limited to the embodiments described in the specific implementation manner. Those skilled in the art may derive other implementation manners based on the technical solution of the present invention, which also fall within the technical innovation scope of the present invention.
Claims
1. An intelligent height sensing device, characterized in that: The device is arranged on the grounding wire of the intelligent short-circuit grounding device. When the grounding wire is hooked to the electric wire, the device automatically calculates the height and inclination angle of the current position of the grounding wire, and corrects the posture of the grounding wire when the inclination angle exceeds a preset value. The device includes a height sensor, a gyroscope, a microcontroller and a data sensor. The height sensor is used to detect the height of the grounding wire, the gyroscope is used to detect the inclination angle of the grounding wire relative to an initial plane, the data sensor is used to collect detection data output by the height sensor and the gyroscope, and transmit the collected detection data to the microcontroller. The microcontroller processes the detection data transmitted by the data sensor, and transmits the processing result back to the host.
2. An intelligent height sensing device as claimed in claim 1, characterized in that: The altitude sensor is a differential pressure sensor, which measures the change of atmospheric pressure and calculates the altitude of the grounding line in combination with the standard atmospheric pressure at sea level.
3. An intelligent height sensing device as claimed in claim 1, characterized in that: The device further comprises a collar and a control panel, wherein the collar is connected to a ground wire, and the height sensor, the gyroscope, the microcontroller and the data sensor are all arranged on the control panel.
4. An intelligent height sensing device as claimed in claim 3, characterized in that: The gyroscope uses a Kalman filter algorithm or a complementary filter algorithm to calculate the ground line posture.
5. An intelligent height sensing device as claimed in claim 4, characterized in that: The specific steps of using the Kalman filter algorithm to calculate the ground line posture by the gyroscope include: S1. Perform initialization settings, set the initial state and error covariance matrix. The initial state includes the initial position and initial velocity parameters of the gyroscope, and the error covariance matrix describes the uncertainty of the initial estimate; S2, predicting the state at the next moment according to the physical model, updating the error covariance matrix to predict the error covariance matrix, and the predicted error covariance matrix represents the uncertainty of the prediction; S3, integrate detection data and update observations; S4. Repeat steps S2 and S3, continue to process the data at each moment, and continuously optimize the system state estimation.
6. An intelligent height sensing device as claimed in claim 5, characterized in that: In step S2, the physical model is constructed based on the internal state and known system dynamics, and the state at the next moment includes the position and speed parameters at the next moment.
7. An intelligent height sensing device as claimed in claim 5, characterized in that: In step S2, the following formula is used to predict the state at the next moment: in is the state prediction at time k, F k is the state transition matrix, is the optimal state estimate of the previous time k-1, B k is the control input matrix, μ k is the control input.
8. An intelligent height sensing device as claimed in claim 5, characterized in that: In step S2, the following formula is used to predict the error covariance matrix: P k / k-1 is the prediction error covariance, P k-1 / k-1 is the optimal error covariance at the previous time, Q k is the process noise covariance matrix, 9. An intelligent height sensing device as claimed in claim 8, characterized in that: Step S3 includes obtaining observations, namely obtaining pressure difference data from the altitude sensor and obtaining current attitude and direction data from the gyroscope; updating observations, namely comparing the observed data with the predicted state and calculating the residual; calculating the Kalman gain based on the predicted error covariance matrix and the observation noise, calculating the Kalman gain; updating the state estimate, namely using the Kalman gain and adjusting the predicted state in combination with the residual to generate a current state estimate; and updating the error covariance, namely adjusting the error covariance.
10. The intelligent height sensing device according to claim 1, characterized in that: When the device is started, the gyroscope collects initial angular velocity data, and the data is averaged over a short period of time to determine the initial plane of the device.