Multi-source data fusion wire state monitoring method and system

Abstract

The invention discloses a multi-source data fusion wire state monitoring method and system. The method comprises the following steps: acquiring first monitoring data, and presetting a first positioning algorithm and a second positioning algorithm; based on the first monitoring data, obtaining a first positioning result through a first positioning algorithm, and obtaining a second positioning result through a second positioning algorithm; and performing first joint operation on the first positioning result and the second positioning result, and performing primary wire state monitoring according to the first joint operation result. By fusing monitoring results of different positioning algorithms, the accuracy and reliability of monitoring are improved. And the system can meet monitoring requirements under different environmental conditions, and can provide an effective monitoring solution for high mountains, remote areas and complex terrains.

Description

Technical Field

[0001] The present invention relates to the technical field of multi-source data fusion conductor state monitoring, and in particular to a multi-source data fusion conductor state monitoring method and system. Background Art

[0002] Line galloping (also known as conductor galloping) is a periodic vibration phenomenon that occurs when high-voltage transmission lines are affected by external environments such as wind and ice. This phenomenon not only causes mechanical damage to the power transmission system, but may also cause serious faults such as power outages and short circuits. In order to effectively monitor and prevent line galloping, accurate conductor position and posture data are crucial.

[0003] RTK (Real-time Kinematic Positioning) technology uses differential signals provided by ground reference stations to achieve centimeter-level high-precision positioning, which is suitable for measurements within a short baseline range. This high-precision and low-latency feature is very suitable for real-time monitoring of small displacements and vibrations of the line. However, RTK technology relies on the signal coverage of ground reference stations, and its measurement accuracy decreases as the baseline length increases. In addition, in high mountains, remote areas or complex terrain, RTK signals may be interfered by occlusion or multipath effects, affecting positioning accuracy and reliability.

[0004] PPP (Precise Point Positioning) technology can achieve high-precision positioning on a global scale through the precise orbit and clock correction information provided by the Global Navigation Satellite System (GNSS). PPP does not rely on ground reference stations and is suitable for long-baseline and even global positioning, especially in remote areas far away from base stations. It can alleviate the accuracy loss caused by short-term occlusion to a certain extent. The multi-band and long-baseline characteristics of PPP can also help reduce the errors caused by occlusion. Although PPP has the ability to cover the world, its initial positioning time is long (usually takes several minutes to tens of minutes), and its accuracy is limited by the signal quality of the satellite. Especially in high-dynamic environments, the positioning accuracy and real-time performance are weaker than RTK. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed.

[0007] Therefore, the present invention provides a multi-source data fusion conductor state monitoring method and system, which can solve the problems mentioned in the background technology.

[0008] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides a multi-source data fusion conductor state monitoring method, comprising:

[0010] Acquire first monitoring data, and preset a first positioning algorithm and a second positioning algorithm;

[0011] Based on the first monitoring data, obtaining a first positioning result by using the first positioning algorithm, and obtaining a second positioning result by using the second positioning algorithm;

[0012] A first joint operation is performed on the first positioning result and the second positioning result, and a wire status monitoring is performed according to the first joint operation result.

[0013] As a preferred solution of the multi-source data fusion conductor state monitoring method of the present invention, it also includes:

[0014] Update the first positioning algorithm and the second positioning algorithm according to the primary conductor state monitoring result;

[0015] and performing secondary wire status monitoring according to the updated first positioning algorithm and the second positioning algorithm;

[0016] Repeat the wire status monitoring several times.

[0017] As a preferred solution of the multi-source data fusion conductor state monitoring method of the present invention, wherein: the conductor state monitoring is performed several times by performing a first joint operation to obtain a first joint operation result, and performing corresponding conductor state monitoring.

[0018] As a preferred solution of the multi-source data fusion conductor state monitoring method of the present invention, the first positioning result and the second positioning result both include at least two indicators: positioning coordinates and measurement speed.

[0019] As a preferred solution of the multi-source data fusion conductor state monitoring method of the present invention, wherein: obtaining the first positioning result by the first positioning algorithm and obtaining the second positioning result by the second positioning algorithm include:

[0020] Setting a first priori probability matrix and a second priori probability matrix based on the first positioning algorithm and the second positioning algorithm;

[0021] A first weight matrix and a second weight matrix are calculated based on the first prior probability matrix and the second prior probability matrix.

[0022] As a preferred solution of the multi-source data fusion conductor state monitoring method of the present invention, wherein: the conductor state monitoring according to the first joint operation result comprises:

[0023] Calculate the posture change of the wire dancing according to the first joint operation result;

[0024] Convert the dancing posture changes of the wire into the inertial coordinate system.

[0025] As a preferred solution of the multi-source data fusion conductor state monitoring method of the present invention, wherein: the conducting conductor state monitoring according to the first combined operation result further comprises:

[0026] The velocity of the wire dancing monitoring module is obtained by integrating the posture change in the inertial coordinate system.

[0027] The position of the wire dancing monitoring module is obtained by integrating the posture change in the inertial coordinate system twice.

[0028] In a second aspect, the present invention provides a multi-source data fusion conductor state monitoring system, comprising:

[0029] A prediction operation module, used for acquiring first monitoring data, and presetting a first positioning algorithm and a second positioning algorithm;

[0030] A positioning result determination module, configured to obtain a first positioning result through the first positioning algorithm based on the first monitoring data, and obtain a second positioning result through the second positioning algorithm;

[0031] The monitoring module is used to perform a first joint operation on the first positioning result and the second positioning result, and perform a wire status monitoring according to the first joint operation result.

[0032] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0033] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described above when executed by a processor.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention proposes a multi-source data fusion conductor state monitoring method and system, obtains the first monitoring data, and presets the first positioning algorithm and the second positioning algorithm; based on the first monitoring data, obtains the first positioning result through the first positioning algorithm, and obtains the second positioning result through the second positioning algorithm; performs a first joint operation on the first positioning result and the second positioning result, and performs a conductor state monitoring according to the first joint operation result. By fusing the monitoring results of different positioning algorithms, the accuracy and reliability of monitoring are improved. Specifically, by jointly operating the first positioning result and the second positioning result, the actual state of the conductor can be more comprehensively reflected, thereby providing more accurate data support for the monitoring of line dancing. In addition, by continuously updating the positioning algorithm and repeating the conductor state monitoring, the changes in the conductor state can be tracked in real time, potential fault risks can be discovered in time, and the stable operation of the power system can be guaranteed. At the same time, the present invention can also adapt to the monitoring needs under different environmental conditions, whether it is high mountains, remote areas or complex terrain, it can provide an effective monitoring solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0036] Figure 1 A method flow chart of a multi-source data fusion conductor status monitoring method and system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0038] Example 1

[0039] Reference Figure 1 , which is the first embodiment of the present invention, provides a multi-source data fusion conductor state monitoring method and system, including:

[0040] There are some problems in the existing related technologies. For example, traditional wire condition monitoring methods often rely on a single data source, which makes the monitoring results incomplete and easily affected by environmental changes and equipment failures. In addition, due to the lack of an effective data fusion mechanism, these methods often cannot provide accurate and timely monitoring information when dealing with changing external conditions.

[0041] The present application provides a method that can effectively solve the above-mentioned problems. Next, how to implement the multi-source data fusion wire status monitoring method will be described in detail in combination with multiple embodiments.

[0042] Figure 1 A method flow chart of a multi-source data fusion conductor state monitoring method and system is shown, including:

[0043] S100: Acquire first monitoring data, and preset a first positioning algorithm and a second positioning algorithm;

[0044] In an optional embodiment, the first monitoring data may be temperature data from a conductor temperature sensor, which reflects the temperature change of the conductor during operation. By analyzing the temperature data, abnormal conditions such as conductor overheating can be discovered in time, thereby preventing potential failures.

[0045] In an optional embodiment, the first monitoring data may also be vibration data from a conductor vibration sensor, which can reflect the vibration state of the conductor during operation. Analysis of vibration data helps detect problems such as mechanical wear, looseness or breakage of the conductor. By combining temperature data and vibration data, the health of the conductor can be more comprehensively evaluated, thereby improving the accuracy and reliability of monitoring.

[0046] In an optional embodiment, the first monitoring data may be tension data from a wire tension sensor, which reflects the tension change of the wire under different loads and environmental conditions. By analyzing the tension data, it is possible to monitor whether the wire is subjected to a pulling force beyond its design range, thereby preventing wire breakage or loosening caused by excessive tension.

[0047] It should be noted that the combination of temperature, vibration and tension data can provide a more accurate assessment of the comprehensive condition of the conductor and provide a scientific basis for maintenance decisions.

[0048] In an optional embodiment, the first monitoring data may be other types of data besides temperature, vibration and tension data, such as current data. The current data may reflect the current load of the wire, and by monitoring the change of the current, the overload problem of the wire may be discovered in time to prevent the wire from overheating or fusing due to excessive current.

[0049] It should be noted that the analysis of current data can also assist in determining the contact quality of the conductor connection points, thereby ensuring the stable operation of the power system. By integrating these multi-source data, the monitoring system can provide a more comprehensive and in-depth analysis of the conductor status, providing a strong guarantee for the safe operation of the power system.

[0050] In the embodiment of the present application, the first monitoring data is not limited, and any type of data mentioned above can be used to implement the final wire state monitoring through the method of the present application;

[0051] In an optional embodiment, the first positioning algorithm or the second positioning algorithm can be a positioning technology based on GPS, which is used to determine the precise position of the conductor in geographic space. Through GPS technology, the movement and position change of the conductor can be tracked in real time, which is particularly important for outdoor power transmission lines because they may be affected by weather and environmental factors and move.

[0052] In an optional embodiment, the first positioning algorithm or the second positioning algorithm can be a positioning technology based on a wireless sensor network, which monitors the wire status through multiple sensor nodes deployed along the wire. These sensor nodes can collect data such as wire vibration, temperature, and tension, and send the data to a central processing unit through wireless communication. By analyzing these data, the health status of the wire can be evaluated and potential problems can be discovered in a timely manner.

[0053] In an optional embodiment, the first positioning algorithm and the second positioning algorithm can be two positioning methods, such as RTK (real-time kinematic positioning) and PPP (precision point positioning). These positioning methods can provide high-precision positioning services, which are particularly suitable for occasions that require high-precision positioning information.

[0054] In the embodiment of the present application, the first positioning algorithm uses RTK (real-time dynamic positioning), and the second positioning algorithm uses PPP (precision point positioning). RTK technology can provide centimeter-level positioning accuracy in real time by using a fixed base station and one or more mobile stations. PPP technology does not require a ground base station, and high-precision positioning can be achieved worldwide through a single receiver. Although its initialization time is long, the positioning accuracy can also reach the centimeter level. The combination of these two technologies can provide a more flexible and accurate positioning solution for wire status monitoring.

[0055] It should be noted that obtaining the first monitoring data and presetting the first positioning algorithm and the second positioning algorithm can achieve real-time monitoring and rapid response to the conductor status. The first monitoring data usually contains the physical location information of the conductor, and the combined use of the first positioning algorithm and the second positioning algorithm can ensure that accurate positioning information can be obtained under different environments and conditions. This not only improves the reliability of the monitoring system, but also enhances the early warning capability of abnormal conductor conditions. In addition, this data fusion method can also reduce dependence on a single data source and reduce the risks caused by data source failures or errors. Through the comprehensive analysis of multi-source data, the health status of the conductor can be more comprehensively evaluated, providing a scientific basis for maintenance decisions.

[0056] S200: Based on the first monitoring data, obtain a first positioning result by using a first positioning algorithm, and obtain a second positioning result by using a second positioning algorithm;

[0057] In the embodiment of the present application, obtaining a first positioning result by using a first positioning algorithm, and obtaining a second positioning result by using a second positioning algorithm includes:

[0058] Setting a first priori probability matrix and a second priori probability matrix based on the first positioning algorithm and the second positioning algorithm;

[0059] A first weight matrix and a second weight matrix are calculated based on the first prior probability matrix and the second prior probability matrix.

[0060] In the embodiment of the present application, the first positioning result and the second positioning result both include at least two indicators, namely, positioning coordinates and measurement speed. Relevant technicians can select corresponding indicators according to actual needs.

[0061] In an optional embodiment, the prior probability matrix can be constructed based on historical data and expert experience to describe the reliability of different positioning algorithms in different situations. For example, when the wire is in a specific environmental condition, the first positioning algorithm may be more accurate than the second positioning algorithm, and the prior probability value of the first positioning algorithm corresponding to the first prior probability matrix will be higher.

[0062] It should be noted that in this way, the weight matrix can be dynamically adjusted to make the final positioning result more accurate. In addition, the system can also dynamically update the prior probability matrix based on real-time data to adapt to environmental changes and the evolution of the wire state.

[0063] In an optional embodiment, the prior probability matrix can also be adjusted using weights to reflect the performance changes of different positioning algorithms under different times or conditions. For example, if the first positioning algorithm performs better at night or under certain weather conditions, then under these conditions, the weight of the corresponding first positioning algorithm in the first prior probability matrix can be increased accordingly.

[0064] It should be noted that in this way, the system can dynamically adjust the weights according to real-time data and environmental changes, thereby improving the accuracy and reliability of positioning.

[0065] In an optional embodiment, a machine learning algorithm may also be integrated to further optimize the calculation of the prior probability matrix and the weight matrix to ensure that the monitoring method and system can adapt to various complex and changing environments and conditions.

[0066] In the embodiment of the present application, the prior probability matrix P(H) of RTK and PPP is set RTK (k) ) and P(H PPP (k) ), P(H RTK (k) ) and P(H PPP (k) ) is a 6*6 diagonal matrix, k is the number of iterations, and the initial value of k is 0. Specifically:

[0067]

[0068]

[0069] Where i represents the dimension of the RTK measurement vector or the PPP measurement vector; when k = 0, p RTKii (k) represents the initial likelihood function of the RTK measurement vector in dimension i, represents the variance of the RTK measurement vector in dimension i, represents the error of the RTK measurement vector in dimension i, p PPPii (k) represents the likelihood function of the PPP measurement vector in dimension i, represents the variance of the PPP measurement vector in dimension i, Represents the error of the PPP measurement vector in dimension i. The RTK measurement vector and the PPP measurement vector include 3 coordinate dimensions and 3 velocity dimensions.

[0070] In an optional embodiment, the first weight matrix and the second weight matrix are calculated based on the first prior probability matrix and the second prior probability matrix. By fusing the RTK and PPP measurement data, a more accurate wire state estimation can be obtained. Specifically, the first weight matrix is ​​used to adjust the weight of the RTK measurement data, and the second weight matrix is ​​used to adjust the weight of the PPP measurement data.

[0071] In an optional embodiment, the weight matrix can be dynamically adjusted to meet different measurement accuracy requirements according to different measurement environments and conditions. For example, in open areas with less signal obstruction, the weight of RTK measurement data can be set higher, while in areas with severe signal obstruction such as urban canyons or dense forests, the weight of PPP measurement data may be given a greater proportion. In this way, the accuracy and reliability of wire status monitoring can be effectively improved.

[0072] In the embodiment of the present application, the specific steps of calculating the first weight matrix and the second weight matrix based on the first prior probability matrix and the second prior probability matrix are as follows:

[0073] According to the prior probability matrix P(H RTK (k) ) and P(H PPP (k) ) Calculate the PPP weight matrix W PPP (k) and the RTK weight matrix W RTK (k) , the PPP weight matrix and RTK weight matrix are 6*6 diagonal matrices,

[0074]

[0075]

[0076] in,

[0077]

[0078] It should be noted that based on the first monitoring data, the first positioning result is obtained by the first positioning algorithm, and the second positioning result is obtained by the second positioning algorithm, which improves the accuracy and reliability of positioning. The first monitoring data usually contains a variety of physical parameters of the conductor, such as temperature, tension, vibration, etc. These parameters can provide preliminary information on the state of the conductor. The first positioning algorithm may perform preliminary positioning calculations based on these physical parameters, while the second positioning algorithm may use other types of data, such as image recognition or sound analysis, to further refine the positioning results. By fusing the outputs of these two algorithms, the errors that may be caused by a single data source or algorithm can be effectively reduced, thereby achieving more accurate conductor state monitoring in a complex and changing environment.

[0079] S300: performing a first joint operation on the first positioning result and the second positioning result, and performing a wire status monitoring according to the first joint operation result.

[0080] In an optional embodiment, the first joint operation can be a weighted average method, in which the first positioning result and the second positioning result are assigned different weights according to their respective confidence levels. For example, if the first positioning algorithm is more reliable under certain conditions, then its result can be assigned a higher weight. In this way, the advantages of the two algorithms can be comprehensively considered to obtain more accurate wire status monitoring results. In addition, the joint operation can also include detection and processing of outliers to ensure that the final monitoring result will not have a large deviation due to the anomaly of a single data point.

[0081] In an optional embodiment, the first joint operation can also be a fusion strategy based on machine learning, which learns the best combination of different positioning results by training a fusion model. The fusion model can use a variety of machine learning algorithms, such as support vector machine (SVM), random forest or neural network. During the training process, the model uses historical data to learn how to adjust the weight distribution according to different environmental conditions and sensor data to achieve the best monitoring effect. In this way, the fusion model can dynamically adapt to environmental changes and improve the accuracy and robustness of wire status monitoring.

[0082] In an optional embodiment, the first joint operation can also be a fusion strategy based on deep learning, which uses deep neural networks to process and fuse data from different sensors. By building a deep learning model, automatic feature extraction and high-level abstraction of data can be achieved, thereby capturing complex patterns and associations in the data. The deep learning model can adopt structures such as convolutional neural networks (CNN), recurrent neural networks (RNN) or long short-term memory networks (LSTM) to adapt to different types of data and monitoring task requirements. During the training process, the model learns how to integrate information from different sensors through a large amount of monitoring data to improve the recognition accuracy and prediction ability of changes in wire status. This fusion strategy based on deep learning is capable of processing large-scale multi-source data and providing more stable and reliable monitoring results in complex environments.

[0083] In the embodiment of the present application, performing a wire status monitoring according to the first combined operation result includes:

[0084] Calculate the posture change of the wire dancing through the first joint operation result;

[0085] Convert the dancing posture changes of the wire into the inertial coordinate system.

[0086] In the embodiment of the present application, performing a wire status monitoring according to the first combined operation result further includes:

[0087] The velocity of the wire dancing monitoring module is obtained by integrating the posture change in the inertial coordinate system.

[0088] The position of the wire dancing monitoring module is obtained by integrating the posture change in the inertial coordinate system twice.

[0089] Exemplarily, this application adopts a method combining weight analysis to obtain the positioning result X of PPP RTK (k) And RTK positioning result X ppp (k) , the positioning result of PPP is X RTK (k) And RTK positioning result X ppp (k) Perform weighted summation to obtain the joint positioning result X (k) , X RTK (k) is a 6-dimensional vector composed of RTK positioning coordinates and measurement speed, X ppp (k) is a 6-dimensional vector composed of the positioning coordinates and measurement speed of PPP.

[0090] X (k) =W RTK (k) X RTK (k) +W ppp (k) X ppp (k) ;

[0091] In the embodiment of the present application, the first positioning algorithm and the second positioning algorithm are updated according to the primary wire status monitoring result;

[0092] and performing secondary wire status monitoring according to the updated first positioning algorithm and the second positioning algorithm;

[0093] Repeat the wire status monitoring several times.

[0094] In an optional embodiment, the number of repetitions can be set to three or more to ensure the accuracy and reliability of conductor status monitoring. After each monitoring, the system will fine-tune the positioning algorithm based on the latest monitoring data to adapt to environmental changes and fluctuations in equipment performance. Through this iterative process, the monitoring accuracy of the conductor status can be continuously optimized, thereby providing strong technical support for the stable operation of the power system.

[0095] In an optional embodiment, the number of repetitions can also adopt a dynamic adjustment strategy, that is, to decide whether to continue the next round of monitoring based on the stability and accuracy of the real-time monitoring data. If the monitoring results show that the wire state has stabilized and the accuracy meets the predetermined requirements, the number of repetitions can be reduced or even further monitoring can be stopped to save resources. On the contrary, if the monitoring data shows that there are large fluctuations in the wire state or the accuracy does not meet the expected standards, the number of monitoring times is increased until stable and reliable monitoring results are obtained. For example, under extreme weather conditions, the system may automatically increase the monitoring frequency to ensure that the condition of the wire can be accurately assessed even in harsh environments.

[0096] In the embodiment of the present application, the wire status monitoring is performed several times, and the first joint operation result is obtained through the first joint operation, and the corresponding wire status monitoring is performed.

[0097] In summary, the present invention proposes a multi-source data fusion conductor state monitoring method, obtains the first monitoring data, and presets the first positioning algorithm and the second positioning algorithm; based on the first monitoring data, obtains the first positioning result through the first positioning algorithm, and obtains the second positioning result through the second positioning algorithm; performs a first joint operation on the first positioning result and the second positioning result, and performs a conductor state monitoring according to the first joint operation result. By fusing the monitoring results of different positioning algorithms, the accuracy and reliability of monitoring are improved. Specifically, by jointly operating the first positioning result and the second positioning result, the actual state of the conductor can be more comprehensively reflected, thereby providing more accurate data support for the monitoring of line dancing. In addition, by continuously updating the positioning algorithm and repeating the conductor state monitoring, the changes in the conductor state can be tracked in real time, potential fault risks can be discovered in time, and the stable operation of the power system can be guaranteed. At the same time, the present invention can also adapt to the monitoring needs under different environmental conditions, whether it is high mountains, remote areas or complex terrain, it can provide an effective monitoring solution.

[0098] Example 2

[0099] In a preferred embodiment, the following specific steps can be designed according to the method designed in the above embodiment:

[0100] S01. Set the prior probability matrix P(H) of RTK and PPP RTK (k) ) and P(H PPP (k) ), P(H RTK (k) ) and P(H PPP (k) ) is a 6*6 diagonal matrix, k is the number of iterations, and the initial value of k is 0.

[0101]

[0102] Where i represents the dimension of the RTK measurement vector or the PPP measurement vector; when k = 0, p RTKii (k) represents the initial likelihood function of the RTK measurement vector in dimension i, represents the variance of the RTK measurement vector in dimension i, represents the error of the RTK measurement vector in dimension i, p PPPii (k) represents the likelihood function of the PPP measurement vector in dimension i, represents the variance of the PPP measurement vector in dimension i, Represents the error of the PPP measurement vector in dimension i. The RTK measurement vector and the PPP measurement vector include three coordinate dimensions and three velocity dimensions.

[0103] S02, according to the prior probability matrix P(H RTK (k) ) and P(H PPP (k) ) Calculate the PPP weight matrix W PPP (k) and the RTK weight matrix W RTK (k) , the PPP weight matrix and RTK weight matrix are 6*6 diagonal matrices,

[0104]

[0105] in,

[0106]

[0107] S03. Obtain PPP positioning result X RTK (k) And RTK positioning result X ppp (k) , the positioning result of PPP is X RTK (k) And RTK positioning result X ppp (k) Perform weighted summation to obtain the joint positioning result X (k) , X RTK (k) is a 6-dimensional vector composed of RTK positioning coordinates and measurement speed, X ppp (k) is a 6-dimensional vector composed of the positioning coordinates and measurement velocity of PPP,

[0108] X (k) =W RTK (k) X RTK (k)+W ppp (k) X ppp (k) ;

[0109] S04, combined with IMU measurement data and joint positioning results X (k) Calculate the posture change of the wire dancing monitoring module, convert the posture change of the wire dancing monitoring module to the inertial coordinate system, integrate the posture change in the inertial coordinate system once to get the speed of the wire dancing monitoring module, integrate the posture change in the inertial coordinate system twice to get the position of the wire dancing monitoring module, and combine the speed and position of the wire dancing monitoring module into a standard vector X (k) , k represents the number of iterations;

[0110] S05. According to the positioning result of PPP RTK (k) , RTK positioning result X ppp (k) With the standard vector X (k)

[0111]

[0112] The probability matrix P(H RTK (k) ) and P(H PPP (k) ), the update method is as follows:

[0113]

[0114] S07, according to the prior probability matrix P(H RTK (k) ) and P(H PPP (k) ) Update the RTK weight matrix W RTK (k) and the PPP weight matrix W PPP (k) ,

[0115]

[0116] S8. Get the PPP positioning result X RTK (k) And RTK positioning result X ppp (k) , the positioning result of PPP is X RTK (k) And RTK positioning result X ppp (k) Perform weighted summation to obtain the joint positioning result X (k) , X RTK(k) is a 6-dimensional vector consisting of the positioning coordinates and measured velocity of the kth iteration of RTK, X ppp (k) is a 6-dimensional vector consisting of the positioning coordinates and measured velocity of the kth iteration of PPP,

[0117] X (k) =W RTK (k) X RTK (k) +W ppp (k) X ppp (k) ;

[0118] S9. Jump to step S04.

[0119] In an optional embodiment, the IMU measurement data is combined with the joint positioning result X (k) The method of calculating the posture change of the wire dancing monitoring module, converting the posture change of the wire dancing monitoring module to an inertial coordinate system, integrating the posture change in the inertial coordinate system once to obtain the speed of the wire dancing monitoring module, and integrating the posture change in the inertial coordinate system twice to obtain the position of the wire dancing monitoring module specifically includes:

[0120] Use the angular velocity data measured by the IMU to construct an antisymmetric angular velocity matrix;

[0121] The rate of change of attitude is obtained by performing matrix multiplication of the angular velocity matrix and the current direction cosine matrix;

[0122] Discretize the attitude change rate and update the direction cosine matrix;

[0123] Use the updated direction cosine matrix to transform the acceleration vector of the carrier coordinate system to the inertial coordinate system;

[0124] The acceleration vector converted to the inertial coordinate system is integrated once to obtain the velocity vector, and the acceleration vector converted to the inertial coordinate system is integrated once to obtain the position vector.

[0125] Furthermore, using the angular velocity data measured by the IMU, the method for constructing an antisymmetric angular velocity matrix is:

[0126]

[0127] Among them, ω x represents the angular velocity component of the wire dancing monitoring module rotating around the x-axis in the previous iteration, ω y represents the angular velocity component of the wire dancing monitoring module rotating around the y-axis in the previous iteration, ω zIt represents the angular velocity component of the wire dancing monitoring module rotating around the z-axis in the previous iteration.

[0128] In an optional embodiment, the attitude change rate is obtained by performing matrix multiplication between the angular velocity matrix and the current direction cosine matrix. The method is:

[0129]

[0130] Where R is the direction cosine matrix R measured by IMU at the previous moment,

[0131]

[0132] Wherein, ψ represents the yaw angle of the wire dance monitoring module at the previous iteration, φ represents the roll angle of the wire dance monitoring module at the previous iteration, and θ represents the pitch angle of the wire dance monitoring module at the previous iteration.

[0133] Furthermore, the attitude change rate is discretized and the direction cosine matrix is ​​updated.

[0134]

[0135] Where T represents the time of the previous iteration, and Δt represents the time difference between two iterations.

[0136] In an optional embodiment, the method of converting the acceleration vector of the carrier coordinate system to the inertial coordinate system using the updated direction cosine matrix is:

[0137] a I (t+Δt)=R(t+Δt)·a B (t+Δt)

[0138] Among them, a I (t+Δt) represents the acceleration vector in the inertial coordinate system at time t+Δt, a B (t+Δt) represents the acceleration vector in the carrier coordinate system at time t+Δt.

[0139] In an optional embodiment, according to the positioning result X of PPP RTK (k) , RTK positioning results

[0140]

[0141] Among them, E PPPii (k-1) represents the mathematical expectation of the PPP measurement vector in the i-th dimension at the k-1th iteration, E RTKii(k -1) Represents the mathematical expectation of the RTK measurement vector in the i-th dimension at the k-1th iteration.

[0142] It should be noted that based on the advantages of combining PPP (precision point positioning) and RTK (real-time dynamic positioning) technologies, high-precision wire status monitoring is achieved by dynamically adjusting the weights of the two. Specifically, the method sets the prior probability matrices of PPP and RTK, and updates these matrices and corresponding weights in real time according to the measurement results of each iteration. When RTK is interfered or PPP has errors in a high-dynamic environment, the system automatically reduces the weight of the positioning technology with larger errors and increases the weight of the technology with smaller errors. This dynamic adjustment mechanism ensures that high-precision positioning can be maintained in various complex environments (such as signal shielding or high-dynamic environments), and monitors the posture changes of the wires through IMU data combined with joint positioning results, realizing accurate monitoring of wire dancing.

[0143] Example 3

[0144] This embodiment also provides a multi-source data fusion conductor state monitoring system, including:

[0145] A prediction operation module, used for acquiring first monitoring data, and presetting a first positioning algorithm and a second positioning algorithm;

[0146] A positioning result determination module, configured to obtain a first positioning result through a first positioning algorithm based on the first monitoring data, and obtain a second positioning result through a second positioning algorithm;

[0147] The monitoring module is used to perform a first joint operation on the first positioning result and the second positioning result, and perform a wire status monitoring according to the first joint operation result.

[0148] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0149] This embodiment also provides a computer device, which can be a terminal. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a multi-source data fusion wire state monitoring method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse.

[0150] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0151] Acquire first monitoring data, and preset a first positioning algorithm and a second positioning algorithm;

[0152] Based on the first monitoring data, a first positioning result is obtained by using a first positioning algorithm, and a second positioning result is obtained by using a second positioning algorithm;

[0153] A first joint operation is performed on the first positioning result and the second positioning result, and a wire status monitoring is performed according to the first joint operation result.

[0154] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0155] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0156] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0160] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A multi-source data fusion conductor state monitoring method, characterized in that: include: Acquire first monitoring data, and preset a first positioning algorithm and a second positioning algorithm; Based on the first monitoring data, obtaining a first positioning result by using the first positioning algorithm, and obtaining a second positioning result by using the second positioning algorithm; A first joint operation is performed on the first positioning result and the second positioning result, and a wire status monitoring is performed according to the first joint operation result.

2. The multi-source data fusion conductor state monitoring method according to claim 1, characterized in that: Also includes: Update the first positioning algorithm and the second positioning algorithm according to the primary conductor state monitoring result; and performing secondary wire status monitoring according to the updated first positioning algorithm and the second positioning algorithm; Repeat the wire status monitoring several times.

3. The multi-source data fusion conductor state monitoring method according to claim 2, characterized in that: The conducting of the several wire status monitorings all involves obtaining the first combined operation result through the first combined operation, and conducting the corresponding wire status monitoring.

4. The multi-source data fusion conductor state monitoring method according to claim 3, characterized in that: The first positioning result and the second positioning result both include at least two indicators: positioning coordinates and measurement speed.

5. The multi-source data fusion conductor state monitoring method according to claim 4, characterized in that: The obtaining of a first positioning result by using the first positioning algorithm and the obtaining of a second positioning result by using the second positioning algorithm include: Setting a first priori probability matrix and a second priori probability matrix based on the first positioning algorithm and the second positioning algorithm; A first weight matrix and a second weight matrix are calculated based on the first prior probability matrix and the second prior probability matrix.

6. The multi-source data fusion conductor state monitoring method according to claim 5, characterized in that: The performing a wire status monitoring according to the first combined operation result comprises: Calculate the posture change of the wire dancing according to the first joint operation result; Convert the dancing posture changes of the wire into the inertial coordinate system.

7. The multi-source data fusion conductor state monitoring method according to claim 6, characterized in that: The performing a wire status monitoring according to the first combined operation result further comprises: The velocity of the wire dancing monitoring module is obtained by integrating the posture change in the inertial coordinate system. The position of the wire dancing monitoring module is obtained by integrating the posture change in the inertial coordinate system twice.

8. A multi-source data fusion conductor status monitoring system, characterized in that: include: A prediction operation module, used for acquiring first monitoring data, and presetting a first positioning algorithm and a second positioning algorithm; A positioning result determination module, configured to obtain a first positioning result through the first positioning algorithm based on the first monitoring data, and obtain a second positioning result through the second positioning algorithm; The monitoring module is used to perform a first joint operation on the first positioning result and the second positioning result, and perform a wire status monitoring according to the first joint operation result.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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