A method and system for monitoring the clamping degree of a power fitting

Abstract

The present application relates to the technical field of power equipment status monitoring, and specifically provides a method and system for monitoring the clamping degree of power fittings, the method comprising the steps of: synchronously acquiring comprehensive stress data of the power fittings, first ambient temperature data, and first load current data of the transmission line; calculating a first thermally induced stress component caused by ambient temperature changes and a second thermally induced stress component caused by the Joule heating effect of the load current based on the first ambient temperature data, the first load current data, and preset material properties corresponding to the power fittings; calculating a static stress component reflecting the clamping force of the power fittings based on the comprehensive stress data, the first thermally induced stress component, and the second thermally induced stress component; obtaining the current clamping degree of the power fittings based on the static stress component analysis; the method can effectively separate the signal generated by the Joule heating effect of the ambient temperature and the load current from the static stress component reflecting the actual clamping force of the power fittings in the mixed signal collected by the stress sensor.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of power equipment state monitoring, in particular to a power hardware clamp tightness monitoring method and system. BACKGROUND

[0002] The power hardware is a key component in the power transmission line, and the clamp tightness monitoring is crucial for the safety of the power grid. The existing technology integrates a stress sensor on the hardware or fastener to collect real-time data related to the clamping force, and transmits the data to the monitoring center for analysis through wireless communication, which represents the development direction of online monitoring technology and aims to improve the reliability of the line and prevent faults.

[0003] However, in actual operation, this stress sensor monitoring method faces severe interference from complex environmental factors. First, the power hardware and the monitoring device installed thereon are exposed to the natural environment for a long time, and their working temperature changes dynamically with the change of sunlight intensity, the change of seasons, and the significant change of day and night temperature difference. Metal materials generally have the physical property of thermal expansion and contraction, and the rise and fall of temperature will directly cause the size of the hardware body, fastener and even the stress sensor itself to change slightly but significantly, which in turn causes the internal stress state to change accordingly. This thermal stress change caused by temperature change will inevitably superimpose on the mechanical stress generated by the conductor clamping force, making the original data collected by the stress sensor a mixed signal, which cannot directly and accurately reflect the real clamping tightness state. For example, in the hot summer afternoon, the temperature of the hardware rises significantly, and the material expansion may cause the stress sensor reading to drift or fluctuate, and the monitoring system may misjudge the change of the clamping tightness, thereby causing unnecessary maintenance or false alarm.

[0004] Further, the actual working temperature of the power hardware is not only affected by the environmental temperature, but also significantly affected by the Joule heating effect generated by the load current flowing through the power transmission conductor. When the load of the power transmission line increases, the current flowing through the conductor increases, and according to Joule's law, the temperature of the conductor and the power hardware in close contact with it will also rise. It is worth noting that the load current of the power transmission line is dynamically changing, and its change law is closely related to the user's power consumption behavior, showing significant randomness and volatility.

[0005] In summary, the stress signal collected by the stress sensor is a mixed signal generated by the combined action of clamping force, ambient temperature and load current joule heat effect. Since the existing monitoring method based on the stress sensor cannot effectively separate the signal generated by the ambient temperature and load current joule heat effect in the mixed signal, the existing technology has the problem of decreased accuracy of clamping degree evaluation due to the inability to extract the static stress component from the stress signal collected by the stress sensor, which can truly reflect the irreversible loosening trend of the power fittings, thereby causing misjudgment or false alarm.

[0006] At present, there is no effective technical solution to the above problems. It should be noted that the above information disclosed in this part is only used to understand the background of the inventive concept, and therefore can contain information that does not constitute prior art. SUMMARY

[0007] The purpose of the present application is to provide a power fitting clamping degree monitoring method and system, which can effectively separate the signal generated by the ambient temperature and load current joule heat effect in the mixed signal collected by the stress sensor from the static stress component reflecting the real clamping force of the power fitting.

[0008] In a first aspect, the present application provides a power fitting clamping degree monitoring method, which comprises the following steps:

[0009] S1, synchronously acquiring comprehensive stress data of the power fitting, first ambient temperature data and first load current data of the power transmission conductor;

[0010] S2, calculating a first thermal stress component caused by ambient temperature change and a second thermal stress component caused by load current joule heat effect according to the first ambient temperature data, the first load current data and the preset material characteristics corresponding to the power fitting;

[0011] S3, calculating a static stress component reflecting the clamping force of the power fitting according to the comprehensive stress data, the first thermal stress component and the second thermal stress component;

[0012] S4, analyzing and acquiring the current clamping degree of the power fitting according to the static stress component.

[0013] In a second aspect, the present application further provides a power fitting clamping degree monitoring system, which comprises:

[0014] A data acquisition module for synchronously acquiring comprehensive stress data of the power fitting, first ambient temperature data and first load current data of the power transmission conductor;

[0015] a thermal stress component calculation module configured to calculate a first thermal stress component caused by a change in ambient temperature and a second thermal stress component caused by a joule heat effect of a load current according to the first ambient temperature data and the first load current data and preset material properties corresponding to the power fitting;

[0016] a static stress component calculation module configured to calculate a static stress component reflecting a clamping force of the power fitting according to the comprehensive stress data, the first thermal stress component and the second thermal stress component;

[0017] a clamping degree analysis module configured to analyze the current clamping degree of the power fitting according to the static stress component.

[0018] As can be seen from the above, the power fitting clamping degree monitoring method and system provided by the application can extract the static stress component reflecting the real clamping force of the power fitting from the comprehensive stress data by synchronously acquiring the comprehensive stress data, the ambient temperature data and the load current data of the power fitting, and calculating and separating the thermal stress components caused by the change in ambient temperature and the joule heat effect of the load current based on the material properties of the power fitting. That is, the application can effectively separate the signals caused by the ambient temperature and the joule heat effect of the load current in the mixed signals collected by the stress sensor from the static stress component reflecting the real clamping force of the power fitting. Therefore, the application can effectively solve the problem of the decline in the evaluation accuracy of the clamping degree caused by the failure to extract the static stress component from the stress signals collected by the stress sensor, which can truly reflect the irreversible loosening trend of the power fitting, thereby effectively avoiding the situation of false judgment or false alarm caused by the evaluation accuracy of the clamping degree. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A flowchart of a power fitting clamping degree monitoring method provided by an embodiment of the application.

[0020] Figure 2 A structural schematic diagram of a power fitting clamping degree monitoring system provided by an embodiment of the application.

[0021] Reference signs: 1, data acquisition module; 2, thermal stress component calculation module; 3, static stress component calculation module; 4, clamping degree analysis module. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. The components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0023] It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0024] In a first aspect, as shown in the drawings, the present application provides a power fitting clamping degree monitoring method, comprising the following steps: Figure 1

[0025] S1, synchronously acquiring comprehensive stress data of the power fitting, first environmental temperature data and first load current data of the power transmission conductor;

[0026] S2, calculating a first thermal stress component caused by environmental temperature change and a second thermal stress component caused by load current Joule heat effect according to the first environmental temperature data and the first load current data and the preset material characteristics corresponding to the power fitting;

[0027] S3, calculating a static stress component reflecting the clamping force of the power fitting according to the comprehensive stress data, the first thermal stress component and the second thermal stress component;

[0028] S4, analyzing and acquiring the current clamping degree of the power fitting according to the static stress component.

[0029] ​The comprehensive stress data of step S1 refers to the original signal reflecting the overall stress state of the power fitting collected by the stress sensor on the power fitting. The comprehensive stress data is a mixed signal containing various stress components such as mechanical stress and thermal stress that the power fitting bears in actual operation. The embodiment can use the resistance strain gauge, the fiber Bragg grating sensor or the piezoelectric sensor arranged on the power fitting to obtain the comprehensive stress data. The embodiment can obtain the total stress information containing various stress components by obtaining the comprehensive stress data. The first environmental temperature data of step S1 refers to the temperature measurement value of the environment where the power fitting is located. The embodiment can use the thermistor, the thermocouple or the infrared temperature sensor to obtain the first environmental temperature data. The embodiment can quantify the influence of the environmental temperature on the stress state of the power fitting by obtaining the first environmental temperature data. The first load current data of the power transmission conductor refers to the current measurement value flowing through the power transmission conductor connected with the power fitting. The embodiment can use the current transformer, the Hall sensor or the flexible current probe to obtain the first load current data. The embodiment can quantify the influence of the load current joule heat effect on the stress state of the power fitting by obtaining the first load current data. Step S1 can keep consistency in time by synchronously obtaining the comprehensive stress data of the power fitting, the first environmental temperature data and the first load current data of the power transmission conductor. The embodiment can use the unified time stamp, the synchronous sampling clock or the centralized data acquisition system to realize the synchronous acquisition of the comprehensive stress data, the first environmental temperature data and the first load current data to ensure that all data points are recorded at the same time or in a very short time interval and provide time-aligned original input for subsequent data processing.

[0030] The preset material property of step S2 refers to the inherent physical attribute parameter of the power fitting body and its fastener, which is preferably measured when the power fitting is manufactured, that is, the preset material property can be obtained by consulting a material manual or laboratory test data, which can include the thermal expansion coefficient, Young's modulus, and resistivity, etc., and the embodiment can provide the basic physical parameters for calculating the thermal stress component by obtaining the preset material property. The first thermal stress component of step S2 refers to the stress component generated by the expansion or contraction of the power fitting material caused by the change of the ambient temperature, and the embodiment can quantify the contribution of the ambient temperature change to the total stress by calculating the first thermal stress component. The second thermal stress component of step S2 refers to the stress component generated by the temperature rise of the power fitting caused by the joule heat effect of the load current of the power transmission conductor, and the embodiment can quantify the contribution of the load current change to the total stress by calculating the second thermal stress component, which can be calculated according to the joule heat law, the heat balance equation, and the thermal expansion coefficient and Young's modulus of the material, for example, by first calculating the temperature rise caused by the current, and then converting the temperature rise into stress.

[0031] The static stress component of step S3 refers to the stress component mainly reflecting the size of the clamping force of the power fitting after the thermal stress component and other dynamic stress components are stripped from the comprehensive stress data. Since the embodiment calculates the static stress component according to the comprehensive stress data, the first thermal stress component, and the second thermal stress component, the static stress component of the embodiment is equivalent to the stress generated by the clamping force of the power fitting itself without being affected by the dynamic changes of the ambient temperature and the load current. Step S3 can calculate the static stress component according to the comprehensive stress data, the first thermal stress component, and the second thermal stress component by using the first thermal stress component and the second thermal stress component in the comprehensive stress data, that is, the calculation formula of the static stress component is: static stress component = comprehensive stress data - first thermal stress component - second thermal stress component.

[0032] Step S4 determines the clamping state of the power fitting by analyzing the static stress component. The embodiment can obtain the current clamping degree of the power fitting by calculating the static stress change amount of the static stress component according to the preset initial clamping stress reference value, and then evaluating the current clamping degree based on the static stress change amount (which can be realized by using a lookup table or a machine learning model), and the embodiment can also obtain the current clamping degree of the power fitting by analyzing the stress component range corresponding to the clamping degree in which the static stress component is located.

[0033] The core innovation of the present application is that the comprehensive stress data of the power fitting, the environmental temperature data and the load current data of the power transmission conductor are synchronously acquired, and the thermal stress components caused by the environmental temperature change and the load current Joule heat effect are calculated and stripped based on the material properties of the power fitting, so as to extract the static stress component reflecting the real clamping force of the power fitting from the comprehensive stress data, that is, the present application can effectively separate the signal generated by the environmental temperature and the load current Joule heat effect in the mixed signal collected by the stress sensor from the static stress component reflecting the real clamping force of the power fitting. Therefore, the present application can effectively solve the problem of the decline of the evaluation accuracy of the clamping degree caused by the inability to extract the static stress component which can truly reflect the irreversible loosening trend of the power fitting from the stress signal collected by the stress sensor, thereby effectively avoiding the situation of false judgment or false alarm caused by the evaluation accuracy of the clamping degree.

[0034] Specifically, the method first synchronously acquires the comprehensive stress data of the power fitting, the first environmental temperature data and the first load current data of the power transmission conductor, to ensure that the multi-source data required for subsequent analysis has correspondence in time. Then, according to the acquired first environmental temperature data, the first load current data and the preset material properties of the power fitting, the first thermal stress component caused by the environmental temperature change and the second thermal stress component caused by the load current Joule heat effect are calculated, which quantifies the influence of environmental and load changes on the stress state of the power fitting. Subsequently, according to the synchronously acquired comprehensive stress data and the calculated first thermal stress component and second thermal stress component, the influence of the thermal stress component is removed from the comprehensive stress data, so as to calculate the static stress component mainly reflecting the clamping force of the power fitting. Finally, based on the calculated static stress component, the current clamping state or change trend of the power fitting is analyzed and evaluated to obtain the current clamping degree of the power fitting. The whole process forms a complete clamping degree monitoring process which can effectively cope with environmental and load interference through data acquisition, thermal stress calculation and separation, static stress extraction and clamping degree analysis.

[0035] As a preferred embodiment, the scheme of the present application is implemented as follows: strain sensors and temperature sensors are installed on the power fittings, and current sensors are installed on the power transmission wires, and the sensors synchronously collect comprehensive stress signals (comprehensive stress data), environmental temperature signals (first environmental temperature data), and power transmission wire current signals (first load current data) through a data acquisition unit. After the collected signals are signal-conditioned and digitized, they are transmitted to a processing unit. The processing unit stores material parameters (such as thermal expansion coefficient, Young's modulus, etc.) of the power fittings, and calculates thermal stress caused by environmental temperature changes (first thermal stress component) according to the collected environmental temperature signals and the material parameters. At the same time, the processing unit calculates temperature rise and thermal stress caused by the Joule heating effect (second thermal stress component) according to the collected current signals, material parameters, and heat transfer model. The processing unit subtracts the calculated two parts of thermal stress from the collected comprehensive stress signals to obtain static stress data. Finally, the processing unit analyzes the static stress data, such as comparing with the initial static stress or monitoring the change rate, to obtain the current clamping degree of the power fittings. Through the above scheme, the present application can effectively separate the interference of environmental temperature and load current changes on the stress measurement of the power fittings, extract the static stress component that truly reflects the clamping state, improve the accuracy and reliability of the clamping degree monitoring of the power fittings, and avoid false alarms or false alarms caused by environmental factors.

[0036] In some preferred embodiments, step S1 comprises:

[0037] S11, synchronously acquiring comprehensive stress data of the power fittings, first environmental temperature data, and first load current data of the power transmission wires;

[0038] S12, preprocessing the comprehensive stress data, the first environmental temperature data, and the first load current data, the preprocessing including signal conditioning and drift compensation.

[0039] The preprocessing of step S12 refers to a series of data processing operations performed after the acquisition of the original data (integrated stress data, first environmental temperature data and first load current data) to improve data quality and reliability. The preprocessing includes signal conditioning and drift compensation, etc. Signal conditioning refers to the process of adjusting and optimizing the original electrical signal, which can include filtering, amplification, impedance matching, etc. Drift compensation refers to correcting the slow, unintended offset or change of the sensor output signal over time or environment. The drift compensation can be achieved by baseline correction, trend fitting and removal, or reference point-based calibration, etc. Due to the influence of factors such as the characteristics of the sensor itself, external electromagnetic interference or environment, the original integrated stress data, first environmental temperature data and first load current data may contain noise or have drift over time. The embodiment can use signal conditioning to remove high-frequency noise or transient interference in the data to make the signal smoother and clearer. The embodiment can use drift compensation to correct the zero-point offset or sensitivity change of the sensor caused by long-term use or environmental changes to ensure the accuracy of the data. Therefore, the embodiment can improve the data quality and reliability of the integrated stress data, first environmental temperature data and first load current data by preprocessing the integrated stress data, first environmental temperature data and first load current data, to improve the accuracy of subsequent calculations, thereby significantly improving the overall accuracy and reliability of the power fitting clamping degree monitoring and further reducing false positives and false alarms.

[0040] In some preferred embodiments, step S11 includes:

[0041] S111, synchronously acquiring first environmental temperature data, first load current data of the power transmission conductor and first local stress data corresponding to different stress acquisition positions on the power fitting;

[0042] S112, generating integrated stress data according to all first local stress data according to the stress acquisition positions corresponding to the first local stress data and the structural characteristics of the power fitting.

[0043] The different stress collection positions on the power fitting of the embodiment are preferably a plurality of discrete points or regions on the power fitting that are representative of stress concentration or stress distribution, such as bolt connections, wire crimping positions, and force-bearing parts of the fitting body, etc. The first local stress data of the embodiment is the stress measurement value collected by the stress sensor arranged at the different stress collection positions. The structural characteristics of the power fitting of the embodiment refer to the physical properties and geometric features of the power fitting itself, such as its material type, geometric shape, size, connection method, stiffness distribution of each part, etc. The structural characteristics determine the internal stress distribution law and transmission path of the power fitting when subjected to load (including clamping force and thermal stress, etc.). The stress collection positions corresponding to the first local stress data and the structural characteristics of the power fitting of the embodiment are used to generate comprehensive stress data according to all the first local stress data, which means that all the first local stress data are integrated into a comprehensive numerical value that can represent the overall stress state of the fitting by using the specific collection positions of the first local stress data and the structural characteristics of the power fitting itself. The embodiment can realize the generation of comprehensive stress data by using a physical model-based calculation (such as post-processing of finite element analysis results), and the embodiment can also realize the generation of comprehensive stress data by using a data-driven method (such as synthesizing local stress data by a machine learning model). The embodiment can also realize the generation of comprehensive stress data by using an empirical or theoretical weighted average (for example, based on expert experience, each first local stress data is assigned a corresponding weight according to the stress collection position and the structural characteristics of the power fitting, and then all the first local stress data and their corresponding weights are weighted and averaged).

[0044] The present scheme first comprehensively understands the stress distribution of the fitting from multiple angles by acquiring first local stress data corresponding to different stress collection positions on the power fitting, so as to provide multi-source information for subsequent generation of comprehensive stress data that can better represent the overall state of the fitting. Subsequently, the present scheme generates comprehensive stress data from all first local stress data according to the stress collection position corresponding to the first local stress data and the structural characteristics of the power fitting, so as to utilize the position information of the first local stress data and the structural characteristics of the power fitting to process and integrate (for example, weighted average, model calculation or other forms of integration) the first local stress data of different stress collection positions in a targeted manner, so as to generate comprehensive stress data that can more accurately reflect the overall stress state of the fitting than simply superimposing or selecting a certain point. This generation method based on multi-point local stress and combined with structural characteristics can improve the representativeness of the comprehensive stress data, so as to lay a more solid foundation for subsequent separation of thermal stress, extraction of static stress and final analysis of clamping degree. Thus, by acquiring multi-point local stress and integrating the structural characteristics of the fitting, comprehensive stress data that can more accurately reflect the overall stress state of the fitting can be obtained, thereby solving the problem that direct acquisition of comprehensive stress data may not be comprehensive or accurate, and providing more reliable basic data for subsequent more accurate calculation of static stress component and analysis of clamping degree.

[0045] As a specific implementation, strain gauges (stress sensors) are pasted at a plurality of key positions (such as bolt root, below wire pressing groove and maximum stress area of fitting body, etc.) on the power fitting, temperature sensors are installed near the power fitting or on the body of the power fitting, and current sensors are installed on the power transmission line. During monitoring, the data acquisition unit can synchronously acquire data from all strain gauges, temperature sensors and current sensors to obtain first local stress data, first environmental temperature data and first load current data corresponding to different stress collection positions. These data are transmitted to the processing unit. The processing unit stores structural model information (such as geometric data and material attribute parameters obtained by three-dimensional scanning or design drawings) of the power fitting, and can run an algorithm that utilizes, for example, finite element reverse analysis or a pre-trained model to integrate these discrete local stress data into a comprehensive stress value representing the overall stress state of the fitting according to the strain gauge position corresponding to each local stress data in combination with the structural model of the fitting. For example, the local stress data can be weighted and summed to obtain comprehensive stress data according to the weight of each position to the overall stress state (which can be predetermined based on structural analysis).

[0046] In some preferred embodiments, step S112 comprises:

[0047] A1, obtaining second ambient temperature data, second load current data and a second local stress data set of the power fitting in an initial operation stage, the second local stress data set comprising second local stress data corresponding to different stress collection positions on the power fitting;

[0048] A2, analyzing the response characteristics of each stress collection position according to the second local stress data set, the second ambient temperature data and the second load current data;

[0049] A3, determining a weighted weight corresponding to each first local stress data according to the response characteristics of each stress collection position and the structural characteristics of the power fitting;

[0050] A4, performing weighted average on all first local stress data and the corresponding weighted weight to obtain comprehensive stress data.

[0051] The collection method of the second environmental temperature data, the second load current data and the second local stress data set of this embodiment is preferably the same as the collection method of the first environmental temperature data, the first load current data and the first local stress data of the above-mentioned first embodiment. The initial running stage of this embodiment refers to a specific period of time after the power fitting is installed and first put into operation, which can be several days, weeks or months, for example, which is sufficient to cover the typical running state of the fitting under different environmental and load conditions and allow the stress distribution to reach a relatively stable state. The response characteristic of this embodiment refers to the sensitivity and mode of the local stress data of a specific stress collection position on the power fitting to changes in external factors such as environmental temperature and load current, which can include the sensitivity of stress to temperature changes, the sensitivity of stress to load current changes, and the reference stress value under different environmental conditions. This embodiment can use linear regression model, nonlinear regression, polynomial fitting or machine learning algorithm to realize the analysis and acquisition of the response characteristic of each stress collection position according to the second local stress data set, the second environmental temperature data and the second load current data. Determining the weighted weight refers to calculating the contribution proportion of each local stress data according to the response characteristic (for example, sensitivity to environmental interference, representativeness of overall stress) of each stress collection position and the structural characteristics (for example, stress concentration area, stress path, structural stiffness of sensor installation position) of the power fitting. This embodiment can use expert experience-based, analytic hierarchy process, principal component analysis or error variance reciprocal-based methods to determine the weighted weight corresponding to each first local stress data according to the response characteristic of each stress collection position and the structural characteristics of the power fitting, for example, higher weight is given to collection points that are less affected by environmental temperature and load current or are located in key stress areas; lower weight is given to collection points that are more affected by environmental temperature and load current or are located in non-key stress areas, that is, the weighted weight of the embodiment refers to a numerical factor assigned to each local stress data, which is used to measure the importance or contribution of the data in calculating the comprehensive stress data.

[0052] The present scheme overcomes the errors that may be caused by simply combining local stress data by introducing a fine analysis of individual differences of the power fittings and the influence of external environment. Specifically, in step A1, first, the basic operation data of the power fittings in the initial operation stage is obtained. Then, in step A2, based on these basic operation data, the relationship between the local stress data of each stress collection position and the environmental temperature and load current is analyzed to quantify the response characteristics of each stress collection position to these external factors in the current installation state, to identify which positions have greater influence on the stress data by temperature or load, and which positions can more stably reflect the clamping force. Subsequently, in step A3, the response characteristics obtained in step A2 and the inherent structural characteristics of the power fittings are combined to determine the weighting weight of each currently collected first local stress data when calculating the comprehensive stress data, for example, positions with strong response characteristics (i.e. greatly affected by external factors) are given lower weights, while positions with weak response characteristics and high correlation with clamping force are given higher weights; at the same time, positions that are more critical in structure and can better represent the overall stress state may also be given higher weights. Finally, in step A4, all the currently collected first local stress data and their corresponding weighting weights are weighted and averaged to obtain the comprehensive stress data, this weighted averaging method can effectively integrate information from different positions, highlight important and reliable data and suppress interference or less relevant data, thereby generating a comprehensive stress data that more accurately reflects the real overall stress state of the power fittings, therefore the present scheme can dynamically or in advance determine the optimal weight distribution according to the actual installation state and operation environment of each specific fitting, so that the generated comprehensive stress data can more accurately reflect the real stress condition of the fittings and lay a solid foundation for subsequent accurate calculation of static stress component.

[0053] For example, in specific implementation, step A1 can be that, through the sensor network deployed on the power fittings, the ambient temperature, the load current flowing through the conductor and the readings of the plurality of stress sensors distributed at the key stress positions (such as bolts and body junctions) of the fittings are synchronously collected every hour within one month after the fittings are installed, and the data is stored in a local storage unit or uploaded to a remote server. Step A2 can be that, through offline analysis on the stored initial operation data, for each stress collection point, a multivariate linear regression model of the local stress and the ambient temperature and the load current is established, and the coefficients of the model can be taken as the response characteristic parameters of the collection point to reflect the sensitivity of the collection point to the temperature and current changes in the current installation state. Step A3 can be that, after the response characteristic analysis is completed, a weighted weight is determined based on the coefficients reflecting the temperature and current influences in the regression model and the position of the collection point in the fitting structure (such as whether it is located in the main load-bearing area), for example, the weight of the point with a larger absolute value of the temperature coefficient or the current coefficient can be lower, and the weight of the point located in the main load-bearing area can be higher. Step A4 can be that, in the subsequent real-time monitoring process, whenever a new set of first local stress data is collected, a weighted average is performed on all the first local stress data and the corresponding weighted weights to obtain comprehensive stress data. Through the above technical solution, the application can dynamically or in advance determine the contribution weights of the data of different stress collection positions according to the individual differences and actual operation environment of the power fittings, so as to generate comprehensive stress data which can more accurately reflect the real overall stress state of the power fittings, thereby effectively solving the problem that the comprehensive stress data is inaccurate in the prior art due to the failure to fully consider the individual differences and external environment influences of the fittings, and improving the accuracy of subsequent clamping degree evaluation.

[0054] In some preferred embodiments, the preset material properties include a thermal expansion coefficient, a Young's modulus, an electrical resistivity, an effective heat exchange coefficient, an effective heat dissipation perimeter and an effective conduction cross-sectional area, and step S2 includes:

[0055] S21, calculating a temperature difference according to the first ambient temperature data and a preset reference temperature, and then calculating a first thermal stress component caused by ambient temperature changes according to the temperature difference, the thermal expansion coefficient and the Young's modulus;

[0056] S22, calculating a temperature rise of the power fittings caused by the joule heat effect of the load current according to the first load current data, the electrical resistivity, the effective heat exchange coefficient, the effective heat dissipation perimeter and the effective conduction cross-sectional area, and then calculating a second thermal stress component caused by the joule heat effect of the load current according to the temperature rise of the power fittings, the thermal expansion coefficient and the Young's modulus.

[0057] The thermal expansion coefficient of the embodiment refers to the relative change in length or volume of the material per unit temperature increase, and the thermal expansion coefficient can be obtained by using an expansion apparatus or the like. The Young's modulus of the embodiment refers to the ratio of stress to strain within the elastic deformation range of the material, and the Young's modulus can reflect the ability of the material to resist elastic deformation. The electrical resistivity of the embodiment refers to the ability of the material to hinder the flow of current, and the electrical resistivity can be obtained by using a four-terminal method or the like. The effective heat exchange coefficient of the embodiment refers to the ability of the surface of the power fitting to exchange heat with the surrounding air through convection, and the effective heat exchange coefficient can be obtained by using numerical simulation or the like. The effective heat dissipation perimeter of the embodiment refers to the effective surface perimeter of the power fitting for heat exchange with the environment, and the effective heat dissipation perimeter can be calculated or estimated according to the geometric shape of the power fitting. The effective conduction cross-sectional area of the embodiment refers to the effective cross-sectional area of the power fitting through which the current flows, and the effective conduction cross-sectional area can be calculated or estimated according to the structure of the power fitting and the current distribution characteristics. The preset reference temperature of the embodiment refers to the reference temperature for calculating the temperature difference, and the preset reference temperature can be the ambient temperature when the power fitting is installed or a long-term average ambient temperature. Specifically, the calculation formula of the first thermal stress component of the embodiment is: ; wherein thermal_env represents the first thermal stress component, k_env represents the preset environmental thermal stress calibration factor, E represents the Young's modulus, a represents the thermal expansion coefficient, T ref represents the preset reference temperature, and T env represents the first environmental temperature data. The calculation formula of the temperature rise of the power fitting of the embodiment is: ; wherein represents the temperature rise of the power fitting, k_joule_temp represents the preset Joule heat temperature rise calibration factor, I_load represents the first load current data, p represents the electrical resistivity, h_eff represents the effective heat exchange coefficient, P_eff represents the effective heat dissipation perimeter, and A_eff represents the effective conduction cross-sectional area. The calculation formula of the second thermal stress component of the embodiment is: ; wherein thermal_joule represents the second thermal stress component, and k_joule_stress represents the preset Joule heat stress calibration factor.

[0058] In some preferred embodiments, step S2 further comprises a step performed before step S21:

[0059] B1, obtaining historical operation data of the power fitting;

[0060] B2, evaluating the material aging state of the power fitting according to the historical operation data;

[0061] B3. Correcting the thermal expansion coefficient, Young's modulus, resistivity, effective convective heat transfer coefficient, effective heat dissipation perimeter, and effective conduction cross-sectional area according to the material aging state.

[0062] The historical operation data of this embodiment refers to the relevant data recorded at different time points or under different operating conditions after the power fittings are put into use, which can include operating time, cumulative load current, environmental temperature variation range, and exposure time to specific environments (such as high humidity, corrosive gas), etc. The material aging state of this embodiment refers to the degree of performance degradation of the power fitting material due to the combined effects of heat, electricity, mechanical stress, and environmental factors (such as oxidation, corrosion, fatigue) during long-term operation, which can be characterized by changes in key performance parameters such as material strength, toughness, electrical conductivity, thermal expansion coefficient, etc. The correction of the thermal expansion coefficient, Young's modulus, resistivity, effective convective heat transfer coefficient, effective heat dissipation perimeter, and effective conduction cross-sectional area of this embodiment refers to the process of adjusting the numerical values of these material property parameters for subsequent calculations according to the evaluated material aging state, so that they are closer to the actual performance values of the power fittings. This embodiment can achieve the correction of the thermal expansion coefficient, Young's modulus, resistivity, effective heat transfer coefficient, effective heat dissipation perimeter, and effective conduction cross-sectional area according to the material aging state based on aging models, empirical formulas, or lookup table methods, etc.

[0063] The present application effectively improves the accuracy of the calculation of the thermal stress component by introducing the evaluation of the aging state of the power fitting material and correcting the material property parameters according to the evaluation results before calculating the thermal stress component. Specifically, the historical operation data of the power fitting is obtained to provide the necessary data basis for evaluating the possible changes of the material in the long-term operation. According to the historical operation data, the aging degree that the power fitting material may experience is evaluated, for example, the influence of factors such as operation time, environmental conditions, etc. on the material performance is considered, so as to obtain an evaluation result reflecting the current aging state of the material. According to the aging state of the material evaluated, the thermal expansion coefficient, Young's modulus, resistivity, effective convective heat transfer coefficient, effective heat dissipation perimeter and effective conduction cross-sectional area are corrected, which means that instead of using fixed preset values, the material property parameters that are closer to the current actual values adjusted according to the actual operation situation and the aging state are used when calculating the thermal stress component. By using the corrected material property parameters for subsequent calculation, the first thermal stress component caused by the change of environmental temperature and the second thermal stress component caused by the joule heat effect of the load current can be more accurately calculated, thereby providing a more reliable basis for the subsequent calculation of the static stress component reflecting the clamping force of the power fitting, and finally improving the accuracy of the clamping degree evaluation. This way of dynamically correcting the material parameters before calculation makes the whole monitoring method adapt to the change of the material performance of the power fitting over time, improves the robustness and long-term effectiveness of the method.

[0064] In one embodiment, the historical operation data of the power fitting can be collected by sensors, data recorders installed on the power fitting or power transmission line, or through the SCADA system, which can include the cumulative operation time of the power fitting, the highest / lowest environmental temperature experienced, the cumulative amount of charge passed (related to joule heat), and the humidity, salt mist, etc. of the environment. The evaluation of the material aging state of the power fitting according to the historical operation data can be through the establishment of a material aging model, which can be based on laboratory accelerated aging test data and field operation experience data, taking the historical operation data as the input of the model, and outputting a quantitative aging index or directly giving the predicted value of each material performance parameter, for example, for aluminum alloy fittings, the aging model can consider the influence of factors such as operation time, temperature cycle times, cumulative high temperature exposure time, etc. on the yield strength and electrical conductivity of the material. The correction of the material property parameters according to the material aging state can be through consulting a pre-established correction coefficient table, which can give the correction proportion or correction amount of each material property parameter relative to the initial value according to different aging indexes or aging stages, for example, if the evaluation result shows that the material is in the moderate aging stage, the thermal expansion coefficient may need to be increased by a certain proportion, while the Young's modulus and the electrical conductivity may need to be reduced by a certain proportion.

[0065] In some preferred embodiments, step S22 comprises:

[0066] S221, acquire a current environment parameter, the current environment parameter including a current wind speed, a current humidity and a current rainfall;

[0067] S222, correct the effective heat exchange coefficient and the effective heat dissipation perimeter according to the current environment parameter;

[0068] S223, calculate a temperature rise amount of the power fitting caused by the joule heat effect of the load current according to the first load current number, the resistivity, the effective heat exchange coefficient, the effective heat dissipation perimeter and the effective conduction cross-sectional area, and then calculate a second thermal stress component caused by the joule heat effect of the load current according to the temperature rise amount of the power fitting, the thermal expansion coefficient and the Young's modulus.

[0069] The current environment parameter of the embodiment refers to real-time environment state data of a position where the power fitting is located when the power fitting clamping degree is monitored. The current environment parameter can include a current wind speed, a current humidity and a current rainfall and other external factors affecting heat exchange. The current environment parameter can be acquired by deploying environment sensors (such as an anemometer, a humidity sensor and a rain gauge) near the power fitting or by acquiring real-time data provided by a local weather station. The embodiment corrects the effective convective heat exchange coefficient and the effective heat dissipation perimeter according to the current environment parameter, which refers to a process of adjusting the values of the effective convective heat exchange coefficient and the effective heat dissipation perimeter in the temperature calculation model according to the current environment parameter acquired in real time, so as to make them more consistent with the current actual environment conditions. The embodiment can correct the effective heat exchange coefficient and the effective heat dissipation perimeter according to the current environment parameter by using a method based on a preset empirical formula, a table lookup method or a physical model.

[0070] The technical solution of the present application improves the accuracy of the temperature rise and the calculation of the second thermal stress component by introducing the current environmental parameters to correct the key parameters affecting heat exchange when calculating the second thermal stress component caused by the load current joule heat effect. Specifically, step S221 obtains the current environmental parameters, which include the current wind speed, current humidity and current rainfall. These environmental parameters are important factors affecting the heat exchange efficiency between the surface of the power fitting and the surrounding environment. For example, wind speed can significantly affect the convective heat transfer intensity, and rainfall can change the surface heat exchange conditions. Step S222 corrects the effective convective heat transfer coefficient and the effective heat dissipation perimeter according to the obtained current environmental parameters. Since the effective heat transfer coefficient and the effective heat dissipation perimeter are both dynamically changed by environmental factors such as wind speed, humidity, rainfall, etc., this embodiment can correct the effective heat transfer coefficient and the effective heat dissipation perimeter used to calculate the temperature rise by correcting the effective heat transfer coefficient and the effective heat dissipation perimeter according to the current environmental parameters, so as to be closer to the actual operating environment. Step S223 calculates the temperature rise of the power fitting caused by the load current joule heat effect according to the first load current, resistivity, effective convective heat transfer coefficient corrected by environmental parameters, effective heat dissipation perimeter corrected by environmental parameters and effective current conduction cross-sectional area, and then calculates the second thermal stress component caused by the load current joule heat effect according to the calculated temperature rise of the power fitting, thermal expansion coefficient and Young's modulus. This step uses the more accurate effective convective heat transfer coefficient and effective heat dissipation perimeter corrected by environmental parameters to calculate the more accurate temperature rise of the power fitting caused by the joule heat effect in combination with other related material and current parameters, and then calculates the more accurate second thermal stress component caused by the joule heat effect based on the more accurate temperature rise in combination with the thermal expansion coefficient and Young's modulus of the material, so as to more accurately separate the stress component caused by the thermal effect from the comprehensive stress, thereby improving the accuracy of the subsequent static stress component calculation, and further effectively improving the accuracy and reliability of the clamping degree evaluation.

[0071] In one embodiment, step S221 can be implemented by installing a small weather station near the power fitting, which can integrate a wind speed sensor, a humidity sensor and a rainfall sensor, collect real-time wind speed, humidity and rainfall data, and transmit these data to the monitoring system through wireless means. Step S222 can pre-establish a correction model or lookup table based on environmental parameters. For example, for the effective convective heat transfer coefficient, a functional relationship can be established, so that its value increases with the increase of wind speed and changes in a specific way with the occurrence of rainfall; for the effective heat dissipation perimeter, the influence of the water film formed by rainfall on the surface of the fitting on the heat dissipation area can be considered for correction. When receiving real-time current environmental parameters, the monitoring system can call the model or lookup table to calculate the corrected effective convective heat transfer coefficient and effective heat dissipation perimeter according to the current wind speed, humidity and rainfall. Step S223 calculates the temperature rise of the power fitting according to the corrected effective convective heat transfer coefficient and effective heat dissipation perimeter combined with the real-time acquired first load current, the pre-set resistivity and the effective conductive cross-sectional area, and then calculates the second thermal stress component according to the temperature rise of the power fitting, the pre-set thermal expansion coefficient and the Young's modulus.

[0072] In some preferred embodiments, step S3 comprises:

[0073] S31, frequency characteristic analysis is performed on the comprehensive stress data to identify a dynamic stress component caused by external mechanical vibration and having a specific frequency range;

[0074] S32, a static stress component reflecting the clamping force of the power fitting is calculated according to the comprehensive stress data, the first thermal stress component, the second thermal stress component and the dynamic stress component.

[0075] The frequency characteristic analysis of this embodiment refers to a process of performing mathematical transformation on a signal to convert it from a time domain representation to a frequency domain representation, so as to reveal different frequency components contained in the signal and their strengths. The frequency characteristic analysis can be implemented by using Fourier transform, wavelet transform, power spectral density analysis and the like. Identifying the dynamic stress component caused by external mechanical vibration and having a specific frequency range refers to identifying the stress signal caused by external mechanical vibration from the comprehensive stress data after frequency characteristic analysis according to the frequency characteristics of the stress signal that can be generated by known or estimated external mechanical vibration (such as wind vibration and flutter). The identification can be implemented by using band-pass filtering, spectral analysis, modal analysis and the like. Calculating the static stress component reflecting the clamping force of the power fitting from the comprehensive stress data, the first thermal stress component, the second thermal stress component and the dynamic stress component refers to a process of subtracting the stress components caused by non-clamping force (including the first thermal stress component, the second thermal stress component and the dynamic stress component) that have been calculated or identified from the comprehensive stress data, so as to obtain a relatively stable stress component generated only by the clamping force of the power fitting.

[0076] The comprehensive stress data of the present application is the result of superposition of multiple factors, including static stress generated by clamping force, thermal stress generated by environmental temperature and load current, and dynamic stress generated by external mechanical vibration. After obtaining the comprehensive stress data, the first environmental temperature data and the first load current data, the first thermal stress component and the second thermal stress component are calculated according to the temperature and current data. This part of stress change is usually slow or synchronized with the environment and load change. At the same time, the stress caused by external mechanical vibration usually exhibits periodic or random fluctuations with a specific frequency range, so this embodiment can distinguish this part of rapidly changing dynamic component from other stress components and identify its size by frequency characteristic analysis of the comprehensive stress data. Finally, when calculating the static stress component reflecting the clamping force of the power fitting, not only the calculated thermal stress component is subtracted, but also the dynamic stress component identified by frequency analysis is further subtracted. In this way, the interference caused by thermal effect and vibration effect is removed from the original comprehensive stress signal, so that the static stress component calculated finally can more purely reflect the static stress level determined by the clamping state of the power fitting, thereby effectively improving the accuracy of the extraction of the clamping force related stress component, and providing a more reliable data basis for subsequent clamping degree evaluation.

[0077] In one embodiment, frequency characteristic analysis on the comprehensive stress data can employ fast Fourier transform (FFT) or wavelet transform, for example, a sequence of comprehensive stress data in a period of time is collected and subjected to FFT processing to obtain the energy distribution of the stress signal at different frequencies. According to the structural characteristics of the power transmission line and the type of the conductor and the common wind vibration and galloping mode, it is determined that the stress signal caused by these vibrations is mainly concentrated in a specific frequency range (for example, the micro-vibration may be in several hertz to several tens of hertz, and the galloping may be in several hertz to several hertz). By analyzing in the frequency domain, the energy components in these specific frequency ranges can be identified, and the corresponding time domain signal can be reconstructed or quantified as a dynamic stress component. For example, the FFT result in the specific frequency range can be integrated or summed, or a band-pass filter can be used to directly filter out the components in the frequency range from the time domain signal as the dynamic stress component. After identifying the dynamic stress component, the static stress component reflecting the clamping force of the power fitting can be calculated according to the following formula: static stress component = comprehensive stress data - first thermal stress component - second thermal stress component - dynamic stress component. This embodiment can more accurately calculate the static stress component reflecting the clamping force of the power fitting by analyzing the frequency characteristics of the comprehensive stress data to identify and remove the dynamic stress component caused by external mechanical vibration, so this embodiment can significantly reduce the influence of vibration interference on the stress monitoring result and make the extracted static stress component more truly reflect the actual clamping state of the power fitting, so that the clamping degree analysis and evaluation based on the more accurate static stress component will be more reliable, which helps to reduce false positives and false negatives, thereby effectively improving the accuracy and effectiveness of the power fitting clamping degree monitoring.

[0078] In some preferred embodiments, step S31 comprises:

[0079] S311, acquiring a current environmental parameter;

[0080] S312, determining the frequency range and amplitude characteristics of the vibration mode according to the environmental parameter, the structural characteristics of the power fitting, and the type of the power transmission conductor;

[0081] S313, performing time-frequency domain conversion on the comprehensive stress data to obtain a time-frequency domain conversion result, the time-frequency domain conversion result comprising the frequency distribution and energy distribution of the comprehensive stress data at different time points;

[0082] S314, identifying a dynamic stress component caused by external mechanical vibration and having a specific frequency range from the time-frequency domain conversion result according to the frequency range and amplitude characteristics.

[0083] The type of the power transmission conductor refers to the attribute of the power transmission conductor connected with the power hardware, which can include but is not limited to conductor material, cross-sectional area, diameter, mass per unit length, suspension mode, etc. The frequency range and amplitude characteristics of the vibration mode refer to the main frequency interval corresponding to the typical vibration form (such as wind vibration, sub-span vibration) that the power hardware-conductor system can occur under certain environmental conditions and the stress amplitude level that these vibrations can reach. The time-frequency domain conversion result refers to the two-dimensional or three-dimensional data representation obtained after time-frequency domain conversion, such as the spectrogram obtained by STFT or the scalogram obtained by wavelet transform, which can show how the frequency components of the signal change over time and their corresponding energy or intensity.

[0084] The present scheme introduces the consideration of multiple factors affecting the characteristics of external mechanical vibration and combines time-frequency domain analysis means to construct a more accurate dynamic stress component identification process. First, the current environmental parameters are obtained to provide real-time external condition information for subsequent analysis. Then, according to these environmental parameters and the inherent characteristics of the power hardware and the power transmission conductor, the vibration mode that can occur under the current working condition and its corresponding frequency and amplitude characteristics are predicted. This prediction process utilizes the response law of the system to external excitation to make the judgment of vibration stress characteristics more targeted. Subsequently, the original comprehensive stress data is converted into time and frequency domain to decompose the signal into a two-dimensional plane of time and frequency, to show the frequency composition and energy distribution of the signal at different times in detail. Finally, the frequency range and amplitude characteristics of the predetermined vibration mode are used as the basis for identification, and the signal components that meet these characteristics are accurately located and extracted in the time-frequency domain conversion result to identify the dynamic stress component caused by external mechanical vibration. This method avoids the misjudgment or omission caused by filtering only with fixed frequency range, to improve the accuracy of dynamic stress component identification. Since the embodiment can more accurately identify and remove the dynamic stress component, the embodiment can more accurately separate the static stress component reflecting the clamping force of the power hardware from the comprehensive stress data, thereby improving the reliability of the overall clamping degree monitoring.

[0085] In a specific embodiment, the current environmental parameters can be obtained by a sensor network installed on or near the power transmission line, such as a wind speed sensor, a temperature sensor, etc., to collect wind speed, ambient temperature, etc. in real time. The frequency range and amplitude characteristics of the vibration mode are determined by querying a pre-established database or model based on historical monitoring data, field tests or simulation analysis according to the environmental parameters, the structural characteristics of the power fittings and the type of the power transmission conductor, which stores the frequency range (for example, for a specific conductor and wind speed, the wind vibration frequency can be between 0.1 Hz and 3 Hz) and the approximate amplitude level of the stress vibration that may be caused by typical external mechanical vibration (such as wind vibration) under different environmental conditions (such as different wind speed levels), different fitting structures and different conductor types. The time-frequency domain conversion of the comprehensive stress data can be: using short-time Fourier transform (STFT) to divide the stress data in a period of time into multiple overlapping short-time windows, and performing Fourier transform on each window to obtain a series of time-varying frequency spectrum, thereby forming a frequency spectrum diagram. The dynamic stress component is identified from the time-frequency domain conversion result according to the frequency range and amplitude characteristics, which can be: in the obtained frequency spectrum diagram, searching for frequency components within the predetermined frequency range (for example, 0.1 Hz-3 Hz) and having energy or amplitude exceeding a certain threshold (the threshold can be determined according to the predetermined amplitude characteristics), and identifying the stress change corresponding to these components as the dynamic stress component. This embodiment can more accurately identify the dynamic stress component caused by external mechanical vibration from complex comprehensive stress signals by comprehensively considering the influence of environment, structure and conductor type on vibration characteristics and using a refined time-frequency domain analysis method, so that the precision of dynamic stress component separation is significantly improved, so that the static stress component reflecting the clamping force of the power fitting calculated subsequently is more accurate, thereby improving the reliability and accuracy of the power fitting clamping degree monitoring.

[0086] In a second aspect, as shown in Figure 2 The present application also provides a power fitting clamping degree monitoring system, which comprises:

[0087] The data acquisition module 1 is used to synchronously acquire the comprehensive stress data of the power fitting, the first ambient temperature data and the first load current data of the power transmission conductor.

[0088] The thermal stress component calculation module 2 is used to calculate the first thermal stress component caused by the change of the ambient temperature and the second thermal stress component caused by the joule heating effect of the load current according to the first ambient temperature data and the first load current data and the corresponding preset material characteristics of the power fitting.

[0089] The static stress component calculation module 3 is used to calculate the static stress component reflecting the clamping force of the power fitting according to the comprehensive stress data, the first thermal stress component and the second thermal stress component.

[0090] The clamping degree analysis module 4 is used for obtaining the current clamping degree of the power fitting according to the static stress component analysis.

[0091] The power fitting clamping degree monitoring system provided in the embodiment comprises the data acquisition module 1, the thermal stress component calculation module 2, the static stress component calculation module 3 and the clamping degree analysis module 4, and is used for executing the steps in the power fitting clamping degree monitoring method provided in the first aspect. The principle of the power fitting clamping degree monitoring system provided in the embodiment is the same as that of the power fitting clamping degree monitoring method provided in the first aspect, and will not be discussed in detail here.

[0092] As can be seen from the above, the power fitting clamping degree monitoring method and system provided in the application can effectively solve the problem of the decline in the evaluation accuracy of the clamping degree caused by the failure to extract the static stress component that can truly reflect the irreversible loosening trend of the power fitting from the stress signal collected by the stress sensor, thereby effectively avoiding the situation of causing misjudgment or false alarm caused by the evaluation accuracy of the clamping degree.

[0093] In the embodiments provided in the application, it should be understood that the disclosed devices and methods can be implemented in other manners. The above-described device embodiments are only schematic. For example, the division of the units is only a logical function division. There can be another division manner for the actual implementation. For example, a plurality of units or components can be combined or integrated into another machine, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some communication interfaces, devices or units, and can be electrical, mechanical or in other forms.

[0094] In addition, each functional module in each embodiment of the application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0095] In this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.

[0096] The above description is merely illustrative of the application and not in limitation of the principles of the application. Numerous modifications and adaptations thereof will be readily apparent to those skilled in the art without departing from the spirit and scope of the application as defined in the following claims.

Claims

1. A method for monitoring the clamping degree of electric power fittings, characterized in that: The method for monitoring the clamping degree of electric fittings comprises the following steps: S1. Synchronously obtain comprehensive stress data of power fittings, first ambient temperature data, and first load current data of transmission lines; S2. Calculate a first thermally induced stress component caused by ambient temperature change and a second thermally induced stress component caused by Joule heating effect of the load current based on the first ambient temperature data, the first load current data, and preset material properties corresponding to the electrical fittings; S3. Calculating a static stress component reflecting the clamping force of the electrical hardware according to the comprehensive stress data, the first thermally induced stress component, and the second thermally induced stress component; S4, according to the static stress component analysis to obtain the current clamping degree of the power fittings; The preset material properties include thermal expansion coefficient, Young's modulus, resistivity, effective heat transfer coefficient, effective heat dissipation perimeter and effective conductive cross-sectional area. Step S2 includes: S21, calculating a temperature difference based on the first ambient temperature data and a preset reference temperature, and then calculating a first thermally induced stress component caused by the ambient temperature change based on the temperature difference, the thermal expansion coefficient, and the Young's modulus; S22. Calculate a temperature rise of the electrical hardware caused by the Joule heating effect of the load current based on the first load current, the resistivity, the effective heat transfer coefficient, the effective heat dissipation perimeter, and the effective conductive cross-sectional area, and then calculate a second thermally induced stress component caused by the Joule heating effect of the load current based on the temperature rise of the electrical hardware, the thermal expansion coefficient, and the Young's modulus. The calculation formula of the first thermally induced stress component is: ; Wherein, thermal_env represents the first thermal stress component, k_env represents the preset environmental thermal stress calibration factor, E represents Young's modulus, α represents the thermal expansion coefficient, T ref Indicates the preset reference temperature, T env represents the first ambient temperature data, and the calculation formula for the temperature rise of the electrical fitting is: ;in, represents the temperature rise of the electrical fitting, k_joule_temp represents the preset Joule heat temperature rise calibration factor, I_load represents the first load current data, ρ represents the resistivity, h_eff represents the effective heat transfer coefficient, P_eff represents the effective heat dissipation perimeter, A_eff represents the effective conductive cross-sectional area, and the calculation formula for the second thermally induced stress component is: ; Where thermal_joule represents the second thermally induced stress component, and k_joule_stress represents the preset Joule thermal stress calibration factor.

2. The method for monitoring the clamping degree of electric power fittings according to claim 1, characterized in that: Step S1 includes: S11, synchronously obtaining comprehensive stress data of the power fitting, first ambient temperature data, and first load current data of the transmission line; S12. Preprocess the comprehensive stress data, the first ambient temperature data, and the first load current data, wherein the preprocessing includes signal conditioning and drift compensation.

3. The method for monitoring the clamping degree of electric power fittings according to claim 2, characterized in that: Step S11 includes: S111, synchronously acquiring first ambient temperature data, first load current data of the transmission line, and first local stress data corresponding to different stress collection positions on the power fitting; S112: Generate comprehensive stress data based on all of the first local stress data according to the stress collection position corresponding to the first local stress data and the structural characteristics of the electrical hardware.

4. The method for monitoring the clamping degree of electric power fittings according to claim 3, characterized in that: Step S112 includes: A1. Obtaining second ambient temperature data, second load current data, and a second local stress data set of the electrical hardware during an initial operation phase, wherein the second local stress data set includes second local stress data corresponding to different stress collection positions on the electrical hardware; A2. Analyze and obtain response characteristics of each stress collection location based on the second local stress data set, the second ambient temperature data, and the second load current data; A3. Determine the weight corresponding to each of the first local stress data according to the response characteristics of each of the stress collection positions and the structural characteristics of the electrical hardware; A4. Perform weighted averaging on all the first local stress data and their corresponding weights to obtain comprehensive stress data.

5. The method for monitoring the clamping degree of electric power fittings according to claim 1, characterized in that: Step S2 also includes the following steps performed before step S21: B1. Obtaining historical operating data of the electrical fittings; B2. evaluating the material aging status of the electrical fittings based on the historical operating data; B3. Correct the thermal expansion coefficient, the Young's modulus, the resistivity, the effective heat transfer coefficient, the effective heat dissipation perimeter, and the effective conductive cross-sectional area according to the aging state of the material.

6. The method for monitoring the clamping degree of electric power fittings according to claim 5, characterized in that: Step S22 includes: S221. Acquire current environmental parameters, where the current environmental parameters include current wind speed, current humidity, and current rainfall; S222. Correct the effective heat transfer coefficient and the effective heat dissipation perimeter according to the current environmental parameters; S223. Calculate the temperature rise of the electrical hardware caused by the Joule heating effect of the load current based on the first load current data, the resistivity, the effective heat transfer coefficient, the effective heat dissipation perimeter, and the effective conductive cross-sectional area. Then, calculate the second thermally induced stress component caused by the Joule heating effect of the load current based on the temperature rise of the electrical hardware, the thermal expansion coefficient, and the Young's modulus.

7. The method for monitoring the clamping degree of electric power fittings according to claim 1, characterized in that: Step S3 includes: S31. Performing frequency characteristic analysis on the comprehensive stress data to identify a dynamic stress component caused by external mechanical vibration and having a specific frequency range, where the specific frequency range is 0.1 Hz-3 Hz; S32. Calculate a static stress component reflecting the clamping force of the electrical hardware according to the comprehensive stress data, the first thermally induced stress component, the second thermally induced stress component, and the dynamic stress component.

8. The method for monitoring the clamping degree of electric power fittings according to claim 7, characterized in that: Step S31 includes: S311, obtaining current environment parameters; S312. Determine the frequency range and amplitude characteristics of the vibration mode according to the environmental parameters, the structural characteristics of the power fittings, and the type of the transmission line; S313, performing time-frequency domain conversion on the comprehensive stress data to obtain a time-frequency domain conversion result, wherein the time-frequency domain conversion result includes frequency distribution and energy distribution of the comprehensive stress data at different time points; S314 . Identify a dynamic stress component with a specific frequency range caused by external mechanical vibration from the time-frequency domain conversion result according to the frequency range and the amplitude characteristics.

9. An electric power fitting clamping degree monitoring system, characterized in that: The electric power fitting clamping degree monitoring system comprises: A data acquisition module, configured to synchronously acquire comprehensive stress data of the power fittings, first ambient temperature data, and first load current data of the transmission conductor; a thermally induced stress component calculation module, configured to calculate a first thermally induced stress component caused by ambient temperature change and a second thermally induced stress component caused by Joule heating effect of the load current based on the first ambient temperature data, the first load current data, and preset material properties corresponding to the electrical fitting; a static stress component calculation module, configured to calculate a static stress component reflecting the clamping force of the electrical fitting based on the comprehensive stress data, the first thermally induced stress component, and the second thermally induced stress component; A clamping degree analysis module for obtaining the current clamping degree of the power fittings based on the static stress component analysis; The preset material properties include thermal expansion coefficient, Young's modulus, resistivity, effective heat transfer coefficient, effective heat dissipation perimeter, and effective conductive cross-sectional area. The process of calculating the first thermally induced stress component caused by ambient temperature change and the second thermally induced stress component caused by Joule heating effect of the load current based on the first ambient temperature data, the first load current data, and the preset material properties corresponding to the electrical hardware includes: S21, calculating a temperature difference based on the first ambient temperature data and a preset reference temperature, and then calculating a first thermally induced stress component caused by the ambient temperature change based on the temperature difference, the thermal expansion coefficient, and the Young's modulus; S22. Calculate a temperature rise of the electrical hardware caused by the Joule heating effect of the load current based on the first load current, the resistivity, the effective heat transfer coefficient, the effective heat dissipation perimeter, and the effective conductive cross-sectional area, and then calculate a second thermally induced stress component caused by the Joule heating effect of the load current based on the temperature rise of the electrical hardware, the thermal expansion coefficient, and the Young's modulus. The calculation formula of the first thermally induced stress component is: ; Wherein, thermal_env represents the first thermal stress component, k_env represents the preset environmental thermal stress calibration factor, E represents Young's modulus, α represents the thermal expansion coefficient, T ref Indicates the preset reference temperature, T env represents the first ambient temperature data, and the calculation formula for the temperature rise of the electrical fitting is: ;in, represents the temperature rise of the electrical fitting, k_joule_temp represents the preset Joule heat temperature rise calibration factor, I_load represents the first load current data, ρ represents the resistivity, h_eff represents the effective heat transfer coefficient, P_eff represents the effective heat dissipation perimeter, A_eff represents the effective conductive cross-sectional area, and the calculation formula for the second thermally induced stress component is: ; Where thermal_joule represents the second thermally induced stress component, and k_joule_stress represents the preset Joule thermal stress calibration factor.

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