Intelligent detection control method, system and equipment for strain clamp and medium

Abstract

The invention belongs to the technical field of strain clamp detection control, and discloses a strain clamp intelligent detection control method, system and device and a medium, and the method comprises the steps: dynamically regulating and controlling the detection data collection frequency of a strain clamp according to an installation environment and a use state; determining a risk judgment threshold value of the strain clamp and outputting a fault early warning information standard based on the detection data acquisition frequency; acquiring use process data of the strain clamp according to the detection data acquisition frequency, and processing the use process data based on the risk judgment threshold and the strain clamp state analysis model to obtain a state judgment index of the strain clamp and output fault early warning information; and performing secondary analysis on the use process data of the strain clamp based on the state judgment index and the output fault early warning information, and determining fault information of the strain clamp according to an analysis result. According to the invention, the effectiveness of data acquisition is ensured, system resources are saved, and the response speed and resource consumption of the system are effectively balanced.

Description

Technical Field

[0001] The present invention relates to the technical field of detection and control of tension clamps, and in particular to an intelligent detection and control method, system, equipment and medium for tension clamps. Background Art

[0002] Strain clamps are mainly used for corner, splice and terminal connections, and serve as anchors to fix high-voltage lines or lightning conductors to the tension insulator strings of non-straight towers. They are also used to fix the guy wires of guy towers. At present, the inspection of strain clamps is mainly done by manpower, with inspectors carrying inspection equipment and climbing poles to inspect the clamps on each high-voltage line in turn.

[0003] For example, Chinese patent CN117420752B discloses a control system and control method for a tension clamp detection robot, including an Arduino controller and a host computer. The host computer includes a position following system, which controls the tension clamp detection robot through PID combined with RBF neural network. The Arduino controller receives control instructions from the host computer and outputs them to the tension clamp detection robot, controls the start and stop of the tension clamp robot, the sliding of the walking wheels along the high-voltage line, the movement of the guide rail slide along the detection guide rail, and the rotation of the tension clamp detection module; it also collects and processes images taken by the tension clamp detection module and data returned by the sensor, and transmits them to the host computer through wireless transmission.

[0004] However, the above detection and control system is not convenient for optimizing the control detection strategy in real time according to the actual situation, and cannot effectively reduce the false alarm and missed alarm of the equipment, and thus cannot effectively ensure the stability and safety of line operation.

[0005] Therefore, how to provide a method, system, equipment and medium for intelligent detection and control of tension clamps is a problem that needs to be solved urgently. Summary of the invention

[0006] The embodiments of the present invention provide a method, system, device and medium for intelligent detection and control of a tension clamp, so as to solve the problem in the prior art that it is inconvenient to optimize the control and detection strategy in real time according to actual conditions.

[0007] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended to be a general review, nor is it intended to identify key / important components or to delineate the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0008] According to a first aspect of an embodiment of the present invention, a method for intelligent detection and control of a tension clamp is provided.

[0009] In one embodiment, a method for intelligent detection and control of a tension clamp includes:

[0010] Dynamically adjust the detection data collection frequency of the tension clamp according to the installation environment and usage status, and determine the risk judgment threshold and output fault warning information standard of the tension clamp based on the detection data collection frequency;

[0011] The use process data of the tension clamp is collected according to the detection data collection frequency, and the use process data is processed based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information;

[0012] Based on the state judgment index and the output fault warning information, the usage process data of the tension clamp is secondary analyzed, and the fault information of the tension clamp is determined according to the analysis results.

[0013] In one embodiment, dynamically adjusting the detection data collection frequency of the tension clamp according to the installation environment and the usage status, and determining the risk determination threshold and output fault warning information standard of the tension clamp based on the detection data collection frequency include:

[0014] Determine the installation environment information of the tension clamp based on the environmental sensor, and obtain the current, tension and vibration amplitude of the tension clamp when it is in use based on the multi-source sensor data;

[0015] Determine the load value of the tension clamp according to the current, tension and vibration amplitude, calculate the data acquisition frequency adjustment coefficient based on the installation environment information, and obtain the upper and lower limits of the acquisition frequency in the historical detection process;

[0016] Dynamically adjust the detection data collection frequency of the tension clamp based on the upper and lower limits of the collection frequency and the data collection frequency adjustment coefficient;

[0017] The risk judgment threshold during the detection of the tension clamp is adjusted according to the detection data collection frequency adjustment coefficient and the installation environment information, and the output fault warning information is determined based on the risk judgment threshold and the surface temperature of the tension clamp.

[0018] In one embodiment, the risk determination threshold value during the detection of the tension clamp is adjusted according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and the output fault warning information is determined based on the risk determination threshold value and the surface temperature of the tension clamp, including:

[0019] The detection data collection frequency adjustment coefficient is compared with the fault threshold. When the detection data collection frequency adjustment coefficient is greater than or equal to the fault threshold, a pre-set safety boundary is directly extracted from the database as a risk determination threshold;

[0020] When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk determination threshold;

[0021] The surface temperature and actual vibration amplitude of the tension clamp are obtained, and the fault warning information of the tension clamp is output by combining the temperature risk threshold and the vibration risk threshold.

[0022] In one embodiment, when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, obtaining the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp based on the installation environment information of the tension clamp as the risk determination threshold includes:

[0023] When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the installation environment information of the tension clamp and the tension clamp current are combined into temperature threshold matching data;

[0024] Based on the Euclidean distance calculation technology, the temperature threshold matching data is compared with the temperature threshold pointing data pre-stored in the database, and the matching temperature risk threshold corresponding to the optimal temperature threshold pointing data is selected according to the comparison result as the temperature risk threshold after the detection data collection frequency is adjusted;

[0025] Based on the installation environment information of the tension clamp, the tension and stress data of the tension clamp are combined as vibration threshold matching data, and the vibration threshold matching data is compared with the vibration threshold pointing data pre-stored in the database by using the Euclidean distance calculation technology to obtain the vibration comparison result;

[0026] Based on the vibration comparison results, the matching vibration amplitude risk threshold corresponding to the optimal vibration threshold pointing data is selected as the vibration risk threshold after the detection data acquisition frequency is adjusted.

[0027] In one embodiment, the use process data of the tension clamp is collected according to the detection data collection frequency, and the use process data is processed based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information including:

[0028] Based on the detection data collection frequency, data collection is performed on the use process of the tension clamp, and the use process data of the tension clamp is obtained according to the collection results, and the parameter change data of the tension clamp set in the database is obtained;

[0029] The parameter change data of the tension clamp is compared with the use process data of the tension clamp, and the change state allowable deviation data is obtained according to the comparison result. Based on the state analysis model of the tension clamp, the use process data, the parameter change data of the tension clamp and the change state allowable deviation data are processed to obtain the state judgment index of the tension clamp;

[0030] The surface temperature and actual vibration amplitude of the tension clamp during process data collection are determined based on environmental sensors, and the surface temperature and actual vibration amplitude are compared with the risk judgment threshold to obtain the output fault warning information of the tension clamp.

[0031] In one embodiment, secondary analysis is performed on the use process data of the tension clamp based on the state determination index and the output fault warning information, and the fault information of the tension clamp is determined according to the analysis result, including:

[0032] When both the state judgment index and the output fault warning information meet the preset requirements, the use state of the tension clamp is defined as stable;

[0033] When the state judgment index and the output fault warning information do not meet the preset requirements, the use process data of the tension clamp are compared with the fault parameter data preset in the database, and the tension clamp fault parameter data that best matches the use process data of the tension clamp is determined based on the comparison result;

[0034] The fault type of the tension clamp is analyzed based on the parameter data when the tension clamp fails, and the fault information of the tension clamp is determined according to the fault type.

[0035] According to a second aspect of an embodiment of the present invention, a tension clamp intelligent detection and control system is provided.

[0036] In one embodiment, the intelligent detection and control system for tension clamps includes:

[0037] An intelligent detection pre-processing unit is used to dynamically adjust the detection data collection frequency of the tension clamp according to the installation environment and usage status, and determine the risk judgment threshold of the tension clamp and the output fault warning information standard based on the detection data collection frequency;

[0038] The state fault detection output unit is used to collect the use process data of the tension clamp according to the detection data collection frequency, and process the use process data based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information;

[0039] The fault information analysis and determination unit is used to perform secondary analysis on the use process data of the tension clamp based on the state judgment index and the output fault warning information, and determine the fault information of the tension clamp according to the analysis result.

[0040] In one embodiment, the intelligent detection pre-processing unit includes:

[0041] A data acquisition definition module is used to determine the installation environment information of the tension clamp based on the environmental sensor, and to obtain the current, tension and vibration amplitude of the tension clamp when it is in use based on the multi-source sensor data;

[0042] The limit value acquisition and determination module is used to determine the load value of the tension clamp according to the current, tension and vibration amplitude, calculate the data acquisition frequency adjustment coefficient in combination with the installation environment information, and obtain the upper and lower limits of the acquisition frequency in the historical detection process;

[0043] A detection data acquisition frequency adjustment module is used to dynamically adjust the detection data acquisition frequency of the tension clamp based on the upper and lower limits of the acquisition frequency and the data acquisition frequency adjustment coefficient;

[0044] The threshold fault determination output module is used to adjust the risk judgment threshold during the tension clamp detection according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and output fault warning information based on the risk judgment threshold and the surface temperature of the tension clamp.

[0045] In one embodiment, the threshold fault determination output module adjusts the risk judgment threshold during the detection of the tension clamp according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and determines the output fault warning information based on the risk judgment threshold and the surface temperature of the tension clamp. The detection data acquisition frequency adjustment coefficient can be compared with the fault threshold. When the detection data acquisition frequency adjustment coefficient is greater than or equal to the fault threshold, a pre-set safety boundary is directly extracted from the database as the risk judgment threshold; when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk judgment threshold; the surface temperature and actual vibration amplitude of the tension clamp are obtained, and the fault warning information of the tension clamp is output in combination with the temperature risk threshold and the vibration risk threshold.

[0046] In one embodiment, when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, obtaining the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp based on the installation environment information of the tension clamp as the risk determination threshold includes:

[0047] When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the installation environment information of the tension clamp and the tension clamp current are combined into temperature threshold matching data;

[0048] Based on the Euclidean distance calculation technology, the temperature threshold matching data is compared with the temperature threshold pointing data pre-stored in the database, and the matching temperature risk threshold corresponding to the optimal temperature threshold pointing data is selected according to the comparison result as the temperature risk threshold after the detection data collection frequency is adjusted;

[0049] Based on the installation environment information of the tension clamp, the tension and stress data of the tension clamp are combined as vibration threshold matching data, and the vibration threshold matching data is compared with the vibration threshold pointing data pre-stored in the database by using the Euclidean distance calculation technology to obtain the vibration comparison result;

[0050] Based on the vibration comparison results, the matching vibration amplitude risk threshold corresponding to the optimal vibration threshold pointing data is selected as the vibration risk threshold after the detection data acquisition frequency is adjusted.

[0051] In one embodiment, the status fault detection output unit includes:

[0052] The use process data acquisition module is used to collect data on the use process of the tension clamp based on the detection data acquisition frequency, obtain the use process data of the tension clamp according to the acquisition results, and obtain the tension clamp parameter change data set in the database;

[0053] The state judgment index analysis module is used to compare the parameter change data of the tension clamp with the use process data of the tension clamp, obtain the change state allowable deviation data according to the comparison result, and process the use process data, the parameter change data of the tension clamp and the change state allowable deviation data based on the tension clamp state analysis model to obtain the state judgment index of the tension clamp;

[0054] The fault warning information output module is used to determine the surface temperature and actual vibration amplitude of the tension clamp when using process data collection based on the environmental sensor, and compare the surface temperature and actual vibration amplitude with the risk judgment threshold to obtain the output fault warning information of the tension clamp.

[0055] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0056] In one embodiment, the computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0057] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0058] In one embodiment, the computer-readable storage medium stores a computer program, and the computer program implements the steps of the above method when executed by a processor.

[0059] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0060] 1. The present invention dynamically adjusts the data collection frequency according to the environment in which the tension clamp is located and its load, dynamically controls the risk assessment threshold and the data processing method, can optimize the control detection strategy in real time according to the actual situation, can effectively reduce the false alarm and missed alarm phenomenon of the equipment, and thus ensure the stability and safety of the line operation, and can solve the problem that traditional detection methods are difficult to effectively respond to changes in the environment and usage status.

[0061] 2. The present invention can adjust the frequency of data collection. When the load is heavy or the environment is complex, the collection frequency can be increased to ensure that key data is not missed. In a relatively stable environment, the collection frequency can be appropriately reduced, which not only ensures the effectiveness of data collection but also saves system resources, effectively balancing the system's response speed and resource consumption.

[0062] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0064] Figure 1 is a flow chart showing a method for intelligent detection and control of a tension clamp according to an exemplary embodiment;

[0065] Figure 2 is a principle block diagram of an intelligent detection and control system for a tension clamp according to an exemplary embodiment;

[0066] Figure 3 The figure is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0067] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0068] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0069] As used herein, the term "plurality" means two or more than two, unless otherwise specified.

[0070] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0071] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0072] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0073] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can 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 modules.

[0074] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0075] Figure 1An embodiment of the intelligent detection and control method of the tension clamp of the present invention is shown.

[0076] In this optional embodiment, the intelligent detection and control method of the tension clamp includes:

[0077] Step S101, dynamically adjusting the detection data collection frequency of the tension clamp according to the installation environment and the use status, and determining the risk determination threshold and output fault warning information standard of the tension clamp based on the detection data collection frequency;

[0078] Step S103, collecting the use process data of the tension clamp according to the detection data collection frequency, and processing the use process data based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information;

[0079] Step S105, performing a secondary analysis on the use process data of the tension clamp based on the state determination index and the output fault warning information, and determining the fault information of the tension clamp according to the analysis result.

[0080] In this optional embodiment, when the detection data collection frequency of the strain clamp is dynamically regulated according to the installation environment and usage status, and the risk judgment threshold and output fault warning information standard of the strain clamp are determined based on the detection data collection frequency, the installation environment information of the strain clamp can be determined based on the environmental sensor, and the current, tension and vibration amplitude of the strain clamp when it is in use can be obtained based on the multi-source sensor data; the load value of the strain clamp is determined based on the current, tension and vibration amplitude, and the data collection frequency adjustment coefficient is calculated in combination with the installation environment information, and the upper and lower limits of the collection frequency in the historical detection process are obtained; the detection data collection frequency of the strain clamp is dynamically regulated based on the upper and lower limits of the collection frequency and the data collection frequency adjustment coefficient; the risk judgment threshold during the detection of the strain clamp is adjusted according to the detection data collection frequency adjustment coefficient and the installation environment information, and the output fault warning information is determined based on the risk judgment threshold and the surface temperature of the strain clamp.

[0081] In this optional embodiment, when the risk judgment threshold during the detection of the tension clamp is adjusted according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and when the output fault warning information is determined based on the risk judgment threshold and the surface temperature of the tension clamp, the detection data acquisition frequency adjustment coefficient can be compared with the fault threshold. When the detection data acquisition frequency adjustment coefficient is greater than or equal to the fault threshold, the pre-set safety boundary is directly extracted from the database as the risk judgment threshold; when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk judgment threshold; the surface temperature and the actual vibration amplitude of the tension clamp are obtained, and the fault warning information of the tension clamp is output in combination with the temperature risk threshold and the vibration risk threshold.

[0082] In this optional embodiment, when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and vibration risk threshold during the tension clamp detection are obtained based on the installation environment information of the tension clamp as the risk judgment threshold. When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the installation environment information of the tension clamp and the tension clamp current are combined into temperature threshold matching data; based on the Euclidean distance calculation technology, the temperature threshold matching data are compared with the temperature threshold pointing data pre-stored in the database, and the matching temperature risk threshold corresponding to the optimal temperature threshold pointing data is selected according to the comparison result as the temperature risk threshold after the detection data acquisition frequency is adjusted; based on the installation environment information of the tension clamp, the tension and stress data of the tension clamp are combined as vibration threshold matching data, and the Euclidean distance calculation technology is used to compare the vibration threshold matching data with the vibration threshold pointing data pre-stored in the database to obtain the vibration comparison result; based on the vibration comparison result, the matching vibration amplitude risk threshold corresponding to the optimal vibration threshold pointing data is selected as the vibration risk threshold after the detection data acquisition frequency is adjusted.

[0083] In this optional embodiment, when the usage process data of the strain clamp is collected according to the detection data collection frequency, and the usage process data is processed based on the risk judgment threshold and the strain clamp state analysis model to obtain the state judgment index and output fault warning information of the strain clamp, data collection can be performed on the usage process of the strain clamp based on the detection data collection frequency, and the usage process data of the strain clamp is obtained according to the collection results, and the tension clamp parameter change data set in the database is obtained; the tension clamp parameter change data is compared with the usage process data of the strain clamp, and the change state allowable deviation data is obtained according to the comparison result, and the usage process data, the tension clamp parameter change data and the change state allowable deviation data are processed based on the tension clamp state analysis model to obtain the state judgment index of the tension clamp; the surface temperature and actual vibration amplitude of the tension clamp when the usage process data is collected are determined based on the environmental sensor, and the surface temperature and the actual vibration amplitude are respectively compared with the risk judgment threshold to obtain the output fault warning information of the tension clamp.

[0084] In this optional embodiment, based on the state determination index and the output fault warning information, the use process data of the strain clamp is secondary analyzed, and the fault information of the strain clamp is determined according to the analysis result. When the state determination index and the output fault warning information both meet the preset requirements, the use state of the strain clamp can be defined as stable; when the state determination index and the output fault warning information do not meet the preset requirements, the use process data of the strain clamp is compared with the fault parameter data preset in the database, and the strain clamp fault parameter data that best matches the use process data of the strain clamp is determined based on the comparison result; the fault type of the strain clamp is analyzed based on the strain clamp fault parameter data, and the fault information of the strain clamp is determined according to the fault type.

[0085] Figure 2 An embodiment of an intelligent detection and control system for a tension clamp of the present invention is shown.

[0086] In this optional embodiment, the intelligent detection and control system for the tension clamp includes:

[0087] The intelligent detection pre-processing unit 201 is used to dynamically adjust the detection data collection frequency of the tension clamp according to the installation environment and the use status, and determine the risk judgment threshold and output fault warning information standard of the tension clamp based on the detection data collection frequency;

[0088] The state fault detection output unit 203 is used to collect the use process data of the tension clamp according to the detection data collection frequency, and process the use process data based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information;

[0089] The fault information analysis and determination unit 205 is used to perform a secondary analysis on the use process data of the tension clamp based on the state determination index and the output fault warning information, and determine the fault information of the tension clamp according to the analysis result.

[0090] In this optional embodiment, the intelligent detection pre-processing unit 201 includes a data acquisition definition module (not shown in the figure), a limit acquisition determination module (not shown in the figure), a detection data acquisition frequency adjustment module (not shown in the figure) and a threshold fault determination output module (not shown in the figure), wherein:

[0091] A data acquisition definition module is used to determine the installation environment information of the strain clamp based on environmental sensors, and to obtain the current, tension and vibration amplitude of the strain clamp when it is in use based on multi-source sensor data; a limit acquisition determination module is used to determine the load value of the strain clamp based on the current, tension and vibration amplitude, calculate the data acquisition frequency adjustment coefficient in combination with the installation environment information, and obtain the upper and lower limits of the acquisition frequency in the historical detection process; a detection data acquisition frequency adjustment module is used to dynamically control the detection data acquisition frequency of the strain clamp based on the upper and lower limits of the acquisition frequency and the data acquisition frequency adjustment coefficient; a threshold fault determination output module is used to adjust the risk judgment threshold during the detection of the strain clamp based on the detection data acquisition frequency adjustment coefficient and the installation environment information, and output fault warning information based on the risk judgment threshold and the surface temperature of the strain clamp.

[0092] In this optional embodiment, the threshold fault determination output module adjusts the risk judgment threshold during the detection of the tension clamp according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and determines the output fault warning information based on the risk judgment threshold and the surface temperature of the tension clamp. The detection data acquisition frequency adjustment coefficient can be compared with the fault threshold. When the detection data acquisition frequency adjustment coefficient is greater than or equal to the fault threshold, a pre-set safety boundary is directly extracted from the database as the risk judgment threshold; when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk judgment threshold; the surface temperature and actual vibration amplitude of the tension clamp are obtained, and the tension clamp fault warning information is output in combination with the temperature risk threshold and the vibration risk threshold.

[0093] In this optional embodiment, when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk judgment threshold, including: when the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the installation environment information of the tension clamp and the tension clamp current are combined into temperature threshold matching data; based on the Euclidean distance calculation technology, the temperature threshold matching data are compared with the temperature threshold pointing data pre-stored in the database, and the matching temperature risk threshold corresponding to the optimal temperature threshold pointing data is selected according to the comparison result as the temperature risk threshold after the detection data acquisition frequency is adjusted; based on the installation environment information of the tension clamp, the tension and stress data of the tension clamp are combined as vibration threshold matching data, and the Euclidean distance calculation technology is used to compare the vibration threshold matching data with the vibration threshold pointing data pre-stored in the database to obtain a vibration comparison result; based on the vibration comparison result, the matching vibration amplitude risk threshold corresponding to the optimal vibration threshold pointing data is selected as the vibration risk threshold after the detection data acquisition frequency is adjusted.

[0094] In this optional embodiment, the state fault detection output unit 203 includes a use process data acquisition module (not shown in the figure), a state determination index analysis module (not shown in the figure) and a fault warning information output module (not shown in the figure), wherein:

[0095] The use process data acquisition module is used to collect data on the use process of the tension clamp based on the detection data collection frequency, obtain the use process data of the tension clamp according to the collection results, and obtain the tension clamp parameter change data set in the database; the state judgment index analysis module is used to compare the tension clamp parameter change data with the use process data of the tension clamp, obtain the change state allowable deviation data according to the comparison result, and process the use process data, the tension clamp parameter change data and the change state allowable deviation data based on the tension clamp state analysis model to obtain the state judgment index of the tension clamp; the fault warning information output module is used to determine the surface temperature and actual vibration amplitude of the tension clamp when the use process data is collected based on the environmental sensor, and compare the surface temperature and the actual vibration amplitude with the risk judgment threshold respectively to obtain the output fault warning information of the tension clamp.

[0096] In this embodiment, a method for intelligent detection and control of tension clamps is proposed for tension clamps. The main steps are divided into four steps, including dynamic adjustment of acquisition frequency, adjustment of risk assessment threshold, acquisition of detection data and adjustment of detection data processing method. By dynamically adjusting the data acquisition frequency, risk assessment threshold and data processing method, the method can optimize and adjust the detection strategy in real time according to the actual situation, thereby improving the accuracy and timeliness of fault warning, effectively reducing the false alarm and missed alarm of the equipment, ensuring the stability and safety of line operation, and solving the problem that it is difficult to effectively cope with changes in the environment and usage status in traditional detection methods. The details are as follows:

[0097] Step 1: Dynamic adjustment of the acquisition frequency is used to dynamically adjust the data acquisition frequency when the tension clamp is detected based on the environment in which the tension clamp is located and the use status of the tension clamp. The frequency of data acquisition is adjusted according to the environment and use status of the tension clamp. For situations with heavy loads or complex environments, the acquisition frequency can be increased to ensure that key data is not missed. In a relatively stable environment, the acquisition frequency can be appropriately reduced to save system resources. The benefit of dynamically adjusting the acquisition frequency is to balance the system's response speed and resource consumption;

[0098] The process of determining the data acquisition frequency adjustment coefficient is as follows: determining the environmental data of the tension clamp based on the integrated environmental sensor, the environmental data of the tension clamp including the ambient temperature, ambient humidity and ambient wind speed; obtaining the load of the tension clamp when the tension clamp is in use, wherein the load of the tension clamp when the tension clamp is in use is obtained based on multi-source sensor data, the multi-source sensor data including the tension clamp current, the tension clamp tension and the vibration amplitude of the tension clamp; determining the data acquisition frequency adjustment coefficient based on the environmental data of the tension clamp and the load of the tension clamp when the tension clamp is in use.

[0099] The steps of determining the data acquisition frequency adjustment coefficient are as follows: obtaining the environmental parameter data of the tension clamp stored in the database, wherein the environmental parameter data of the tension clamp includes the parameterized environmental temperature cT, the parameterized environmental humidity cD, and the parameterized environmental wind speed cF; obtaining the maximum defined current cR of the tension clamp, the maximum defined tension cZ of the tension clamp, and the maximum defined vibration amplitude cY of the tension clamp stored in the database;

[0100] The calculation formula of data acquisition frequency adjustment coefficient is:

[0101]

[0102] Wherein, A represents the data acquisition frequency adjustment coefficient, sT represents the ambient temperature, cT represents the reference ambient temperature, sD represents the ambient humidity, cD represents the reference ambient humidity, cF represents the reference ambient wind speed, sF represents the ambient wind speed, sL represents the load of the tension clamp, α1 represents the weight factor of the ambient temperature deviation, α2 represents the weight factor of the ambient humidity, α3 represents the weight factor of the ambient wind speed, α4 represents the weight factor of the load of the tension clamp, sR represents the current of the tension clamp, sZ represents the tension of the tension clamp, and sY represents the load of the tension clamp. Vibration amplitude, cR represents the maximum limiting current of the tension clamp, cZ represents the maximum limiting tension of the tension clamp, cY represents the maximum limiting vibration amplitude of the tension clamp, β1 represents the weight factor of the tension clamp current, β2 represents the weight factor of the tension clamp tension, β3 represents the weight factor of the vibration amplitude of the tension clamp, α1+α2+α3+α4=1, β1+β2+β3=1, α1, α2, α3, α4, β1, β2, β3 are all directly obtained from the database, and these weight factors can be determined using the objective assignment method.

[0103] The temperature change is measured by calculating |sT - cT|. The temperature fluctuation directly affects the operating safety of the clamp. Therefore, when the temperature deviation is large, this item will increase the value of A, thereby increasing the acquisition frequency, which can effectively cope with the situation of high temperature or drastic temperature changes and improve the monitoring sensitivity. Humidity and wind speed also play important roles in the system operation. For example, the increase in humidity may accelerate corrosion or insulation degradation, while the wind speed affects vibration. Therefore, the ratios of sD and sF to the reference values are used to reflect the deviation. When the humidity or wind speed changes significantly, these two items will amplify A, prompting the acquisition frequency to increase. Through the proportional deviation design, the system can sensitively capture the influence of different environmental factors. The load change will directly affect the working load and safety of the clamp. sL is used to measure A, so that when the load increases, the value of A will be automatically increased, thereby increasing the acquisition frequency, enabling the system to sensitively respond to the load change, especially strengthening the detection intensity under high-load conditions.

[0104] The sL of the strain clamp is obtained by weighted calculation of the deviations of sR, sZ, and sY. All of these three directly affect the working state and fatigue degree of the strain clamp. Unified calculation can more comprehensively evaluate the load situation. The weight factor depends on the importance of each factor. For example, when the influence of vibration on the system is large, the value of β3 can be appropriately increased. The system can automatically adapt to different influencing factors in different working conditions, improve the flexibility and adaptability of detection, obtain the maximum acquisition frequency and the minimum acquisition frequency of the data stored in the database, and adjust the data acquisition frequency when detecting the strain clamp in combination with the data acquisition frequency adjustment coefficient.

[0105] The dynamic regulation method of the data acquisition frequency is as follows:

[0106]

[0107] In the formula, f c represents the data acquisition frequency after dynamic regulation, f max represents the maximum data acquisition frequency, and f min represents the minimum data acquisition frequency.

[0108] Under normal circumstances, since α1 + α2 + α3 + α4 = 1 and β1 + β2 + β3 = 1, the calculation result of A will be normalized between 0 and 1. However, when there are abnormal situations, a certain parameter will increase abnormally, resulting in A being greater than 1. When 0 < A ≤ 10, the acquisition frequency increases linearly with A between f max and f min . In this way, when the environmental or load deviation is not large, the system can flexibly adjust the acquisition frequency between the maximum and minimum frequencies, achieving a balance between accuracy and resource consumption. Set f max and f minrange, which can prevent the frequency from being too high or too low, causing waste of system resources or insufficient data. At the same time, this design ensures that the system automatically adjusts the frequency within a safe range, enhancing the stability of the overall operation.

[0109] When A>1, the acquisition frequency is directly set to the maximum value f max This design is used to respond to emergencies (such as significant deterioration of environmental conditions or excessive load). It monitors data in real time at high frequencies to capture possible signs of faults in a timely manner. Each parameter reflects different aspects of the clamp. For example, temperature has a significant impact on the physical properties and current carrying capacity of the tension clamp material. High temperature may accelerate the aging of the clamp material and even cause thermal fatigue, reducing its mechanical strength. Therefore, temperature change is an important reference data in the detection process. Tension represents the stress of the tension clamp under the weight of the cable and wind load. Increased tension will aggravate the mechanical fatigue of the clamp and may cause physical deformation or loosening. Therefore, tension change is an important parameter reflecting the load state. Wind speed has a greater impact on the vibration of the tension clamp. Especially under high wind speed conditions, the clamp will be affected by wind-induced vibration, resulting in an increase in its vibration frequency and amplitude. This vibration will aggravate the fatigue and wear of the clamp, thereby increasing the risk of failure.

[0110] Through weighted combined calculation, the acquisition frequency can be intelligently adjusted according to different environmental and load conditions. When parameters change drastically, the acquisition frequency can be increased, and when conditions are stable, the frequency can be reduced, which not only ensures detection accuracy but also optimizes resource consumption.

[0111] Step 2: Risk assessment threshold adjustment is used to dynamically adjust the risk judgment threshold during tension clamp detection, and output fault warning information in combination with the surface temperature of the tension clamp and the actual vibration amplitude of the tension clamp. The output fault warning information includes 0 and 1. The risk judgment threshold includes a temperature risk threshold and a vibration amplitude risk threshold. This step dynamically adjusts the risk judgment threshold. Through the temperature risk threshold and the vibration amplitude risk threshold, it can be timely determined whether there is a fault risk. For example, when the temperature or vibration exceeds the set threshold, a warning signal will be immediately issued to indicate a potential fault. The logic of this step is to optimize the detection sensitivity in real time according to environmental conditions to ensure the accuracy of judgment under different conditions.

[0112] Dynamically adjust the risk judgment threshold during tension clamp detection. The specific analysis process is as follows: If the data acquisition frequency adjustment coefficient is not greater than 1: Regulate the temperature risk threshold based on the environmental data of the tension clamp and the current of the tension clamp: Combine the environmental data of the tension clamp and the current of the tension clamp into temperature threshold matching data; Compare the temperature threshold matching data with the temperature threshold pointing data stored in the database. A similarity function can be used for comparison, such as Euclidean distance. According to the minimum Euclidean distance, determine the temperature threshold pointing data closest to the temperature threshold matching data. The temperature threshold pointing data includes ambient temperature matching value, ambient humidity matching value, ambient wind speed matching value and tension clamp current matching value; Obtain the matching temperature risk threshold corresponding to the closest temperature threshold pointing data from the database, and use the matching temperature risk threshold as the adjusted temperature risk threshold.

[0113] Temperature directly affects the physical properties of the tension clamp. High temperature may cause the material to soften and accelerate aging, affecting the load-bearing capacity of the tension clamp. High humidity may cause condensation on the surface of the material, thereby affecting the insulation effect and increasing the risk of failure. Wind speed will cause vibration to the tension clamp, and vibration often affects the conductivity of temperature changes, making the temperature risk more complicated. When the wind speed is high, the material damage caused by temperature fluctuations may be more significant. By taking wind speed into consideration, the potential impact of temperature changes on the overall equipment status can be more accurately judged. The increase in current will cause the temperature of the clamp to rise, especially under high load, which may cause the temperature to rise sharply, increasing the risk of material damage.

[0114] The vibration amplitude risk threshold is regulated based on the ambient wind speed, the tension of the tension clamp and the tension clamp stress data obtained by the fiber Bragg grating sensor (FBG): the ambient wind speed, the tension of the tension clamp and the stress data of the tension clamp are combined into vibration threshold matching data; the vibration threshold matching data is compared with each vibration threshold pointing data stored in the database. The similarity function, such as the Euclidean distance, can also be used for this comparison to determine the vibration threshold pointing data closest to the vibration threshold matching data. The vibration threshold pointing data includes the ambient wind speed matching value, the tension clamp tension matching value and the tension clamp stress matching data; the matching vibration amplitude risk threshold corresponding to the closest vibration threshold pointing data is obtained from the database, and the matching vibration amplitude risk threshold is used as the regulated vibration amplitude risk threshold.

[0115] An increase in wind speed usually leads to an increase in the vibration frequency and amplitude of the wire clamp, and long-term high wind speed can cause fatigue damage to the wire clamp. Therefore, wind speed is an important factor in determining the vibration amplitude risk threshold. By monitoring wind speed changes, vibration risks can be better predicted. Tension represents the tensile load borne by the wire clamp, which is usually related to factors such as cable weight and wind load. Larger tension may increase the fatigue strength of the wire clamp and intensify the impact force and deformation caused by vibration. Stress is a key parameter that reflects the internal force of the wire clamp, and can characterize the strain of the wire clamp under the action of various external factors. In particular, fiber Bragg grating sensors can measure stress changes with high precision. Stress monitoring can detect stress concentration and material fatigue damage caused by vibration in advance, which helps to make a more accurate prediction of vibration risks.

[0116] By searching for the closest matching data in the database through a similarity function (such as Euclidean distance), we can make full use of historical and preset data to select the most appropriate threshold value, so that the adjusted threshold value is more in line with the current actual working conditions. This method draws on the advantages of empirical data and enhances the accuracy of prediction.

[0117] If the data acquisition frequency adjustment coefficient is greater than 1: the pre-set calibrated temperature risk threshold and calibrated vibration amplitude risk threshold are directly obtained from the database as the temperature risk threshold and vibration amplitude risk threshold. When the acquisition frequency adjustment coefficient A>1, it means that the current environment or load conditions have been detected to be abnormal and it is necessary to enter a high-attention state. At this time, dynamic adjustment is no longer performed, but the pre-set safety boundary (calibrated threshold) is directly extracted from the database to ensure the highest sensitivity under extreme working conditions.

[0118] By dynamically adjusting the threshold, the sensitivity of the detection can be automatically fine-tuned according to the real-time environment and load conditions to avoid unnecessary false alarms caused by small environmental changes. For example, when there are slight fluctuations in temperature and humidity, the system can adapt to these changes and reduce the risk of false alarms caused by overly strict thresholds.

[0119] When the acquisition frequency adjustment coefficient A>1, the calibration threshold is directly called, which simplifies the adjustment process. It is suitable for fast response scenarios and ensures that high-sensitivity monitoring can be entered immediately in extreme or high-risk situations, avoiding delays caused by dynamic adjustments and improving response efficiency.

[0120] If the surface temperature of the tension clamp is not greater than the temperature risk threshold and the actual vibration amplitude of the tension clamp is not greater than the vibration amplitude risk threshold, the output fault warning information is 0; if the surface temperature of the tension clamp is greater than the temperature risk threshold or the actual vibration amplitude of the tension clamp is greater than the vibration amplitude risk threshold, the output fault warning information is 1.

[0121] Step three, detection data acquisition is used to detect and collect data on the strain clamp based on the data collection frequency determined by the acquisition frequency dynamic adjustment module, and send the detected and collected data to be processed to the detection data processing method adjustment module through the set communication method. The data to be processed include the current change curve of the strain clamp, the tension change curve of the strain clamp, the vibration change curve of the strain clamp and the stress change curve of the strain clamp. The function of this step is to effectively transmit all relevant detection data to subsequent steps, laying the foundation for accurate data analysis and early warning. The set communication method can be a wireless communication method, including but not limited to Wi-Fi, or a wired communication method, such as Ethernet. In addition, satellite communication can be used in remote areas or areas that are not covered by the ground network.

[0122] Step 4. Adjust the detection data processing method to receive the data to be processed sent by the detection data acquisition module, determine the analysis results after analyzing the data to be processed, and achieve accurate status assessment through the tension clamp status judgment index and dynamic matching deviation data. Utilize similarity analysis and dynamic adjustment technology to intelligently optimize the judgment criteria according to equipment characteristics and environmental conditions to ensure monitoring sensitivity and accuracy.

[0123] The parameter change data of the tension clamp stored in the database are obtained, and the parameter change data of the tension clamp includes the current parameter change curve of the tension clamp, the tension parameter change curve of the tension clamp, the vibration parameter change curve of the tension clamp, and the stress parameter change curve of the tension clamp; the change state allowable deviation data are obtained, and the change state allowable deviation data includes the current change allowable deviation value of the tension clamp, the tension change allowable deviation value of the tension clamp, the vibration change allowable deviation value of the tension clamp, and the stress change allowable deviation value of the tension clamp; the data to be processed, the parameter change data of the tension clamp, and the parameter change data of the tension clamp are processed by the tension clamp state analysis model to obtain the tension clamp state judgment index, and the constraint formula of the tension clamp state analysis model is:

[0124]

[0125] In the formula, ρ Zrepresents the state judgment index of the tension clamp, σ(D1, D2) represents the similarity function between the tension clamp current change curve D1 and the tension clamp current parameter change curve D2, σ(Z1, Z2) represents the similarity function between the tension clamp tension change curve Z1 and the tension clamp tension parameter change curve Z2, σ(F1, F2) represents the similarity function between the tension clamp vibration change curve F1 and the tension clamp vibration parameter change curve F2, σ(Y1, Y2) represents the similarity function between the tension clamp stress change curve Y1 and the tension clamp stress parameter change curve Y2, ΔD represents the tension clamp The allowable deviation value of the current change of the tension clamp, ΔZ represents the allowable deviation value of the tension change of the tension clamp, ΔF represents the allowable deviation value of the vibration change of the tension clamp, ΔY represents the allowable deviation value of the stress change of the tension clamp, and the similarity function in the tension clamp state determination index can use the mean square error or cosine similarity. If the tension clamp state determination index is less than the tension clamp state determination threshold stored in the database, the analysis result is that the tension clamp state is stable; if the tension clamp state determination index is not less than the tension clamp state determination threshold stored in the database, the analysis result is that the tension clamp state is unstable.

[0126] The formula calculates the similarity of the change curves of current, tension, vibration and stress to determine the deviation between them and the reference data. Specifically, the change curves of current, tension, vibration and stress of the tension clamp are compared with the reference change curves in the database, and the similarity is expressed by a similarity function (such as Euclidean distance). The smaller the deviation value, the closer the current state is to the reference value, and the more stable the state of the tension clamp is.

[0127] This calculation can comprehensively and quantitatively evaluate the overall operating status of the tension clamp under various factors. The current directly determines the heating of the tension clamp. Excessive current may cause the clamp temperature to rise, causing material aging or physical property changes, thereby increasing the risk of failure. Current fluctuations may also indicate a drastic change in the system load, which can reflect the load-bearing status of the equipment and is also an important indicator for judging whether the equipment is in an overload or overtemperature state.

[0128] Tension reflects the pulling force on the tension clamp, which is mainly caused by factors such as the cable's own weight and external loads (such as wind loads). The increase in tension will aggravate the mechanical fatigue of the tension clamp and may cause physical looseness or damage. The tension change of the tension clamp directly affects its mechanical stability, especially in severe weather conditions (such as strong winds) or when the load increases. Monitoring the tension change can help determine whether the tension clamp is working within the mechanical load range and prevent possible mechanical failures in advance.

[0129] Vibration changes reflect the dynamic stress of the tension clamp under the influence of factors such as wind speed and external impact. Large amplitude vibration will accelerate the fatigue of the clamp, especially in the case of long-term frequent vibration, which will accelerate the fatigue and fracture of the material. Vibration changes are an important signal for identifying deteriorating environmental conditions. Especially in the case of high wind speed, increased vibration may indicate that the equipment may be subjected to higher dynamic loads. Therefore, incorporating vibration into ρ Z Calculation can identify safety risks caused by environmental changes at an early stage. Stress is the internal force generated by the tension clamp under multiple loads. Stress changes directly reflect the stress state of the material and can indicate potential material fatigue and structural deformation in advance. Stress monitoring is one of the core parameters for judging the health status of the tension clamp, especially through precision sensing technologies such as fiber Bragg gratings, which can accurately capture small changes in stress. When the stress exceeds the allowable range of the material, it may cause internal damage or structural damage to the material. Therefore, changes in stress help to identify material fatigue caused by comprehensive loads and prevent accidents such as sudden fractures.

[0130] The deviation values ​​of each variation curve reflect the allowable variation range of different factors. Items with larger deviations may represent greater instability factors. Therefore, adjusting these deviations according to actual monitoring data can help accurately evaluate the state stability of the tension clamp.

[0131] Obtain the change state allowable deviation data. The specific analysis process is as follows:

[0132] Determine the model and usage time of the tension clamp. Different models and usage time of the tension clamp correspond to different aging degrees and tolerances. Therefore, different equipment requires different allowable deviation data. Therefore, based on the model and usage time of the tension clamp, determine the change state allowable deviation matching data set corresponding to the model and usage time of the tension clamp from the database. The change state allowable deviation matching data set includes multiple change state allowable deviation matching data. The change state allowable deviation matching data includes environmental wind force matching value, environmental temperature matching value and electromagnetic strength matching value; obtain the environmental wind force, environmental temperature and electromagnetic strength of the environment where the tension clamp is located; judge Whether the ambient wind force in the environment where the tension clamp is located is less than the wind force threshold set in the database: If so, the ambient wind force, ambient temperature and electromagnetic intensity are compared with the allowable deviation matching data of each change state. This part of the comparison can also use a similarity function, such as Euclidean distance, to determine the closest change state allowable deviation matching data, obtain the matching change state allowable deviation data corresponding to the change state allowable deviation matching data from the database, and use the matching change state allowable deviation data as the change state allowable deviation data; if not, obtain the set change state allowable deviation data from the database as the change state allowable deviation data.

[0133] Strain clamps of different models and service life correspond to different working characteristics. By dynamically matching the use characteristics of the strain clamps and the current environmental conditions, the deviation data that best matches the actual working conditions can be obtained to ensure the accuracy of the detection; when the wind is strong, the preset deviation data is directly called to ensure the use of safety margins under extreme conditions and avoid misjudgments caused by frequent adjustments; when the wind is moderate, the deviation value will be dynamically adjusted based on wind speed, temperature and electromagnetic intensity, so that it can adapt to different environmental conditions and reduce false alarms and missed alarms.

[0134] Adjust the secondary processing strategy of the data to be processed based on the analysis results and fault warning information, as follows:

[0135] If the state of the tension clamp is stable and the fault warning information is 0, the secondary processing strategy is adjusted to continue to analyze the data to be processed (usage data) sent by the detection data acquisition to determine the analysis results. When the state is stable and there is no fault warning, it means that all parameters detected by the system are within the normal range and there is no abnormal change. In this case, the secondary processing strategy of the system is to continue to analyze the data to be processed sent by the detection data acquisition step to confirm the stable state, which can reduce invalid processing steps and resource consumption, and does not require additional complex processing or database comparison, thereby improving the working efficiency of the detection system.

[0136] If the state of the tension clamp is stable and the fault warning information is 1, the secondary processing strategy is adjusted to compare the data to be processed with the parameter data of each tension clamp stored in the database at the time of failure, determine the parameter data of the tension clamp at the time of failure that is closest to the data to be processed, and determine the corresponding fault type from the database based on the closest parameter data of the tension clamp at the time of failure; when the state of the tension clamp is stable but the warning information appears, it indicates that some indicators may be close to abnormal state, but the overall is still within an acceptable range. This situation may indicate early signs of failure. This part can help the system identify potential risks in the early stage of failure and avoid ignoring the occurrence of potential faults due to stable state. By matching the closest fault parameter data, the system can detect potential abnormalities in time, improve the accuracy of warnings, and help to perform maintenance and repairs before the problem expands.

[0137] If the state of the tension clamp is unstable, the secondary processing strategy is adjusted to compare the data to be processed with the parameter data of each tension clamp fault stored in the database, determine the parameter data of the tension clamp fault that is closest to the data to be processed, determine the corresponding fault type from the database based on the closest tension clamp fault parameter data, and at the same time control the monitoring equipment to obtain the video monitoring data of the tension clamp, analyze the video monitoring data, and further determine the tension clamp fault.

[0138] When the status is unstable, it means that some indicators have exceeded the normal range, and the equipment may be in a state of failure or pre-failure, which requires a more in-depth analysis. Not only is the data to be processed compared with the fault parameter data stored in the database, but the monitoring equipment is also used to collect video data and analyze the visual information of the equipment. This multi-dimensional analysis helps to more comprehensively evaluate the equipment status and determine the specific cause of the failure. For example, video monitoring can identify visual information about the physical state of the equipment (such as looseness or breakage), and assist data analysis in providing more detailed status confirmation. In addition, the intuitive feedback of video monitoring data in complex environments can be used as a second confirmation method to further improve the accuracy and credibility of fault determination.

[0139] The system selects corresponding processing strategies for different states and warning conditions. This combined design can improve the accuracy of fault detection. Multi-level data verification avoids the uncertainty brought by a single data source, thereby reducing the risk of misjudgment and missed judgment.

[0140] Assume that a power company has installed an intelligent monitoring system on the tension clamp of a high-voltage transmission line to monitor the working status and health of the clamp in real time. The tension clamp is located in a coastal area with high wind speed and high humidity. It is exposed to variable climatic conditions for a long time and is subject to frequent wind-induced vibrations, high humidity and electrical load fluctuations. The power company hopes to prevent potential failures through the intelligent monitoring system and ensure the stability of power supply. The following are the specific application scenarios and verification process of the system:

[0141] 1. Environmental conditions and initial settings:

[0142] The model of the tension clamp is XYZ-300, and its service life is 8 years. In the current environmental data, sT is 25°C, sD is 85%, sF is 20m / s, sR is 500A, sZ is 3000N, sY is 1.5mm, and the stress data of the tension clamp (in numerical expression to simplify the calculation) is 200MPa.

[0143] The parameter change data of the tension clamp in the database and the change state allowable deviation data obtained by comparison (to simplify the calculation, each curve is represented by a numerical value, sF is less than the wind force threshold set in the database, and the process of determining the change state allowable deviation data based on the Euclidean distance is omitted):

[0144] D1 is 500A, D2 is standard 500A, ΔD is 50A; Z1 is 3000N, Z2 is standard 3100N, ΔZ is 200N;

[0145] F1 is 1.5mm, F2 is standard 1.6mm, ΔF is 0.2mm; Y1 is 200Mpa, Y2 is standard 220MPa, ΔY is 20MPa; f maxis 10Hz, f min is 1Hz; cR is 550A, cZ is 3400N, and cY is 1.7mm.

[0146] 2. Data collection frequency adjustment:

[0147] Calculate the acquisition frequency adjustment coefficient A, assuming that the parameter data given in the database are cT = 20°C, cD = 70%, cF = 15m / s;

[0148] α1=α2=α3=α4=0.25, β1=β2=β3=1 / 3, and A is calculated to be 2.11>1, so the data acquisition frequency is directly set to the maximum frequency of 10 Hz to quickly capture real-time changes.

[0149] Since A>1, the pre-set calibrated temperature risk threshold and calibrated vibration amplitude risk threshold are directly used as the temperature risk threshold and vibration amplitude risk threshold. Assuming that the temperature risk threshold is 30°C and the vibration amplitude risk threshold is 1.7mm, the detected surface temperature of the tension clamp is 27°C. Since it is less than 30°C and sY is less than 1.7mm, the output fault warning information is 0.

[0150] Calculate ρ Z , ρ Z =0+0.5+0.5+1=2 (to simplify the calculation, ρ Z The similarity function in can be simplified to the absolute value calculation of the difference), the stored tension clamp state judgment threshold is 3, the output analysis result is that the tension clamp state is stable, and the output fault warning information is 0, and the current strategy is maintained to continue the detection and analysis.

[0151] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory and a network interface 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, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0152] Those skilled in the art will understand that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0153] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0154] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0155] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0156] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A method for intelligent detection and control of a tension clamp, characterized in that: The intelligent detection and control method of the tension clamp comprises: Dynamically adjust the detection data collection frequency of the tension clamp according to the installation environment and usage status, and determine the risk judgment threshold and output fault warning information standard of the tension clamp based on the detection data collection frequency; The use process data of the tension clamp is collected according to the detection data collection frequency, and the use process data is processed based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information; Based on the state judgment index and the output fault warning information, the usage process data of the tension clamp is secondary analyzed, and the fault information of the tension clamp is determined according to the analysis results.

2. The intelligent detection and control method for tension clamps according to claim 1 is characterized in that: The method of dynamically adjusting the detection data collection frequency of the tension clamp according to the installation environment and the use status, and determining the risk determination threshold and output fault warning information standard of the tension clamp based on the detection data collection frequency includes: Determine the installation environment information of the tension clamp based on the environmental sensor, and obtain the current, tension and vibration amplitude of the tension clamp when it is in use based on the multi-source sensor data; Determine the load value of the tension clamp according to the current, tension and vibration amplitude, calculate the data acquisition frequency adjustment coefficient based on the installation environment information, and obtain the upper and lower limits of the acquisition frequency in the historical detection process; Dynamically adjust the detection data collection frequency of the tension clamp based on the upper and lower limits of the collection frequency and the data collection frequency adjustment coefficient; The risk judgment threshold during the detection of the tension clamp is adjusted according to the detection data collection frequency adjustment coefficient and the installation environment information, and the output fault warning information is determined based on the risk judgment threshold and the surface temperature of the tension clamp.

3. The intelligent detection and control method for tension clamps according to claim 2 is characterized in that: The calculation formula of the data acquisition frequency adjustment coefficient is: In the formula, A represents the data acquisition frequency adjustment coefficient, sT represents the ambient temperature, cT represents the reference ambient temperature, sD represents the ambient humidity, cD represents the reference ambient humidity, cF represents the reference ambient wind speed, sF represents the ambient wind speed, sL represents the load of the tension clamp, α1 represents the weight factor of the ambient temperature deviation, α2 represents the weight factor of the ambient humidity, α3 represents the weight factor of the ambient wind speed, α4 represents the weight factor of the load of the tension clamp, sR represents the current of the tension clamp, sZ represents the tension of the tension clamp, sY represents the vibration amplitude of the tension clamp, cR represents the maximum defined current of the tension clamp, cZ represents the maximum defined tension of the tension clamp, cY represents the maximum defined vibration amplitude of the tension clamp, β1 represents the weight factor of the current of the tension clamp, β2 represents the weight factor of the tension of the tension clamp, and β3 represents the weight factor of the vibration amplitude of the tension clamp.

4. The intelligent detection and control method for tension clamps according to claim 3 is characterized in that: The step of adjusting the risk determination threshold value during the detection of the tension clamp according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and outputting the fault warning information based on the risk determination threshold value and the surface temperature of the tension clamp comprises: The detection data collection frequency adjustment coefficient is compared with the fault threshold. When the detection data collection frequency adjustment coefficient is greater than or equal to the fault threshold, a pre-set safety boundary is directly extracted from the database as a risk determination threshold; When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk determination threshold; The surface temperature and actual vibration amplitude of the tension clamp are obtained, and the fault warning information of the tension clamp is output by combining the temperature risk threshold and the vibration risk threshold.

5. The intelligent detection and control method for tension clamps according to claim 4 is characterized in that: When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, obtaining the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp based on the installation environment information of the tension clamp as the risk determination threshold includes: When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the installation environment information of the tension clamp and the tension clamp current are combined into temperature threshold matching data; Based on the Euclidean distance calculation technology, the temperature threshold matching data is compared with the temperature threshold pointing data pre-stored in the database, and the matching temperature risk threshold corresponding to the optimal temperature threshold pointing data is selected according to the comparison result as the temperature risk threshold after the detection data collection frequency is adjusted; Based on the installation environment information of the tension clamp, the tension and stress data of the tension clamp are combined as vibration threshold matching data, and the vibration threshold matching data is compared with the vibration threshold pointing data pre-stored in the database by using the Euclidean distance calculation technology to obtain the vibration comparison result; Based on the vibration comparison results, the matching vibration amplitude risk threshold corresponding to the optimal vibration threshold pointing data is selected as the vibration risk threshold after the detection data acquisition frequency is adjusted.

6. The intelligent detection and control method for tension clamps according to claim 1 is characterized in that: The method of collecting the use process data of the tension clamp according to the detection data collection frequency, and processing the use process data based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information includes: Based on the detection data collection frequency, data collection is performed on the use process of the tension clamp, and the use process data of the tension clamp is obtained according to the collection results, and the parameter change data of the tension clamp set in the database is obtained; The parameter change data of the tension clamp is compared with the use process data of the tension clamp, and the change state allowable deviation data is obtained according to the comparison result. Based on the state analysis model of the tension clamp, the use process data, the parameter change data of the tension clamp and the change state allowable deviation data are processed to obtain the state judgment index of the tension clamp; The surface temperature and actual vibration amplitude of the tension clamp during process data collection are determined based on environmental sensors, and the surface temperature and actual vibration amplitude are compared with the risk judgment threshold to obtain the output fault warning information of the tension clamp.

7. The intelligent detection and control method for tension clamps according to claim 6 is characterized in that: The expression of the tension clamp state analysis model is: In the formula, ρ Z represents the state judgment index of the tension clamp, σ(D1, D2) represents the similarity function between the current change curve D1 of the tension clamp and the current parameter change curve D2 of the tension clamp, σ(Z1, Z2) represents the similarity function between the tension change curve Z1 of the tension clamp and the tension parameter change curve Z2 of the tension clamp, σ(F1, F2) represents the similarity function between the vibration change curve F1 of the tension clamp and the vibration parameter change curve F2 of the tension clamp, σ(Y1, Y2) represents the similarity function between the stress change curve Y1 of the tension clamp and the stress parameter change curve Y2 of the tension clamp, ΔD represents the allowable deviation value of the current change of the tension clamp, ΔZ represents the allowable deviation value of the tension change of the tension clamp, ΔF represents the allowable deviation value of the vibration change of the tension clamp, and ΔY represents the allowable deviation value of the stress change of the tension clamp.

8. The intelligent detection and control method for tension clamps according to claim 1 is characterized in that: The secondary analysis of the use process data of the tension clamp based on the state determination index and the output fault warning information, and determining the fault information of the tension clamp according to the analysis result includes: When both the state judgment index and the output fault warning information meet the preset requirements, the use state of the tension clamp is defined as stable; When the state judgment index and the output fault warning information do not meet the preset requirements, the use process data of the tension clamp are compared with the fault parameter data preset in the database, and the tension clamp fault parameter data that best matches the use process data of the tension clamp is determined based on the comparison result; The fault type of the tension clamp is analyzed based on the parameter data when the tension clamp fails, and the fault information of the tension clamp is determined according to the fault type.

9. An intelligent detection and control system for tension clamps, characterized in that: The intelligent detection and control system of the tension clamp includes: Intelligent detection pre-processing unit, used to dynamically adjust the detection data collection frequency of the tension clamp according to the installation environment and usage status, and determine the risk judgment threshold of the tension clamp and the output fault warning information standard based on the detection data collection frequency; The state fault detection output unit is used to collect the use process data of the tension clamp according to the detection data collection frequency, and process the use process data based on the risk judgment threshold and the tension clamp state analysis model to obtain the state judgment index of the tension clamp and output fault warning information; The fault information analysis and determination unit is used to perform secondary analysis on the use process data of the tension clamp based on the state judgment index and the output fault warning information, and determine the fault information of the tension clamp according to the analysis result.

10. The intelligent detection and control system for tension clamps according to claim 9, characterized in that: The intelligent detection pre-processing unit comprises: A data acquisition definition module is used to determine the installation environment information of the tension clamp based on the environmental sensor, and to obtain the current, tension and vibration amplitude of the tension clamp when it is in use according to the multi-source sensor data; The limit value acquisition and determination module is used to determine the load value of the tension clamp according to the current, tension and vibration amplitude, calculate the data acquisition frequency adjustment coefficient in combination with the installation environment information, and obtain the upper and lower limits of the acquisition frequency in the historical detection process; A detection data acquisition frequency adjustment module is used to dynamically adjust the detection data acquisition frequency of the tension clamp based on the upper and lower limits of the acquisition frequency and the data acquisition frequency adjustment coefficient; The threshold fault determination output module is used to adjust the risk judgment threshold during the tension clamp detection according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and output fault warning information based on the risk judgment threshold and the surface temperature of the tension clamp.

11. The intelligent detection and control system for tension clamps according to claim 10, characterized in that: The calculation formula of the data acquisition frequency adjustment coefficient is: In the formula, A represents the data acquisition frequency adjustment coefficient, sT represents the ambient temperature, cT represents the reference ambient temperature, sD represents the ambient humidity, cD represents the reference ambient humidity, cF represents the reference ambient wind speed, sF represents the ambient wind speed, sL represents the load of the tension clamp, α1 represents the weight factor of the ambient temperature deviation, α2 represents the weight factor of the ambient humidity, α3 represents the weight factor of the ambient wind speed, α4 represents the weight factor of the load of the tension clamp, sR represents the current of the tension clamp, sZ represents the tension of the tension clamp, sY represents the vibration amplitude of the tension clamp, cR represents the maximum defined current of the tension clamp, cZ represents the maximum defined tension of the tension clamp, cY represents the maximum defined vibration amplitude of the tension clamp, β1 represents the weight factor of the current of the tension clamp, β2 represents the weight factor of the tension of the tension clamp, and β3 represents the weight factor of the vibration amplitude of the tension clamp.

12. The intelligent detection and control system for tension clamps according to claim 11, characterized in that: The threshold fault determination output module adjusts the risk determination threshold during the detection of the tension clamp according to the detection data acquisition frequency adjustment coefficient and the installation environment information, and determines the output fault warning information based on the risk determination threshold and the surface temperature of the tension clamp. When the detection data acquisition frequency adjustment coefficient is greater than or equal to the fault threshold, the pre-set safety boundary is directly extracted from the database as the risk determination threshold; When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp are obtained based on the installation environment information of the tension clamp as the risk determination threshold; The surface temperature and actual vibration amplitude of the tension clamp are obtained, and the fault warning information of the tension clamp is output by combining the temperature risk threshold and the vibration risk threshold.

13. The intelligent detection and control system for tension clamps according to claim 12, characterized in that: When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, obtaining the temperature risk threshold and the vibration risk threshold during the detection of the tension clamp based on the installation environment information of the tension clamp as the risk determination threshold includes: When the detection data acquisition frequency adjustment coefficient is less than the fault threshold, the installation environment information of the tension clamp and the tension clamp current are combined into temperature threshold matching data; Based on the Euclidean distance calculation technology, the temperature threshold matching data is compared with the temperature threshold pointing data pre-stored in the database, and the matching temperature risk threshold corresponding to the optimal temperature threshold pointing data is selected according to the comparison result as the temperature risk threshold after the detection data collection frequency is adjusted; Based on the installation environment information of the tension clamp, the tension and stress data of the tension clamp are combined as vibration threshold matching data, and the vibration threshold matching data is compared with the vibration threshold pointing data pre-stored in the database by using the Euclidean distance calculation technology to obtain the vibration comparison result; Based on the vibration comparison results, the matching vibration amplitude risk threshold corresponding to the optimal vibration threshold pointing data is selected as the vibration risk threshold after the detection data acquisition frequency is adjusted.

14. The intelligent detection and control system for tension clamps according to claim 9, characterized in that: The state fault detection output unit comprises: The use process data acquisition module is used to collect data on the use process of the tension clamp based on the detection data acquisition frequency, obtain the use process data of the tension clamp according to the acquisition results, and obtain the tension clamp parameter change data set in the database; The state judgment index analysis module is used to compare the parameter change data of the tension clamp with the use process data of the tension clamp, obtain the change state allowable deviation data according to the comparison result, and process the use process data, the parameter change data of the tension clamp and the change state allowable deviation data based on the tension clamp state analysis model to obtain the state judgment index of the tension clamp; The fault warning information output module is used to determine the surface temperature and actual vibration amplitude of the tension clamp when using process data collection based on the environmental sensor, and compare the surface temperature and actual vibration amplitude with the risk judgment threshold to obtain the output fault warning information of the tension clamp.

15. 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 8 are implemented.

16. 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 8 are implemented.

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