Ground anchor calculation auxiliary measuring and calculating system for electric power construction

Abstract

The invention discloses a ground anchor calculation auxiliary measuring and calculating system for electric power construction, and relates to the technical field of ground anchor construction, and the ground anchor calculation auxiliary measuring and calculating system for electric power construction comprises a data input module which is used for inputting ground anchor information and receiving electric power construction ground anchor related parameters input by a user. The microprocessor evaluates the safety condition in combination with ground anchor data, the sensor calibration module calibrates a sensor to provide accurate original data for the real-time monitoring data fusion module, the module integrates the data and then provides the data for the microprocessor for safety evaluation, and the data quality evaluation module evaluates a microprocessor instruction to provide a basis for the abnormity and early warning module. The module receives related data, data abnormity with small deviation is corrected by using a moving average algorithm and a smooth and linear interpolation method, the modules and the algorithms are matched to realize accurate safety assessment, effective early warning and risk prediction functions, and popularization is facilitated.

Description

Technical Field

[0001] The invention relates to the technical field of ground anchor construction, and in particular to a ground anchor calculation auxiliary measurement system for electric power construction. Background Art

[0002] In power construction, ground anchor plays a vital role. It is the key anchoring structure to ensure the stability of power facilities. With the continuous expansion of the scale and complexity of power projects, the requirements for the calculation and selection of ground anchors are also increasing.

[0003] Among them, the "A tension detection system and method for the anchor wire of the iron tower construction bracket" disclosed in the publication number "CN109799022A" has solved the various disadvantages of the wire breaking due to uneven force, which in turn causes construction accidents.

[0004] However, there are still many defects in the actual use of the ground anchor calculation auxiliary measurement system with similar structures. For example, the traditional ground anchor calculation and selection rely on empirical formulas and manual judgment, which have many limitations: First, in the face of complex construction environments and diversified loads, empirical formulas are difficult to accurately reflect actual working conditions, which can easily lead to unreasonable selection. For example, using the same selected ground anchor for soft and hard soil foundations will result in insufficient anchoring force or waste of resources; Second, manual judgment is prone to errors and low efficiency in processing large amounts of data and complex relationships, and cannot meet the needs of fast and accurate selection under the increasing number of power construction projects and progress requirements. In terms of safety, it is impossible to accurately predict load changes and ground anchor stress conditions, which may cause safety accidents due to ground anchor failure, threatening the stability of power supply and personnel safety. Therefore, it is necessary to design a ground anchor calculation auxiliary measurement system for power construction to meet efficient computing needs. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a ground anchor calculation auxiliary measurement system for electric power construction to solve the above problems.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A ground anchor calculation auxiliary measurement system for power construction includes:

[0007] The data input module is used to input the anchor information and receive the relevant parameters of the power construction anchor input by the user;

[0008] The load calculation module calculates the various loads borne by the anchor according to the parameters transmitted by the data input module;

[0009] A database for storing and recording the specification parameters of the anchor;

[0010] The anchor selection module selects the appropriate anchor type and specification based on the load data transmitted by the load calculation module and the pre-stored anchor specification parameter database;

[0011] Safety factor verification module, which performs secondary verification on the anchor parameters selected by the anchor selection module;

[0012] The data input module is connected to an intelligent learning module for learning user input information and supplementing missing input information;

[0013] The database is connected to a risk prediction module for evaluating the use status of the anchor;

[0014] The load calculation module is connected to a safety warning module for conducting a comprehensive assessment of the ground anchor and the construction environment.

[0015] Preferably, the load calculation module calculates various loads borne by the anchor, including vertical load and horizontal load, according to the parameters transmitted by the data input module.

[0016] The algorithm is: vertical load Q v =mg, m is the mass of the hanging object, g is the acceleration due to gravity;

[0017] Horizontal load Q h =Fcosθ, F is the tension, θ is the angle between the tension and the horizontal direction.

[0018] Preferably, the anchor selection module selects anchors by comparing the load with the bearing capacity of different anchors. v ≤V 承载 , and Q h ≤H 承载 , V 承载 , H 承载 are the vertical and horizontal bearing capacities of the anchor respectively, then the anchor is optional.

[0019] Preferably, the safety factor verification module determines whether the selected anchor meets the safety requirements by the formula: R is the ultimate bearing capacity of the anchor, Q is the actual load, and n≥≤n is required 标准 , where n 标准 To specify the safety factor.

[0020] Preferably, the load calculation module is connected to a working condition module for simulating the actual stress conditions of the anchor in different working scenarios.

[0021] Preferably, the load calculation module is also connected to an output module, and the output module is connected to a display terminal. The output module processes the load calculation result data and transmits it to the display terminal. The display terminal intuitively displays the load information, including size, direction, etc., to facilitate user viewing and analysis.

[0022] Preferably, the data input module is connected to a user terminal for inputting the information to be measured into the data input module. The user terminal is the entry for the user to input the information to be measured. The data input end receives the information transmitted from the user terminal and provides the original data for subsequent modules such as load calculation.

[0023] Preferably, the safety warning module includes a microprocessor for calculating data and processing and calculating various data. The microprocessor is connected to a sensor calibration module for calibrating the sensors. The sensor calibration module is connected to a real-time monitoring data fusion module for receiving the data from the calibrated sensors and performing fusion processing on these data. The microprocessor is also connected to a data quality assessment module for evaluating the data instructions issued by the microprocessor. The data quality assessment module is connected to an anomaly and warning module. According to the results of the data quality assessment module, when data anomalies or the safety status of the ground anchor do not meet the requirements, warning information is issued in a timely manner.

[0024] Preferably, the anomaly and warning module receives the calculated data from the data quality assessment module and the real-time monitoring data fusion module. When the data quality assessment module detects data anomalies, the anomaly and warning module activates the corresponding processing mechanism. For data points with small deviations, methods such as data smoothing and interpolation are used for correction. For serious data anomalies, warning information is sent to the user to prompt early warning of relevant external devices. The anomaly and warning module's handling of data anomalies includes the following steps:

[0025] S1. Data smoothing processing;

[0026] In data smoothing processing, the moving average algorithm is used. Let the original data sequence be x1, x2,...., xn, the moving average window size be qp, and qp < n. Then the i-th data y after moving average processing is: i as follows:

[0027]

[0028] S2. Data interpolation;

[0029] For data interpolation, the linear interpolation method is used. If the known data points are (x1, y1) and (x2, y2), for the interpolation point x between x1 < x < x2, the interpolation result y is:

[0030]

[0031] S3. Anomaly warning;

[0032] According to the data quality assessment results, different levels of warning thresholds are set. When the data deviation exceeds a certain degree or the proportion of abnormal values reaches a certain threshold.

[0033] Preferably, the risk prediction module includes a load change monitoring module for recording anchor load information; a trend analysis module for predicting the analysis of historical load data, and predicting future changes through the analysis of historical load data. The algorithm and formula: adopt the time series analysis method, and use the autoregressive moving average model ARMA and the autoregressive integrated moving average module ARIMA, for the load time series data x t , the expression of ARIMA(p, d, q) model is:

[0034]

[0035] Where φ(B) is the autoregressive operator, θ(B) is the moving average operator, B is the backshift operator, d is the number of differences, and e is the moving average operator. t It is white noise, and the load change trend can be predicted by learning from historical data.

[0036] The present invention provides a ground anchor calculation auxiliary measurement system for electric power construction. Compared with the prior art, it has the following beneficial effects:

[0037] 1. The anchor calculation-aided measurement system for power construction provided by the present invention, the microprocessor evaluates the safety status in combination with anchor-related data, the sensor calibration module calibrates tension, displacement and other sensors, and provides accurate original data for the real-time monitoring data fusion module, the real-time monitoring data fusion module integrates different types of monitoring data, and provides comprehensive and accurate data for the microprocessor safety assessment, the data quality assessment module evaluates the microprocessor instructions, and provides a basis for the abnormality and early warning module, the abnormality and early warning module receives data from the data quality assessment module and the real-time monitoring data fusion module, the data abnormalities with small deviations are smoothed by the moving average algorithm and corrected by the linear interpolation method, and an early warning is issued for data with large deviations, and at the same time, an early warning threshold is set according to the data quality assessment result, and the user is prompted through text messages, emails, and system interfaces, which can avoid calculation errors and safety accidents and ensure the accuracy and reliability of anchor safety monitoring. These modules and algorithms cooperate to achieve more accurate safety assessment and effective early warning functions, facilitate risk prediction, increase the intelligent effect of using the system, and facilitate the promotion and use of the system.

[0038] 2. The anchor calculation auxiliary measurement system for power construction provided by the present invention, the anchor selection module can fully consider future load changes in the selection process based on the load change trend information provided by the risk prediction module, avoid the selected anchor due to subsequent load changes due to the inadaptability problem, ensure that the anchor can effectively cope with the load conditions during the entire use cycle, improve the scientificity and foresight of the anchor selection, and ensure the long-term stable operation of the anchor. At the same time, the safety warning module receives the extreme load prediction feedback from the risk prediction module, and can issue a warning in time before the risk of anchor failure due to excessive load occurs. This allows relevant personnel to have enough time to take preventive measures, such as adjusting the load distribution, reinforcing the anchor, etc., effectively reducing the risk of anchor failure and ensuring the safe operation of related facilities or projects.

[0039] 3. The ground anchor calculation auxiliary measurement system for power construction provided by the present invention can learn the records of the data input module and the ground anchor selection module. When the user inputs parameters, it can automatically complete the parameters based on similar engineering cases and perform a preliminary rationality check. It adopts neural network algorithms such as multi-layer perceptrons, and adjusts the weights by training the network by minimizing the mean square error loss function to realize the processing of new input data. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the system principle of the present invention;

[0041] Figure 2 It is a schematic diagram of the safety warning module of the present invention;

[0042] Figure 3 Schematic diagram of the risk prediction module of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] See also Figure 1-Figure 3 , two technical solutions are provided: The first implementation method:

[0045] A ground anchor calculation auxiliary measurement system for electric power construction includes:

[0046] The data input module is used to input the anchor information and receive the power construction anchor related parameters input by the user, including but not limited to the anchor use environment (such as soil type, terrain, etc.), anchor stress conditions (tension magnitude, direction, etc.), construction requirements (such as temporary or permanent anchor), etc.;

[0047] The load calculation module calculates various loads borne by the anchor according to the parameters transmitted by the data input module, including vertical load, horizontal load, etc. For vertical load, if it is generated by the weight of the hanging object, the weight data can be directly obtained; the horizontal load can be calculated based on factors such as the component of the tension in the horizontal direction;

[0048] The load calculation module calculates the various loads borne by the anchor according to the parameters transmitted by the data input module, including vertical load and horizontal load. If there is a weight generated by a hanging object, the weight data can be directly obtained; the horizontal load can be calculated based on factors such as the horizontal component of the tension.

[0049] The algorithm is: vertical load Q v =mg, m is the mass of the hanging object, g is the acceleration due to gravity;

[0050] Horizontal load Q h =Fcosθ, F is the tension, θ is the angle between the tension and the horizontal direction;

[0051] A database for storing and recording the specification parameters of the anchor;

[0052] The anchor selection module selects the appropriate anchor type and specification based on the load data transmitted by the load calculation module and the pre-stored anchor specification parameter database (including the bearing capacity, size and other information of different types of anchors);

[0053] The anchor selection module selects anchors by comparing loads with the bearing capacities of different anchors. v ≤V 承载 , and Q h ≤H 承载 , V 承载 , H 承载 are the vertical and horizontal bearing capacities of the anchor respectively, then the anchor is optional;

[0054] The safety factor verification module conducts a secondary verification on the anchor parameters selected by the anchor selection module, calculates the safety factor based on the actual load conditions and relevant safety standards, and determines whether the selected anchor meets the safety requirements;

[0055] The safety factor verification module determines whether the selected anchor meets the safety requirements. The formula is: R is the ultimate bearing capacity of the anchor, Q is the actual load, and n≥n 标准 , where n 标准 To specify the safety factor;

[0056] The data input module is connected to an intelligent learning module for learning user input information and supplementing missing input information;

[0057] The intelligent learning module can learn the historical records of the data input module and the data record and reading of the anchor selection module. When the user inputs parameters, the intelligent learning module automatically completes and performs preliminary rationality checks on the input parameters based on the learned similar engineering cases. For example, if a certain terrain and soil type are input, it can infer the possible range of other related parameters based on past cases. In the intelligent learning module, the neural network algorithm in deep learning is used, such as the multi-layer perceptron (MLP), and the input parameter quantity is set to X = (x1, x2, ..., xn) (n is the number of parameters, such as soil parameters, tension parameters, etc.), and the output is the predicted related parameters or weight adjustment value vector, Y = (y1, y2, ..., ym) (m is the number of predicted values). The training process of the neural network is to adjust the weight of the network by minimizing the loss function, using the mean square error loss function:

[0058]

[0059] Among them, θ is the parameter of the neural network, N is the number of training samples, and y ij is the jth true output value of the ith sample, is the predicted value. After quantitative data training, the network can be used to process new input data.

[0060] The database is connected to a risk prediction module to evaluate the use status of ground anchors;

[0061] The load calculation module is connected to the safety warning module, which is used to conduct a comprehensive assessment of the anchor and the construction environment;

[0062] The load calculation module is connected to the working condition module to simulate the actual stress conditions of the anchor in different working scenarios, provide accurate parameters for the load calculation module, and consider the factors such as environment and construction stage that affect the load size and direction;

[0063] The load calculation module is also connected to an output module, and the output module is connected to a display terminal. The output module processes the load calculation result data and transmits it to the display terminal. The display terminal intuitively displays the load information, including size, direction, etc., which is convenient for users to view and analyze;

[0064] The data input module is connected to the user end, which is used to input the information to be measured into the data input module. The user end is the entrance for users to input the information to be measured. The data input end receives the information from the user end and provides raw data for subsequent load calculation modules;

[0065] The safety warning module includes a microprocessor for calculating data, which is used to process and calculate various data. For example, according to the received data loads, states, etc. related to the ground anchor, combined with safety standards and algorithms to evaluate the safety status. The microprocessor is connected to a sensor calibration module, which is used to calibrate sensors, such as tension sensors and displacement sensors. Because sensors may have errors during use, calibration can ensure the accuracy of their measurements and provide more accurate raw data for the real-time monitoring data fusion module. The sensor calibration module is connected to the real-time monitoring data fusion module, which receives data from the calibrated sensors and performs fusion processing on these data. Different types of monitoring data, such as load and displacement data, can be integrated together to provide comprehensive and accurate ground anchor working status data for the microprocessor, so as to better conduct safety assessments. The microprocessor is also connected to a data quality assessment module, which evaluates the data instructions issued by the microprocessor. These instructions may be further processing requirements for data, comparison strategies with safety standards, etc. By evaluating, the rationality and accuracy of the instructions are ensured, providing a reliable basis for the anomaly and warning module. The data quality assessment module is connected to the anomaly and warning module. According to the results of the data quality assessment module, when data anomalies are found or the safety status of the ground anchor does not meet the requirements, warning information is sent in a timely manner. For example, when the load on the ground anchor exceeds the safety limit or the sensor data shows abnormal fluctuations, an alarm is sent to the user to remind the user to take corresponding measures;

[0066] The anomaly and warning module receives the calculated data from the data quality assessment module and the real-time monitoring data fusion module. When the data quality assessment module finds data anomalies, the anomaly and warning module starts the corresponding processing mechanism. For data points with small deviations, methods such as data smoothing and interpolation are used for correction. For serious data anomalies (such as a large amount of unreasonable data caused by sensor failures), warning information is sent to the user to prompt early warning of relevant external devices and avoid calculation errors and safety accidents caused by incorrect data. The steps for the anomaly and warning module to handle data anomalies are as follows:

[0067] S1. Data smoothing processing;

[0068] In data smoothing processing, the moving average algorithm is adopted. Let the original data sequence be x1, x2,...., xn, the moving average window size be qp, and (qp < n), then the i-th data y after moving average processing i is:

[0069]

[0070] S2. Data interpolation;

[0071] For data interpolation, the linear interpolation method is adopted. If the known data points are (x1, y1) and (x2, y2), for the interpolation point x between x1 < x < x2, the interpolation result y is:

[0072]

[0073] S3. Abnormal warning;

[0074] Set different levels of warning thresholds according to the data quality assessment results. When the data deviation exceeds a certain degree or the proportion of abnormal values reaches a certain threshold, trigger the corresponding level of warning. The warning information can be conveyed to the user through text messages, emails, or system interface prompts.

[0075] The second implementation mode is mainly different from the first implementation mode in that the risk prediction module includes a load change monitoring module for recording the ground anchor load information and analyzing the changes in the load borne by the ground anchor over time, including changes in parameters such as load magnitude, direction, and frequency; a trend analysis module for predicting through the analysis of historical load data. By analyzing historical load data, predict future changes. Algorithms and formulas: Adopt time series analysis methods and use autoregressive moving average models (ARMA) and autoregressive integrated moving average modules (ARIMA). For the load time series data x t , the expression of the ARIMA(p, d, q) model:

[0076]

[0077] where φ(B) is the autoregressive operator, θ(B) is the moving average operator, B is the backward shift operator, d is the number of differences, and e t is white noise. By learning from historical data, predict the load change trend;

[0078] By using the load change monitoring module and the trend analysis module in combination, the load change trend information can be provided to the ground anchor selection module, enabling it to consider future load changes when selecting a ground anchor and choose a more adaptable ground anchor. At the same time, feedback the extreme load prediction situation to the safety warning module to facilitate early warning of the risk of ground anchor failure caused by excessive load.

[0079] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0080] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A ground anchor calculation auxiliary measurement system for electric power construction, characterized in that: Including: A data input module for inputting ground anchor information and receiving relevant parameters of the power construction ground anchor input by the user; A load calculation module for calculating various loads borne by the ground anchor according to the parameters transmitted by the data input module; A database for storing and recording the specification parameters of the ground anchor; A ground anchor selection module for selecting a suitable ground anchor type and specification based on the load data transmitted by the load calculation module and in combination with the pre-stored ground anchor specification parameter database; A safety factor verification module for secondarily verifying the ground anchor parameters selected by the ground anchor selection module; The data input module is connected to an intelligent learning module for learning the user input information and supplementing the missing input information; The database is connected to a risk prediction module for evaluating the usage status of the ground anchor; The load calculation module is connected to a safety warning module for comprehensively evaluating the ground anchor and the construction environment; 2. The anchor calculation auxiliary measurement system for electric power construction according to claim 1 is characterized in that: The load calculation module calculates various loads borne by the ground anchor according to the parameters transmitted by the data input module, including vertical loads and horizontal loads. The algorithm is: vertical load Q v =mg, m is the mass of the hanging object, g is the acceleration due to gravity; Horizontal load Q h =Fcosθ, F is the tension, θ is the angle between the tension and the horizontal direction.

3. The anchor calculation auxiliary measurement system for electric power construction according to claim 1 is characterized in that: The anchor selection module selects the anchor by comparing the load with the bearing capacity of different anchors. v ≤V 承载 , and Q h ≤H 承载 , V 承载 , H 承载 are the vertical and horizontal bearing capacities of the anchor respectively, then the anchor is optional.

4. The anchor calculation auxiliary measurement system for electric power construction according to claim 1 is characterized in that: The safety factor verification module determines whether the selected anchor meets the safety requirements by the formula: R is the ultimate bearing capacity of the anchor, Q is the actual load, and n≥≤n is required 标准 , Where n 标准 To specify the safety factor.

5. The anchor calculation auxiliary measurement system for electric power construction according to claim 1 is characterized in that: The load calculation module is connected to a working condition module for simulating the actual stress conditions of the ground anchor in different working scenarios; 6. The anchor calculation auxiliary measurement system for electric power construction according to claim 5 is characterized in that: The load calculation module is also connected to an output module, and the output module is connected to a display terminal. The output module processes the load calculation result data and transmits it to the display terminal, and the display terminal intuitively displays the load information, including magnitude and direction, for the user to view and analyze conveniently; 7. The anchor calculation auxiliary measurement system for electric power construction according to claim 1 is characterized in that: The data input module is connected to a user terminal for inputting the information to be measured into the data input module. The user terminal is the entry for the user to input the information to be measured, and the data input end receives the information transmitted by the user terminal to provide the original data for the subsequent load calculation module; 8. The anchor calculation auxiliary measurement system for electric power construction according to claim 1 is characterized in that: The safety warning module includes a microprocessor for calculating data, for processing and calculating various data. The microprocessor is connected to a sensor calibration module for calibrating the sensor. The sensor calibration module is connected to a real-time monitoring data fusion module for receiving the data from the calibrated sensor and performing fusion processing on these data. The microprocessor is also connected to a data quality evaluation module for evaluating the data instructions issued by the microprocessor. The data quality evaluation module is connected to an anomaly and warning module. According to the results of the data quality evaluation module, when data anomalies or the ground anchor safety status do not meet the requirements are found, warning information is sent out in a timely manner; 9. The anchor calculation auxiliary measurement system for electric power construction according to claim 8, characterized in that: The anomaly and warning module receives the data calculated by the data quality evaluation module and the real-time monitoring data fusion module. When the data quality evaluation module finds data anomalies, the anomaly and warning module starts the corresponding processing mechanism. For data points with small deviations, data smoothing and interpolation methods are used for correction. For serious data anomalies, warning information is sent to the user to prompt early warning of relevant external devices. The anomaly and warning module's processing of data anomalies includes the following steps: S1. Data smoothing processing; In data smoothing, the moving average algorithm is adopted. Let the original data sequence be x1, x2,...., xn, the moving average window size be qp, and qp < n. Then the i-th data y after moving average processing i is as follows: S2. Data interpolation; For data interpolation, the linear interpolation method is used. If the known data points are (x1, y1) and (x2, y2), for the interpolation point x between x1 < x < x2, the interpolation result y is: S3. Anomaly warning; Different levels of warning thresholds are set based on the data quality assessment results. When the data deviation exceeds a certain level or the proportion of abnormal values ​​reaches a certain threshold.

10. The anchor calculation auxiliary measurement system for electric power construction according to claim 1, characterized in that: The risk prediction module includes a load change monitoring module for recording anchor load information; Trend analysis module is used to analyze and predict historical load data. By analyzing historical load data, future changes are predicted. Algorithm and formula: time series analysis method is adopted, and the autoregressive moving average model ARMA and autoregressive integrated moving average module ARIMA are used. For load time series data x t , the expression of ARIMA(p, d, q) model is: Where φ(B) is the autoregressive operator, θ(B) is the moving average operator, B is the backshift operator, d is the number of differences, and e is the moving average operator. t It is white noise, and the load change trend can be predicted by learning from historical data.

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