A method and system for underground operation and maintenance based on big data analysis

Abstract

The present invention discloses an underground operation and maintenance method and system based on big data analysis, and relates to the technical field of underground operation and maintenance of coal mines. The underground operation and maintenance method based on big data analysis includes the following steps: sensor stability performance evaluation; signal fluctuation evaluation; sensor interference evaluation; operation and maintenance feedback. The present invention obtains a sensor stability performance evaluation value through underground sensor monitoring data and determines whether to perform stability adjustment, then obtains a signal fluctuation evaluation value by combining the signal fluctuation data and the sensor stability performance evaluation value after stability adjustment and determines whether to perform signal fluctuation adjustment, then obtains a sensor interference evaluation value by combining the signal fluctuation evaluation value after signal fluctuation adjustment and the sensor interference data and determines whether to perform sensor interference adjustment, and finally performs operation and maintenance feedback, thereby achieving the effect of improving the efficiency of underground operation and maintenance, and solving the problem of low efficiency of underground operation and maintenance based on underground data in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of underground coal mine operation and maintenance, and in particular to an underground coal mine operation and maintenance method and system based on big data analysis. Background Art

[0002] The underground operation environment is usually complex and changeable, including complex geological conditions, wide distribution of equipment, and frequent personnel flow. These factors lead to many challenges in underground operation and maintenance, such as difficult to predict equipment failures and difficult to detect safety hazards in time. Therefore, an efficient and intelligent operation and maintenance method is needed to meet these challenges. With the continuous expansion of the scale of underground operations and the continuous increase in the number of equipment, the complexity and workload of operation and maintenance work are also increasing. In recent years, with the rapid development and widespread application of technologies such as big data, artificial intelligence, and the Internet of Things, it has provided strong support for the innovation of underground operation and maintenance methods. These technologies can realize the real-time collection, transmission, and processing of various types of underground data, providing a reliable technical foundation for operation and maintenance methods based on big data analysis. Traditional operation and maintenance methods can no longer meet the needs of efficient operation and maintenance. The operation and maintenance method based on big data analysis can realize predictive maintenance of equipment failures and optimized scheduling of operation and maintenance work through intelligent processing and analysis of underground operation and maintenance data, thereby improving operation and maintenance efficiency.

[0003] Existing underground operation and maintenance methods mainly deploy sensors in key underground equipment and areas to collect data such as the equipment's operating status and environmental parameters in real time, and transmit the collected data to a server or operation and maintenance platform via wired or wireless means.

[0004] For example, a Chinese invention patent with announcement number CN117556978B discloses a coal mine underground operation and maintenance method and system based on big data analysis, including: obtaining tunnel information underground in the coal mine and generating a tunnel plan; collecting environmental data underground in the coal mine, inputting the environmental data into a trained analysis model, and outputting a data pair, which at least includes: a dangerous thermal value and a prediction table; superimposing the dangerous thermal value on the tunnel plan to obtain a dangerous thermal map; dividing the dangerous thermal map into high-risk areas, alert areas, and safe areas, and judging whether there are unauthorized personnel in the high-risk areas.

[0005] For example, the Chinese invention patent application with publication number: CN116384977A discloses a coal mine underground operation and maintenance method and system based on big data analysis and self-diagnosis, including: deploying sensors to collect data and transmit it to the server and operation and maintenance platform; performing big data analysis on the collected underground data to extract equipment information; performing self-diagnosis based on the status and performance parameters of the equipment, predicting equipment failure conditions and prompting maintenance measures.

[0006] However, the above technology has at least the following technical problems:

[0007] In the prior art, due to the continuous high temperature conditions in the underground environment, the high temperature may affect the electronic components and signal transmission of the sensor, causing errors or omissions in the collected data, resulting in low efficiency of underground operation and maintenance based on the underground data. Summary of the invention

[0008] The embodiments of the present invention solve the problem of low efficiency of downhole operation and maintenance based on downhole data in the prior art by providing a downhole operation and maintenance method and system based on big data analysis, thereby improving the efficiency of downhole operation and maintenance.

[0009] The embodiment of the present invention provides a downhole operation and maintenance method based on big data analysis, comprising the following steps: S1, obtaining a sensor stability performance evaluation value according to acquired downhole sensor monitoring data, judging whether to perform stability adjustment based on the sensor stability performance evaluation value, wherein the sensor stability performance evaluation value is used to evaluate the stability performance of a preset sensor deployed downhole, wherein the downhole sensor monitoring data includes resistance change, reference resistance, temperature change, sensor force and sensor mass; S2, obtaining the sensor stability performance evaluation value after stability adjustment and combining it with the acquired signal fluctuation data to obtain a signal fluctuation evaluation value, judging whether to perform signal fluctuation adjustment based on the signal fluctuation evaluation value, wherein the signal fluctuation evaluation value Used to evaluate the fluctuation degree of the output signal of a preset sensor, the signal fluctuation data includes the maximum output signal amplitude and the minimum output signal amplitude; S3, obtain the signal fluctuation evaluation value after signal fluctuation adjustment and obtain the sensor interference evaluation value in combination with the obtained sensor interference data, and judge whether to perform sensor interference adjustment based on the sensor interference evaluation value, the sensor interference evaluation value is used to evaluate the interference degree caused by the signal output of the preset sensor, and the sensor interference data includes the output signal amplitude and the noise signal amplitude; S4, perform operation and maintenance feedback according to the sensor stability performance evaluation value after stability adjustment, the signal fluctuation evaluation value after signal fluctuation adjustment, and the sensor interference evaluation value after sensor interference adjustment.

[0010] Furthermore, the specific process of obtaining the sensor stability performance evaluation value based on the acquired downhole sensor monitoring data is as follows: an initial temperature product is obtained by combining the reference resistance and the temperature change, and the initial temperature product is represented by the result of a ratio operation between the reference resistance and the temperature change; an initial temperature coefficient value is obtained by combining the resistance change and the initial temperature product, and the initial temperature coefficient value is represented by the result of a ratio operation between the resistance change and the initial temperature product; a temperature coefficient deviation is obtained by combining the initial temperature coefficient value and a preset temperature coefficient maximum threshold value obtained from a database, and the temperature coefficient deviation is obtained by dividing the initial temperature coefficient value by the difference between the preset temperature coefficient maximum threshold value and the preset temperature coefficient maximum threshold value. The result of performing a ratio operation and then a power operation on the temperature coefficient is represented by the ratio operation; the initial vibration acceleration is obtained by combining the sensor force and the sensor mass, and the initial vibration acceleration is represented by the result of performing a ratio operation on the sensor force and the sensor mass; the vibration acceleration deviation is obtained by combining the initial vibration acceleration and a preset maximum vibration acceleration threshold, and the vibration acceleration deviation is represented by the result of performing a ratio operation and then a power operation on the difference between the initial vibration acceleration and the preset maximum vibration acceleration threshold and the preset maximum vibration acceleration threshold; the sensor stability performance evaluation value is obtained by combining the temperature coefficient deviation, the vibration acceleration deviation, the first sensor stability weight and the second sensor stability weight.

[0011] Furthermore, the limiting expression of the sensor stability performance evaluation value is as follows:

[0012] ;

[0013] ;

[0014] ;

[0015] In the formula, represents the sensor stability performance evaluation value of the qth preset sensor, , q represents the number of the preset sensor, s represents the total number of preset sensors, k represents the time variable, , Indicates the monitoring start time point, Indicates monitoring the current time point. represents the temperature coefficient deviation of the qth preset sensor at time k, represents the vibration acceleration deviation of the qth preset sensor at time k, represents the resistance change of the qth preset sensor at time k, represents the reference resistance of the qth preset sensor at time k, represents the temperature change of the qth preset sensor at time k, represents the sensor force of the qth preset sensor at time k, represents the sensor quality of the qth preset sensor at time k, represents the temperature coefficient range of the qth preset sensor at time k, represents the vibration acceleration range of the qth preset sensor at time k, Indicates the preset maximum temperature coefficient threshold, Indicates the preset maximum threshold of vibration acceleration. represents the stability weight of the first sensor, represents the second sensor stability weight, and e represents a natural constant.

[0016] Furthermore, the specific process of obtaining the stability performance evaluation value of the sensor after stability adjustment and combining it with the obtained signal fluctuation data to obtain the signal fluctuation evaluation value is as follows: combining the maximum value of the output signal and the minimum value of the output signal to obtain the output signal amplitude change value, and the output signal amplitude change value is used to reflect the output signal fluctuation of the preset sensor; combining the output signal amplitude change value and the preset signal change minimum threshold obtained from the database to obtain the signal fluctuation deviation, and the signal fluctuation deviation is represented by the result of the ratio operation of the initial fluctuation amplitude change and the preset signal change minimum threshold, and the signal fluctuation deviation is used to reflect the deviation of the output signal fluctuation of the preset sensor; combining the signal fluctuation deviation and the sensor stability performance evaluation value that is not lower than the stability minimum threshold to obtain the signal fluctuation evaluation value; the preset signal change minimum threshold is obtained from the database.

[0017] Furthermore, the specific process of obtaining the signal fluctuation evaluation value after signal fluctuation adjustment and obtaining the sensor interference evaluation value in combination with the obtained sensor interference data is as follows: obtaining the initial noise transfer in combination with the output signal amplitude and the noise signal amplitude, the initial noise transfer is represented by the result of a ratio operation between the output signal amplitude and the noise signal amplitude, and the initial noise transfer is used to reflect the noise interference situation of the preset sensor; obtaining the noise transfer deviation in combination with the initial noise transfer and the preset sensor interference minimum threshold obtained from the database, the noise transfer deviation is represented by the result of a ratio operation between the initial noise transfer and the preset sensor interference minimum threshold; obtaining the sensor interference evaluation value in combination with the noise transfer deviation, the signal fluctuation evaluation value not higher than the signal fluctuation minimum threshold, the first sensor interference weight and the second sensor interference weight; the preset sensor interference minimum threshold, the first sensor interference weight and the second sensor interference weight are obtained from the database.

[0018] Furthermore, the operation and maintenance feedback includes stability feedback, fluctuation feedback and interference feedback; the stability feedback means that the sensor stability performance evaluation value obtained after stability adjustment and not lower than the minimum stability threshold is fed back to the preset data control center; the fluctuation feedback means that the signal fluctuation evaluation value obtained after signal fluctuation adjustment and not higher than the minimum signal fluctuation threshold is fed back to the preset data control center; the interference feedback means that the sensor interference evaluation value obtained after sensor interference adjustment and not higher than the maximum interference threshold is fed back to the preset data control center.

[0019] The present invention provides a downhole operation and maintenance system based on big data analysis, including a sensor stability performance evaluation module, a signal fluctuation evaluation module, a sensor interference evaluation module and an operation and maintenance feedback module: wherein the sensor stability performance evaluation module is used to obtain a sensor stability performance evaluation value according to acquired downhole sensor monitoring data, and judge whether to perform stability adjustment based on the sensor stability performance evaluation value, the sensor stability performance evaluation value is used to evaluate the stability performance of a preset sensor deployed downhole, the downhole sensor monitoring data includes resistance change, reference resistance, temperature change, sensor force and sensor quality; the signal fluctuation evaluation module is used to obtain the sensor stability performance evaluation value after stability adjustment and obtain a signal fluctuation evaluation value in combination with the acquired signal fluctuation data, and judge whether to perform stability adjustment based on the signal fluctuation evaluation value. Signal fluctuation adjustment is performed, and the signal fluctuation evaluation value is used to evaluate the fluctuation degree of the preset sensor output signal, and the signal fluctuation data includes the maximum output signal amplitude and the minimum output signal amplitude; the sensor interference evaluation module is used to obtain the signal fluctuation evaluation value after the signal fluctuation adjustment and obtain the sensor interference evaluation value in combination with the obtained sensor interference data, and judge whether to perform sensor interference adjustment based on the sensor interference evaluation value, and the sensor interference evaluation value is used to evaluate the interference degree caused by the signal output of the preset sensor, and the sensor interference data includes the output signal amplitude and the noise signal amplitude; the operation and maintenance feedback module is used to perform operation and maintenance feedback according to the sensor stability performance evaluation value after stability adjustment, the signal fluctuation evaluation value after signal fluctuation adjustment, and the sensor interference evaluation value after sensor interference adjustment.

[0020] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0021] 1. Obtain the sensor stability performance evaluation value through downhole sensor monitoring data and judge whether to make stability adjustment, then obtain the sensor stability performance evaluation value after stability adjustment and combine it with signal fluctuation data to obtain the signal fluctuation evaluation value and judge whether to make signal fluctuation adjustment, then obtain the signal fluctuation evaluation value after signal fluctuation adjustment and combine it with sensor interference data to obtain the sensor interference evaluation value and judge whether to make sensor interference adjustment, finally perform operation and maintenance feedback, thereby realizing the improvement of downhole operation and maintenance reliability, and then realizing the improvement of downhole operation and maintenance efficiency, and effectively solving the problem of low efficiency of downhole operation and maintenance based on downhole data in the prior art.

[0022] 2. The sensor stability performance evaluation value is obtained by combining the temperature coefficient deviation, the vibration acceleration deviation, the first sensor stability weight and the second sensor stability weight, and then the signal fluctuation deviation and the sensor stability performance evaluation value not lower than the minimum stability threshold are combined to obtain the signal fluctuation evaluation value. Finally, the sensor interference evaluation value is obtained by combining the noise transmission deviation, the signal fluctuation evaluation value not higher than the minimum signal fluctuation threshold, the first sensor interference weight and the second sensor interference weight, thereby improving the accuracy of downhole operation and maintenance data acquisition, and then realizing the precise quantification of downhole operation and maintenance.

[0023] 3. By judging whether the sensor stability performance evaluation value is not lower than the minimum stability threshold obtained from the database, and then judging whether the signal fluctuation evaluation value is not higher than the minimum signal fluctuation threshold obtained from the database, and finally judging whether the sensor interference evaluation value is not higher than the maximum interference threshold obtained from the database, dynamic adjustment of downhole operation and maintenance is achieved, thereby improving the accuracy of downhole operation and maintenance adjustment. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flowchart of an underground operation and maintenance method based on big data analysis provided by an embodiment of the present invention;

[0025] Figure 2 A statistical diagram of changes in sensor force-vibration acceleration deviation provided by an embodiment of the present invention;

[0026] Figure 3 A schematic diagram of the structure of an underground operation and maintenance system based on big data analysis provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The embodiments of the present invention solve the problem of low efficiency of downhole operation and maintenance based on downhole data in the prior art by providing a downhole operation and maintenance method and system based on big data analysis. The method obtains a sensor stability performance evaluation value according to downhole sensor monitoring data and determines whether to perform stability adjustment. Then, the sensor stability performance evaluation value after stability adjustment is obtained and combined with signal fluctuation data to obtain a signal fluctuation evaluation value and determine whether to perform signal fluctuation adjustment. Then, the signal fluctuation evaluation value after signal fluctuation adjustment is obtained and combined with sensor interference data to obtain a sensor interference evaluation value and determine whether to perform sensor interference adjustment. Finally, operation and maintenance feedback is performed according to the sensor stability performance evaluation value after stability adjustment, the signal fluctuation evaluation value after signal fluctuation adjustment and the sensor interference evaluation value after sensor interference adjustment, thereby improving the downhole operation and maintenance efficiency.

[0028] The technical solution in the embodiment of the present invention is to solve the problem of low efficiency of downhole operation and maintenance based on downhole data. The overall idea is as follows:

[0029] The obtained sensor stability performance evaluation value is used to determine whether stability adjustment is to be performed, and then the signal fluctuation data and the sensor stability performance evaluation value after stability adjustment are combined to obtain the signal fluctuation evaluation value and determine whether signal fluctuation adjustment is to be performed. Finally, the signal fluctuation evaluation value after signal fluctuation adjustment and the sensor interference data are combined to obtain the sensor interference evaluation value and determine whether sensor interference adjustment is to be performed, thereby achieving the effect of improving underground operation and maintenance efficiency.

[0030] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0031] like Figure 1As shown, it is a flow chart of a downhole operation and maintenance method based on big data analysis provided by an embodiment of the present invention, the method comprising the following steps: S1, sensor stability performance evaluation: obtaining a sensor stability performance evaluation value according to the acquired downhole sensor monitoring data, judging whether to perform stability adjustment based on the sensor stability performance evaluation value, the sensor stability performance evaluation value is used to evaluate the stability performance of a preset sensor deployed downhole, the stability adjustment is used to adjust the sensor stability performance evaluation value to be not less than a minimum stability threshold obtained from a database, the downhole sensor monitoring data comprises resistance change, reference resistance, temperature change, sensor force and sensor mass; S2, signal fluctuation evaluation: obtaining the sensor stability performance evaluation value after stability adjustment and combining it with the acquired signal fluctuation data to obtain a signal fluctuation evaluation value, judging whether to perform signal fluctuation adjustment based on the signal fluctuation evaluation value, the signal fluctuation evaluation value is used to evaluate the preset sensor output signal The signal fluctuation degree of the signal, the signal fluctuation adjustment is used to adjust the signal fluctuation evaluation value to no higher than the signal fluctuation minimum threshold value obtained from the database, and the signal fluctuation data include the maximum output signal amplitude and the minimum output signal amplitude; S3, sensor interference evaluation: obtain the signal fluctuation evaluation value after the signal fluctuation adjustment and obtain the sensor interference evaluation value in combination with the obtained sensor interference data, and judge whether to perform the sensor interference adjustment based on the sensor interference evaluation value. The sensor interference adjustment is used to adjust the sensor interference evaluation value to no higher than the maximum interference threshold value obtained from the database. The sensor interference evaluation value is used to evaluate the interference degree caused by the signal output of the preset sensor, and the sensor interference data include the output signal amplitude and the noise signal amplitude; S4, operation and maintenance feedback: provide operation and maintenance feedback according to the sensor stability performance evaluation value after the stability adjustment, the signal fluctuation evaluation value after the signal fluctuation adjustment, and the sensor interference evaluation value after the sensor interference adjustment.

[0032] In this embodiment, stability adjustment is the basis for signal fluctuation adjustment and sensor interference adjustment, because unstable sensors can hardly ensure the accuracy and reliability of output signals. The sensor stability performance evaluation value is used to evaluate the stability performance of preset sensors deployed underground to ensure that the sensors can continue to work stably in complex environments.

[0033] The signal fluctuation assessment value is used to assess the degree of fluctuation of the preset sensor output signal to ensure that the signal is stable and the fluctuation is normal. The sensor interference assessment value is used to assess the degree of interference caused by the preset sensor signal output, which helps to reduce the impact of signal interference between sensors. Through big data and Internet of Things technologies, the monitored downhole sensor monitoring data, signal fluctuation data and sensor interference data are transmitted to the preset data center for real-time storage and analysis. For example, downhole sensor monitoring data, signal fluctuation data and sensor interference data are collected and integrated through big data technology. Big data technology uses distributed file systems and databases to achieve reliable storage and efficient access to massive data. It can process large amounts of unstructured data, ensure data integrity and accessibility, and provide strong support for subsequent data analysis. It has achieved improved downhole operation and maintenance efficiency.

[0034] Furthermore, the specific process of obtaining the sensor stability performance evaluation value based on the acquired downhole sensor monitoring data is as follows: the initial temperature product is obtained by combining the reference resistance and the temperature change, and the initial temperature product is represented by the result of the ratio operation of the reference resistance and the temperature change; the initial temperature coefficient value is obtained by combining the resistance change and the initial temperature product, and the initial temperature coefficient value is represented by the result of the ratio operation of the resistance change and the initial temperature product, and the initial temperature coefficient value is used to reflect the sensitivity of the preset sensor to temperature changes; the temperature coefficient deviation (i.e., the value in the sensor stability performance evaluation value limit expression) is obtained by combining the initial temperature coefficient value and the preset temperature coefficient maximum threshold obtained from the database. ), the temperature coefficient deviation is represented by the result of the ratio operation between the difference between the initial temperature coefficient value and the preset maximum temperature coefficient threshold and the preset temperature coefficient and then the power operation. The temperature coefficient deviation is used to reflect the sensitivity deviation of the preset sensor to temperature changes; the initial vibration acceleration is obtained by combining the sensor force and the sensor mass. The initial vibration acceleration is represented by the result of the ratio operation between the sensor force and the sensor mass. The initial vibration acceleration is used to reflect the dynamic response of the preset sensor when it is vibrated; the vibration acceleration deviation (i.e., the value in the sensor stability performance evaluation value limit expression) is obtained by combining the initial vibration acceleration and the preset maximum vibration acceleration threshold. ), the vibration acceleration deviation is represented by the result of the ratio operation of the difference between the initial vibration acceleration and the preset vibration acceleration maximum threshold and the preset vibration acceleration maximum threshold, and then the power operation. The vibration acceleration deviation reflects the deviation of the dynamic response of the preset sensor when it is vibrated; the sensor stability performance evaluation value is obtained by combining the temperature coefficient deviation, the vibration acceleration deviation, the first sensor stability weight and the second sensor stability weight; the preset temperature coefficient maximum threshold, the preset vibration acceleration maximum threshold, the first sensor stability weight and the second sensor stability weight are obtained from the database; the first sensor stability weight is used to evaluate the influence of the temperature coefficient deviation of the preset sensor on the sensor stability performance evaluation value; the second sensor stability weight is used to evaluate the influence of the vibration acceleration deviation of the preset sensor on the sensor stability performance evaluation value.

[0035] Among them, the limiting expression of the sensor stability performance evaluation value is as follows:

[0036] ;

[0037] ;

[0038] ;

[0039] In the formula, represents the sensor stability performance evaluation value of the qth preset sensor, , q represents the number of the preset sensor, s represents the total number of preset sensors, k represents the time variable, , Indicates the monitoring start time point, Indicates monitoring the current time point. represents the temperature coefficient deviation of the qth preset sensor at time k, represents the vibration acceleration deviation of the qth preset sensor at time k, represents the resistance change of the qth preset sensor at time k. The resistance change represents the difference between the resistance at the current time point and the resistance at the start point of monitoring. represents the reference resistance of the qth preset sensor at time k, represents the temperature change of the qth preset sensor at time k. The temperature change represents the difference between the temperature at the current time point and the temperature at the start of monitoring. represents the sensor force of the qth preset sensor at time k, represents the sensor quality of the qth preset sensor at time k, represents the temperature coefficient range of the qth preset sensor at time k, represents the vibration acceleration range of the qth preset sensor at time k, Indicates the preset maximum temperature coefficient threshold, Indicates the preset maximum threshold of vibration acceleration. represents the stability weight of the first sensor, represents the second sensor stability weight, and e represents a natural constant.

[0040] In this embodiment, the downhole sensor monitoring data includes resistance change, reference resistance, temperature change, sensor force and sensor mass. The resistance of the preset sensor at a preset time is measured by a resistance strain gauge sensor deployed at a preset position point, and the difference between the measured resistance at the preset time and the resistance corresponding to the preset initial time point is the resistance change; the temperature of the downhole environment at a preset time is measured by a temperature sensor deployed at a preset position point, and the difference between the measured temperature at the preset time and the temperature corresponding to the preset initial time point is the temperature change; the reference resistance is the resistance of the preset sensor corresponding to the temperature at the initial time point, and the force applied to the preset sensor at the preset time is measured by a pressure sensor deployed at a preset position point. When the downhole environment changes, such as rock movement, equipment vibration, etc., the sensor will be subjected to corresponding force, and the mass of the preset sensor at the preset time is measured by a pressure sensor deployed at the preset position point.

[0041] The aforementioned database is a database for storing various types of setting data established before the construction of a downhole operation and maintenance system based on big data analysis provided by an embodiment of the present invention. The database includes but is not limited to vibration acceleration, temperature coefficient, and output signal amplitude, and various numerical values ​​therein are directly set by technical personnel. For example, the preset maximum threshold of the temperature coefficient is represented by the maximum value of the sensor temperature coefficient in the historical time period in the database, and the preset maximum threshold of the vibration acceleration is represented by the maximum value of the sensor vibration acceleration in the historical time period in the database.

[0042] Specifically, the sum of the first sensor stability weight and the second sensor stability weight is 1, for example, the first sensor stability weight is 0.5, and the second sensor stability weight is 0.5; the second sensor stability weight is the weight corresponding to the sensor vibration acceleration value preset in the database, which represents the influence of the sensor vibration acceleration value on the sensor stability performance evaluation value. When used, the weight corresponding to the preset sensor vibration acceleration value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the sensor vibration acceleration in the underground operation and maintenance training set and the weight corresponding to the sensor vibration acceleration value preset in the database form a mapping set, and the real-time sensor vibration acceleration is input into the mapping set to obtain the corresponding weight, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0, 1].

[0043] It should be understood that the algorithm of this embodiment combines the downhole sensor monitoring data with comprehensive analysis to obtain the sensor stability performance evaluation value. The downhole sensor monitoring data in the algorithm of this embodiment does not exist independently, but is interrelated. Temperature changes will affect the resistance value of the sensor, because temperature changes will cause the material to expand or contract, thereby changing the resistance value. Temperature changes may affect the force applied to the sensor, especially in a high temperature environment. The strength and elastic modulus of the material may change, thereby affecting the sensor's response to the force. External forces will cause the elastic element to deform, thereby changing the resistance value of the strain sensitive element. Therefore, the magnitude of the sensor force directly affects the amount of resistance change. The parameters of the algorithm of this embodiment need to be considered together and at the same time.

[0044] Specifically, the temperature coefficient The range of When the temperature coefficient of the preset sensor is not within the temperature coefficient When the vibration acceleration range is less than 200V, the stability of the sensor monitoring under high temperature conditions will be reduced, making the measurement results inaccurate. ,Pick , when the vibration acceleration of the preset sensor is not within the vibration acceleration When it is within the range, the stability of sensor monitoring under high temperature conditions will be reduced, making the measurement results inaccurate.

[0045] Specifically, assuming the sensor quality The range is 0.1-1 (kg), the sensor force The range is 0.1-10 (N), and the maximum threshold of vibration acceleration is preset is 5 (N / kg), such as Figure 2 As shown, it is a statistical diagram of the change of sensor force-vibration acceleration deviation provided by an embodiment of the present invention. It can be seen from the figure that when the sensor mass is fixed at 0.5 (kg), as the sensor force gradually increases, the vibration acceleration deviation gradually increases, which means that the stability performance of the preset sensor deployed underground is gradually enhanced, thereby achieving accurate quantification of the stability performance of the preset sensor deployed underground, and further achieving improved underground operation and maintenance efficiency.

[0046] Furthermore, the specific process of judging whether to perform stability adjustment based on the sensor stability performance evaluation value is as follows: the first step is to judge whether the sensor stability performance evaluation value is not lower than the minimum stability threshold obtained from the database. If so, it indicates that the sensor stability is qualified and no stability adjustment is performed, otherwise the second step is executed; the second step is to perform temperature compensation. When the monitored sensor stability performance evaluation value is not lower than the minimum stability threshold obtained from the database, the stability adjustment is stopped, otherwise the third step is executed. The temperature compensation is used to compensate for the output of the preset sensor to improve the temperature stability of the preset sensor; the third step is to perform buffering and vibration reduction. When the monitored sensor stability performance evaluation value is not lower than the minimum stability threshold, the stability adjustment is stopped, otherwise an alarm is sent to the preset personnel. Buffering and vibration reduction means sending a prompt to the preset personnel to add a buffer device or buffer material to absorb vibration energy.

[0047] In this embodiment, the minimum threshold of stability is represented by the average value of the sensor stability performance evaluation value in the historical time period in the database, and the temperature compensation means that the output value of the measured temperature sensor is input into the compensation circuit for compensation through the temperature compensation algorithm, and the compensation circuit can adjust the output value according to the temperature change. For example, according to the output value of the temperature sensor, the required temperature compensation amount is obtained through the corresponding temperature compensation algorithm to offset the influence of temperature change on the measurement result. The buffer device or buffer material includes a shock absorber and a rubber pad. The shock absorber can effectively reduce the output fluctuation of the preset sensor caused by vibration, which helps to improve the stability of the sensor. The rubber pad is a commonly used buffer material with shock absorption performance; the underground operation and maintenance efficiency is improved.

[0048] Furthermore, the specific process of obtaining the stability performance evaluation value of the sensor after stability adjustment and combining it with the obtained signal fluctuation data to obtain the signal fluctuation evaluation value is as follows: combining the maximum value of the output signal and the minimum value of the output signal to obtain the output signal amplitude change value, the output signal amplitude change value is used to reflect the output signal fluctuation of the preset sensor; combining the output signal amplitude change value and the preset signal change minimum threshold obtained from the database to obtain the signal fluctuation deviation (that is, the value in the signal fluctuation evaluation value restriction expression) ), the signal fluctuation deviation is represented by the result of the ratio operation between the initial fluctuation amplitude change and the preset signal change minimum threshold value. The signal fluctuation deviation is used to reflect the deviation of the output signal fluctuation of the preset sensor; the signal fluctuation evaluation value is obtained by combining the signal fluctuation deviation and the sensor stability performance evaluation value that is not less than the minimum stability threshold value; the preset signal change minimum threshold value is obtained from the database.

[0049] Among them, the limiting expression of the signal fluctuation evaluation value is as follows:

[0050] ;

[0051] ;

[0052] In the formula, represents the signal fluctuation evaluation value of the qth preset sensor, , q represents the number of the preset sensor, s represents the total number of preset sensors, k represents the time variable, , Indicates the monitoring start time point, Indicates monitoring the current time point. represents the signal fluctuation deviation of the qth preset sensor at time k, represents the sensor stability performance evaluation value of the qth preset sensor that is not less than the minimum stability threshold, represents the output signal amplitude change value of the qth preset sensor at time k. The output signal amplitude change value represents the difference between the maximum output signal amplitude and the minimum output signal amplitude of the preset sensor. represents the minimum threshold value of preset signal change, and e represents a natural constant.

[0053] In this embodiment, the preset signal change minimum threshold is represented by the minimum value of the sensor output signal amplitude change in the historical time period in the database, and the signal fluctuation data includes the maximum output signal amplitude and the minimum output signal amplitude. The output signal amplitude change of the preset sensor at the preset time is collected in real time through the preset data control center and the oscilloscope. The output signal amplitude change is represented by the difference between the maximum output signal amplitude and the minimum output signal amplitude.

[0054] It should be understood that the algorithm of this embodiment combines the signal fluctuation data and the sensor stability performance evaluation value for comprehensive analysis to obtain the signal fluctuation evaluation value. In the algorithm of this embodiment, the signal fluctuation data and the sensor stability performance evaluation value do not exist independently, but are interrelated. The maximum and minimum values ​​of the output signal amplitude directly reflect the fluctuation range of the signal. The greater the difference between these two values, the more drastic the signal fluctuation, and the sensor stability performance may be affected. Because the larger the fluctuation of the signal, the greater the interference to the sensor in the underground environment. The parameters of the algorithm of this embodiment need to be considered together and at the same time to affect the results.

[0055] Specifically, assuming that the signal fluctuation deviation The range is 0.1-0.5, and the sensor stability performance evaluation value is not less than the minimum stability threshold The range is 0.1-1, and the monitoring start time point 1, monitoring the current time point is 100, as shown in Table 1, which is a statistical table of changes in the signal fluctuation evaluation value provided by an embodiment of the present invention:

[0056] Table 1. Statistics of changes in signal fluctuation evaluation values

[0057]

[0058] As can be seen from the table above, as the signal fluctuates The sensor stability performance evaluation value is not less than the minimum stability threshold. The signal fluctuation evaluation value The gradual increase means that the fluctuation degree of the preset sensor output signal gradually increases, which realizes the accurate quantification of the fluctuation degree of the preset sensor output signal, and then realizes the improvement of the downhole operation and maintenance efficiency.

[0059] Furthermore, the specific process of judging whether to perform signal fluctuation adjustment based on the signal fluctuation evaluation value is as follows: SS1, judging whether the signal fluctuation evaluation value is not higher than the signal fluctuation minimum threshold value obtained from the database. When the signal fluctuation evaluation value is not higher than the signal fluctuation minimum threshold value, it indicates that the signal fluctuation condition is qualified and no signal fluctuation adjustment is performed, otherwise SS2 is executed; SS2, performing digital filtering processing. When the monitored signal fluctuation evaluation value is not higher than the signal fluctuation minimum threshold value, the signal fluctuation adjustment is stopped, otherwise SS3 is executed. The digital filtering processing indicates improving the reliability of the signal through the digital filtering method; SS3, performing dynamic compensation. When the monitored signal fluctuation evaluation value is not higher than the signal fluctuation minimum threshold value, the signal fluctuation adjustment is stopped, otherwise an alarm is sent to the preset personnel. Dynamic compensation indicates correcting the signal fluctuation caused by vibration through the dynamic compensation algorithm.

[0060] In this embodiment, the minimum threshold of signal fluctuation is represented by the average value of the signal fluctuation evaluation value in the historical time period in the database. Digital filtering includes moving average filtering, median filtering, Kalman filtering, wavelet transform filtering, etc. The embodiment of the present invention decomposes the signal into different frequency components through the wavelet transform filtering method, and then filters out or retains the different frequency components to achieve filtering and denoising of the signal. The embodiment of the present invention automatically adjusts the compensation parameters according to the real-time changes of the signal through the adaptive dynamic compensation method to achieve the best compensation effect, and improves the efficiency of underground operation and maintenance.

[0061] Furthermore, the specific process of obtaining the signal fluctuation evaluation value after the signal fluctuation adjustment and combining it with the obtained sensor interference data to obtain the sensor interference evaluation value is as follows: the initial noise transfer is obtained by combining the output signal amplitude and the noise signal amplitude, and the initial noise transfer is represented by the result of the ratio operation of the output signal amplitude and the noise signal amplitude, and the initial noise transfer is used to reflect the noise interference of the preset sensor; the noise transfer deviation (i.e., the value in the sensor interference evaluation value restriction expression) is obtained by combining the initial noise transfer and the preset sensor interference minimum threshold obtained from the database. ), the noise transfer deviation is represented by the result of the ratio operation between the initial noise transfer and the preset sensor interference minimum threshold, and the noise transfer deviation is used to reflect the deviation of the noise transfer of the preset sensor; the sensor interference evaluation value is obtained by combining the noise transfer deviation, the signal fluctuation evaluation value not higher than the signal fluctuation minimum threshold, the first sensor interference weight and the second sensor interference weight; the preset sensor interference minimum threshold, the first sensor interference weight and the second sensor interference weight are obtained from the database; the first sensor interference weight is used to evaluate the influence of the output signal transfer noise of the preset sensor on the sensor interference evaluation value; the second sensor interference weight is used to evaluate the influence of the signal fluctuation evaluation value of the preset sensor not higher than the signal fluctuation minimum threshold on the sensor interference evaluation value.

[0062] Among them, the limiting expression of the sensor interference evaluation value is as follows:

[0063] dk;

[0064] ;

[0065] In the formula, represents the sensor interference evaluation value of the qth preset sensor, , q represents the number of the preset sensor, s represents the total number of preset sensors, k represents the time variable, , Indicates the monitoring start time point, Indicates monitoring the current time point. represents the noise transfer deviation of the qth preset sensor at time k, represents the signal fluctuation evaluation value of the qth preset sensor, represents the output signal amplitude of the qth preset sensor at time k, represents the noise signal amplitude of the qth preset sensor at time k, Indicates the preset minimum threshold of sensor interference. represents the first sensor interference weight, represents the second sensor interference weight, and e represents a natural constant.

[0066] In this embodiment, the sensor interference data includes the output signal amplitude and the noise signal amplitude. The output signal amplitude and the noise signal amplitude of the preset sensor at the preset time are collected in real time through the preset data control center and the oscilloscope. The preset sensor interference minimum threshold is represented by the minimum value of the sensor signal output amplitude in the historical time period in the database.

[0067] Specifically, the sum of the first sensor interference weight and the second sensor interference weight is 1, for example, the first sensor interference weight is 0.5, and the second sensor interference weight is 0.5; the first sensor interference weight is the weight corresponding to the sensor noise transfer value preset in the database, which represents the degree of influence of the sensor noise transfer value on the sensor interference evaluation value. When used, the weight corresponding to the preset sensor noise transfer value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the sensor noise transfer in the underground operation and maintenance training set and the weight corresponding to the preset sensor noise transfer value in the database form a mapping set, and the real-time sensor noise transfer value is input into the mapping set to obtain the corresponding weight, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. In this example, its value range is [0, 1].

[0068] It should be understood that the algorithm of this embodiment combines the sensor interference data and the signal fluctuation evaluation value for comprehensive analysis to obtain the sensor interference evaluation value. In the algorithm of this embodiment, the sensor interference data and the signal fluctuation evaluation value do not exist independently, but are interrelated. The output signal amplitude represents the signal strength when the sensor is working normally, while the noise signal amplitude represents the strength of the interference signal. The relationship between the two directly affects the size of the sensor interference evaluation value. If the noise signal amplitude is larger than the output signal amplitude, the sensor interference evaluation value will be higher, indicating that the sensor is subject to greater interference. The higher the fluctuating signal, the greater the interference to the sensor. The preset sensor output signal will become unstable, which is manifested as an increase in the fluctuation of the signal amplitude. This will increase the sensor interference evaluation value. The parameters of the algorithm of this embodiment need to consider the impact on the results together at the same time; the precise quantification of the interference degree caused by the signal output of the preset sensor is achieved, thereby improving the efficiency of underground operation and maintenance.

[0069] Furthermore, the specific process of judging whether to perform sensor interference adjustment based on the sensor interference evaluation value is as follows: AQ1, judging whether the sensor interference evaluation value is not higher than the maximum interference threshold obtained from the database. When the sensor interference evaluation value is not higher than the maximum interference threshold, it indicates that the signal interference is qualified and no sensor interference adjustment is performed. Otherwise, AQ2 is executed; AQ2, performing signal amplification, when the monitored sensor interference evaluation value is not higher than the maximum interference threshold, the sensor interference adjustment is stopped, otherwise AQ3 is executed. Signal amplification means sending a prompt to the preset personnel to increase the number of signal amplifiers to enhance the signal-to-noise ratio and thus reduce the signal; AQ3, performing interference isolation, when the monitored sensor interference evaluation value is not higher than the maximum interference threshold, the sensor interference adjustment is stopped, otherwise an alarm prompt is sent to the preset personnel. Interference isolation is used to cut off the coupling channel of signal interference.

[0070] In this embodiment, the maximum interference threshold is represented by the average value of the sensor interference evaluation value in the historical time period in the database; a signal amplifier is deployed at a preset position around the signal source to enhance the signal strength, and interference isolation means that two signals with equal amplitude and opposite polarity (i.e., positive signal and negative signal) are introduced into the transmission line through differential signal transmission, and the original signal is restored by comparing the difference between the two signals at the preset receiving end. Differential signal transmission has a strong suppression ability for common mode interference. Since the positive and negative signals are usually subject to the same interference during transmission, these interferences will be offset by each other at the receiving end, thereby improving the signal's anti-interference ability. Noise signals are often random and affect positive and negative signals at the same time. By processing the signal in a differential manner, the noise signals will also offset each other at the receiving end, thereby improving the signal's anti-noise ability; achieving an improvement in underground operation and maintenance efficiency.

[0071] like Figure 3As shown, it is a structural schematic diagram of a downhole operation and maintenance system based on big data analysis provided by an embodiment of the present invention. The downhole operation and maintenance system based on big data analysis provided by an embodiment of the present invention includes: a sensor stability performance evaluation module, a signal fluctuation evaluation module, a sensor interference evaluation module and an operation and maintenance feedback module: wherein the sensor stability performance evaluation module is used to obtain a sensor stability performance evaluation value according to the acquired downhole sensor monitoring data, and judge whether to perform stability adjustment based on the sensor stability performance evaluation value, the sensor stability performance evaluation value is used to evaluate the stability performance of a preset sensor deployed downhole, and the stability adjustment is used to adjust the sensor stability performance evaluation value to not less than the minimum stability threshold obtained from the database, and the downhole sensor monitoring data includes resistance change, reference resistance, temperature change, sensor force and sensor quality; the signal fluctuation evaluation module is used to obtain the sensor stability performance evaluation value after stability adjustment and obtain the signal fluctuation evaluation value in combination with the acquired signal fluctuation data, and judge whether to perform stability adjustment based on the signal fluctuation evaluation value The sensor interference evaluation value is used to evaluate the degree of fluctuation of the preset sensor output signal. The signal fluctuation adjustment is used to adjust the signal fluctuation evaluation value to no higher than the signal fluctuation minimum threshold value obtained from the database. The signal fluctuation data include the maximum output signal amplitude and the minimum output signal amplitude. The sensor interference evaluation module is used to obtain the signal fluctuation evaluation value after the signal fluctuation adjustment and obtain the sensor interference evaluation value in combination with the obtained sensor interference data. Based on the sensor interference evaluation value, it is determined whether to perform the sensor interference adjustment. The sensor interference adjustment is used to adjust the sensor interference evaluation value to no higher than the maximum interference threshold value obtained from the database. The sensor interference evaluation value is used to evaluate the degree of interference caused by the preset sensor due to the signal output. The sensor interference data include the output signal amplitude and the noise signal amplitude. The operation and maintenance feedback module is used to provide operation and maintenance feedback based on the sensor stability performance evaluation value after the stability adjustment, the signal fluctuation evaluation value after the signal fluctuation adjustment, and the sensor interference evaluation value after the sensor interference adjustment.

[0072] Specifically, the operation and maintenance feedback includes stability feedback, fluctuation feedback and interference feedback; stability feedback means that the sensor stability performance evaluation value obtained after stability adjustment and not lower than the minimum stability threshold is fed back to the preset data control center; fluctuation feedback means that the signal fluctuation evaluation value obtained after signal fluctuation adjustment and not higher than the minimum signal fluctuation threshold is fed back to the preset data control center; interference feedback means that the sensor interference evaluation value obtained after sensor interference adjustment and not higher than the maximum interference threshold is fed back to the preset data control center.

[0073] Specifically, the sensor stability performance evaluation module ensures the stability of the sensor, the signal fluctuation evaluation module further refines the evaluation of signal quality, the sensor interference evaluation module evaluates the degree of interference of the sensor to the surrounding environment and takes corresponding adjustment measures (sensor interference adjustment), and the operation and maintenance feedback module provides feedback on the overall performance of the sensor system. The operation and maintenance feedback provides comprehensive and accurate sensor performance information for the operation and maintenance personnel. This information helps the operation and maintenance personnel to promptly discover and solve sensor performance problems, ensure the normal operation of the downhole monitoring system and the accuracy of the data, and improve the efficiency of downhole operation and maintenance.

[0074] To summarize, the embodiment of the present invention obtains a sensor stability performance evaluation value through downhole sensor monitoring data and determines whether to perform stability adjustment, then obtains the sensor stability performance evaluation value after stability adjustment and obtains a signal fluctuation evaluation value in combination with the signal fluctuation data and determines whether to perform signal fluctuation adjustment, then obtains the signal fluctuation evaluation value after signal fluctuation adjustment and obtains a sensor interference evaluation value in combination with the sensor interference data and determines whether to perform sensor interference adjustment, and finally performs operation and maintenance feedback, thereby achieving an improvement in the reliability of downhole operation and maintenance, and then achieving an improvement in the efficiency of downhole operation and maintenance, effectively solving the problem of low efficiency of downhole operation and maintenance based on downhole data in the prior art.

[0075] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0076] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0079] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0080] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A downhole operation and maintenance method based on big data analysis, characterized in that: The following steps are involved: S1, obtaining a sensor stability performance evaluation value according to the acquired downhole sensor monitoring data, and judging whether to perform stability adjustment based on the sensor stability performance evaluation value, wherein the sensor stability performance evaluation value is used to evaluate the stability performance of a preset sensor deployed downhole, and the downhole sensor monitoring data includes resistance change, reference resistance, temperature change, sensor force and sensor quality; S2, obtaining a stability performance evaluation value of the sensor after stability adjustment and combining it with the obtained signal fluctuation data to obtain a signal fluctuation evaluation value, and judging whether to perform signal fluctuation adjustment based on the signal fluctuation evaluation value, wherein the signal fluctuation evaluation value is used to evaluate the fluctuation degree of the preset sensor output signal, and the signal fluctuation data includes a maximum output signal amplitude and a minimum output signal amplitude; S3, obtaining a signal fluctuation evaluation value after signal fluctuation adjustment and obtaining a sensor interference evaluation value in combination with the obtained sensor interference data, and determining whether to perform sensor interference adjustment based on the sensor interference evaluation value, wherein the sensor interference evaluation value is used to evaluate the interference degree caused by the signal output of the preset sensor, and the sensor interference data includes an output signal amplitude and a noise signal amplitude; S4, providing operation and maintenance feedback according to the sensor stability performance evaluation value after the stability adjustment, the signal fluctuation evaluation value after the signal fluctuation adjustment, and the sensor interference evaluation value after the sensor interference adjustment; The specific process of obtaining the sensor stability performance evaluation value based on the acquired downhole sensor monitoring data is as follows: Acquire an initial temperature product by combining the reference resistance and the temperature change, wherein the initial temperature product is represented by a result of a ratio operation between the reference resistance and the temperature change; Acquire an initial temperature coefficient value by combining the resistance change amount and the initial temperature product, wherein the initial temperature coefficient value is represented by a result of a ratio operation of the resistance change amount and the initial temperature product; The temperature coefficient deviation is obtained by combining the initial temperature coefficient value and the preset temperature coefficient maximum threshold value obtained from the database, wherein the temperature coefficient deviation is represented by the result of performing a ratio operation and then a power operation on the difference between the initial temperature coefficient value and the preset temperature coefficient maximum threshold value and the preset temperature coefficient; Acquire an initial vibration acceleration by combining the sensor force and the sensor mass, wherein the initial vibration acceleration is represented by a result of a ratio operation of the sensor force and the sensor mass; Acquire a vibration acceleration deviation by combining the initial vibration acceleration and the preset maximum vibration acceleration threshold, wherein the vibration acceleration deviation is represented by a result of performing a ratio operation on the difference between the initial vibration acceleration and the preset maximum vibration acceleration threshold and the preset maximum vibration acceleration threshold and then performing a power operation; The sensor stability performance evaluation value is obtained by combining the temperature coefficient deviation, the vibration acceleration deviation, the first sensor stability weight and the second sensor stability weight.

2. A downhole operation and maintenance method based on big data analysis as claimed in claim 1, characterized in that: The limiting expression of the sensor stability performance evaluation value is as follows: ； ； ； In the formula, represents the sensor stability performance evaluation value of the qth preset sensor, , q represents the number of the preset sensor, s represents the total number of preset sensors, k represents the time variable, , Indicates the monitoring start time point, Indicates monitoring the current time point. represents the temperature coefficient deviation of the qth preset sensor at time k, represents the vibration acceleration deviation of the qth preset sensor at time k, represents the resistance change of the qth preset sensor at time k, represents the reference resistance of the qth preset sensor at time k, represents the temperature change of the qth preset sensor at time k, represents the sensor force of the qth preset sensor at time k, represents the sensor quality of the qth preset sensor at time k, represents the temperature coefficient range of the qth preset sensor at time k, represents the vibration acceleration range of the qth preset sensor at time k, Indicates the preset maximum temperature coefficient threshold, Indicates the preset maximum threshold of vibration acceleration. represents the stability weight of the first sensor, represents the second sensor stability weight, and e represents a natural constant.

3. A downhole operation and maintenance method based on big data analysis as claimed in claim 2, characterized in that: The specific process of judging whether to perform stability adjustment based on the sensor stability performance evaluation value is as follows: The first step is to determine whether the sensor stability performance evaluation value is not lower than the minimum stability threshold obtained from the database. If so, no stability adjustment is performed, otherwise the second step is executed; The second step is to perform temperature compensation. When the monitored sensor stability performance evaluation value is not lower than the minimum stability threshold obtained from the database, the stability adjustment is stopped. Otherwise, the third step is executed. The temperature compensation is used to improve the temperature stability of the preset sensor. The third step is to perform buffering and vibration reduction. When the stability performance evaluation value of the monitored sensor is not lower than the minimum stability threshold, stop the stability adjustment. Otherwise, send an alarm to the preset personnel.

4. A downhole operation and maintenance method based on big data analysis as claimed in claim 1, characterized in that: The specific process of obtaining the stability performance evaluation value of the sensor after stability adjustment and combining the obtained signal fluctuation data to obtain the signal fluctuation evaluation value is as follows: Acquire an output signal amplitude variation value by combining the output signal maximum value and the output signal minimum value, wherein the output signal amplitude variation value is used to reflect the output signal fluctuation of the preset sensor; The signal fluctuation deviation is obtained by combining the output signal amplitude change value and the preset signal change minimum threshold value obtained from the database. The signal fluctuation deviation is represented by the result of the ratio operation between the initial fluctuation amplitude change amount and the preset signal change minimum threshold value. The signal fluctuation deviation is used to reflect the deviation of the output signal fluctuation of the preset sensor; Obtaining a signal fluctuation evaluation value by combining the signal fluctuation deviation and a sensor stability performance evaluation value that is not less than a minimum stability threshold; The preset signal change minimum threshold is obtained from a database.

5. The underground operation and maintenance method based on big data analysis according to claim 4, characterized in that: The specific process of judging whether to perform signal fluctuation adjustment based on the signal fluctuation evaluation value is as follows: SS1, judging whether the signal fluctuation evaluation value is not higher than the signal fluctuation minimum threshold obtained from the database, when the signal fluctuation evaluation value is not higher than the signal fluctuation minimum threshold, no signal fluctuation adjustment is performed, otherwise SS2 is executed; SS2, digital filtering processing is performed. When the monitored signal fluctuation evaluation value is not higher than the minimum threshold of signal fluctuation, the signal fluctuation adjustment is stopped. Otherwise, SS3 is executed; SS3, for dynamic compensation, when the monitored signal fluctuation assessment value is not higher than the minimum threshold of signal fluctuation, stop adjusting the signal fluctuation, otherwise send an alarm prompt to the preset personnel.

6. The underground operation and maintenance method based on big data analysis as claimed in claim 1, characterized in that: The specific process of obtaining the signal fluctuation evaluation value after the signal fluctuation adjustment and obtaining the sensor interference evaluation value in combination with the obtained sensor interference data is as follows: Acquire an initial noise transfer by combining the output signal amplitude and the noise signal amplitude, wherein the initial noise transfer is represented by a result of a ratio operation between the output signal amplitude and the noise signal amplitude, and the initial noise transfer is used to reflect the noise interference of the preset sensor; Combining the initial noise transfer and the preset minimum sensor interference threshold obtained from the database to obtain a noise transfer deviation, wherein the noise transfer deviation is represented by a result of a ratio operation between the initial noise transfer and the preset minimum sensor interference threshold; Obtaining a sensor interference evaluation value by combining a noise transfer deviation, a signal fluctuation evaluation value that is not higher than a minimum signal fluctuation threshold, a first sensor interference weight, and a second sensor interference weight; The preset sensor interference minimum threshold, the first sensor interference weight and the second sensor interference weight are obtained from a database.

7. A downhole operation and maintenance method based on big data analysis as claimed in claim 6, characterized in that: The specific process of determining whether to perform sensor interference adjustment based on the sensor interference evaluation value is as follows: AQ1, judging whether the sensor interference evaluation value is not higher than the maximum interference threshold obtained from the database. When the sensor interference evaluation value is not higher than the maximum interference threshold, no sensor interference adjustment is performed, otherwise AQ2 is executed; AQ2, perform signal amplification, when the monitored sensor interference assessment value is not higher than the maximum interference threshold, stop sensor interference adjustment, otherwise execute AQ3; AQ3, perform interference isolation. When the monitored sensor interference assessment value is not higher than the maximum interference threshold, stop sensor interference adjustment. Otherwise, send an alarm prompt to the preset personnel. The interference isolation is used to cut off the coupling channel of signal interference.

8. The underground operation and maintenance method based on big data analysis as claimed in claim 1, characterized in that: The operation and maintenance feedback includes stability feedback, fluctuation feedback and interference feedback; The stability feedback means feeding back the obtained sensor stability performance evaluation value that is not less than the minimum stability threshold after stability adjustment to a preset data control center; The fluctuation feedback means feeding back the obtained signal fluctuation evaluation value which is not higher than the minimum threshold of signal fluctuation after signal fluctuation adjustment to a preset data control center; The interference feedback means feeding back the obtained sensor interference evaluation value which is not higher than the maximum interference threshold after the sensor interference adjustment to a preset data control center.

9. An underground operation and maintenance system based on big data analysis, characterized in that: It includes sensor stability performance evaluation module, signal fluctuation evaluation module, sensor interference evaluation module and operation and maintenance feedback module: The sensor stability performance evaluation module is used to obtain a sensor stability performance evaluation value according to the acquired downhole sensor monitoring data, and determine whether to perform stability adjustment based on the sensor stability performance evaluation value. The sensor stability performance evaluation value is used to evaluate the stability performance of a preset sensor deployed downhole. The downhole sensor monitoring data includes resistance change, reference resistance, temperature change, sensor force and sensor quality. The signal fluctuation evaluation module is used to obtain the stability performance evaluation value of the sensor after stability adjustment and obtain the signal fluctuation evaluation value in combination with the obtained signal fluctuation data, and judge whether to perform signal fluctuation adjustment based on the signal fluctuation evaluation value, the signal fluctuation evaluation value is used to evaluate the fluctuation degree of the preset sensor output signal, and the signal fluctuation data includes the maximum value of the output signal amplitude and the minimum value of the output signal amplitude; The sensor interference assessment module is used to obtain a signal fluctuation assessment value after signal fluctuation adjustment and obtain a sensor interference assessment value in combination with the obtained sensor interference data, and determine whether to perform sensor interference adjustment based on the sensor interference assessment value, wherein the sensor interference assessment value is used to assess the interference degree caused by the signal output of the preset sensor, and the sensor interference data includes the output signal amplitude and the noise signal amplitude; The operation and maintenance feedback module is used to provide operation and maintenance feedback according to the sensor stability performance evaluation value after stability adjustment, the signal fluctuation evaluation value after signal fluctuation adjustment, and the sensor interference evaluation value after sensor interference adjustment; The specific process of obtaining the sensor stability performance evaluation value based on the acquired downhole sensor monitoring data is as follows: Acquire an initial temperature product by combining the reference resistance and the temperature change, wherein the initial temperature product is represented by a result of a ratio operation between the reference resistance and the temperature change; Acquire an initial temperature coefficient value by combining the resistance change amount and the initial temperature product, wherein the initial temperature coefficient value is represented by a result of a ratio operation of the resistance change amount and the initial temperature product; The temperature coefficient deviation is obtained by combining the initial temperature coefficient value and the preset temperature coefficient maximum threshold value obtained from the database, wherein the temperature coefficient deviation is represented by the result of performing a ratio operation and then a power operation on the difference between the initial temperature coefficient value and the preset temperature coefficient maximum threshold value and the preset temperature coefficient; Acquire an initial vibration acceleration by combining the sensor force and the sensor mass, wherein the initial vibration acceleration is represented by a result of a ratio operation of the sensor force and the sensor mass; Acquire a vibration acceleration deviation by combining the initial vibration acceleration and the preset maximum vibration acceleration threshold, wherein the vibration acceleration deviation is represented by a result of performing a ratio operation on the difference between the initial vibration acceleration and the preset maximum vibration acceleration threshold and the preset maximum vibration acceleration threshold and then performing a power operation; The sensor stability performance evaluation value is obtained by combining the temperature coefficient deviation, the vibration acceleration deviation, the first sensor stability weight and the second sensor stability weight.

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