Radar vision fusion torque measurement and control system curve quality automatic judgment method

Abstract

The invention discloses a radar vision fusion torque measurement and control system curve quality automatic judgment method. The method comprises the following steps: S1, carrying out inflection point identification; s2, performing question graph judgment; s3, judging a special button type and a common button type; and S4, applying a matrix formula. According to the method, the operation efficiency of the petroleum instrument is remarkably improved, the manual operation time is shortened, the interference of human factors on the judgment result is reduced, and the consistency and repeatability of the judgment result are ensured. Meanwhile, through real-time and accurate identification and classification of the torque curve, unqualified graphs can be found in time, an alarm is given, and unqualified connection is prevented from entering a subsequent operation link, so that the connection quality of the casing pipe is effectively guaranteed, and more reliable technical support is provided for oil exploitation and drilling operation.

Description

Technical Field

[0001] The present invention relates to the field of petroleum equipment, and particularly to a method for automatically judging the curve quality of a radar-vision fusion torque measurement and control system for a hydraulic tong. Background Art

[0002] In oil extraction and drilling operations, the make-up and break-out of casing are key links, which are directly related to the safety and reliability of petroleum equipment. The sealing and stability of the casing connection are crucial for preventing oil leakage, avoiding environmental pollution, and ensuring operation safety. As a key device for casing make-up and break-out, the torque control accuracy of the hydraulic tong plays a decisive role in ensuring the quality of the casing connection. However, the current hydraulic tong torque measurement and control system still faces many challenges in practical applications.

[0003] Traditional methods mainly rely on manual observation of the torque-revolution curve to judge the make-up quality. This method has obvious limitations. First, manual judgment is subjective and relies on the experience of operators, which is easily interfered by human factors, resulting in inaccurate and unstable judgment results. Second, manual observation and judgment consume a large amount of time and energy. Especially in a high-intensity operation environment, operators are prone to fatigue, further reducing the judgment efficiency and accuracy. In addition, there are differences in the experience and judgment criteria of different operators, resulting in a lack of consistency and repeatability in judgment results, and it is difficult to achieve standardized operation.

[0004] With the development of automation technology, the hydraulic tong torque measurement and control system has been gradually popularized, but there are still many deficiencies in the existing technology for judging the curve quality. For example, when the existing system identifies the inflection point in the torque curve, there is no clear judgment standard, which is prone to misjudgment or missed judgment. The inflection point is a key feature point for judging the casing connection quality, and its identification accuracy directly affects the final judgment result. At the same time, when the existing system judges special thread types and ordinary thread types, there is no clear classification standard, which is prone to confusion. The judgment criteria for special thread types and ordinary thread types are different, and accurately distinguishing between them is crucial for ensuring the casing connection quality. In addition, when the existing system identifies suspicious graphics, there is no effective judgment logic, which is prone to misjudging normal graphics as suspicious graphics or missing real suspicious graphics. The accurate identification of suspicious graphics helps to timely discover potential problems and avoid unqualified connections from entering the subsequent operation links.

[0005] In order to improve the operation efficiency of oil equipment and the quality of casing connection, the industry urgently needs a method that can automatically judge the curve quality of the hydraulic tong torque measurement and control system. This method should have a high degree of automation, reduce manual intervention, and improve the judgment efficiency and accuracy. At the same time, it is necessary to provide clear inflection point identification, classification of special thread types and ordinary thread types, and judgment criteria for doubtful graphics to ensure the consistency and repeatability of judgment results. In addition, this method should also have real-time performance and reliability, be able to judge the curve quality in real time during actual operations, and give an alarm in time to prevent unqualified connections from entering the subsequent operation links. This automated judgment method will significantly improve the operation efficiency, reduce the labor intensity of operators, and at the same time improve the quality and reliability of casing connections, providing more powerful technical support for oil exploitation and drilling operations. Summary of the Invention

[0006] In view of this, the present invention provides an automatic judgment method for the curve quality of a radar-vision fusion torque measurement and control system.

[0007] To solve the above technical problems, the present invention adopts the following technical solutions:

[0008] An automatic judgment method for the curve quality of a radar-vision fusion torque measurement and control system includes the following steps:

[0009] Step S1: Conduct inflection point identification

[0010] The torque value corresponding to the inflection point must be between 10% and 70% of the optimal torque, and the difference in the number of turns between the inflection point position and the end position is not greater than 0.1 turn;

[0011] Step S2: Conduct doubtful graphic judgment

[0012] If the number of turns from the starting torque to the actual torque of the graphic is less than 0.25 turn, or when operating with special threads, the starting torque exceeds 10% of the optimal torque and there is a slipping or translation phenomenon, or the actual starting torque is greater than 10% of the optimal torque, or a large bevel graphic appears for special thread types, it is determined as a doubtful graphic;

[0013] Step S3: Conduct special thread type and ordinary thread type judgment

[0014] The special thread type has an inflection point, and the number of turns from the inflection point torque to the actual torque is within 0.3 turn and between 10% - 70% of the optimal torque, with a linear upward rush; the ordinary thread type has no inflection point;

[0015] Step S4: Application of matrix formula

[0016] The matrix method is used to fit the torque and number of turns data.

[0017] Preferably, in the above step S1, the specific judgment formula is:

[0018] T 拐点 ∈[0.1×T 最佳 , 0.7×T 最佳 , ΔN 周数 = N 终点 - N 拐点 ≤0.1;

[0019] Among them, T 拐点 is the torque value at the inflection point, T 最佳 is the optimal torque value, ΔN 周数 is the difference in the number of turns from the inflection point to the end point, N 终点 is the number of turns at the end point, N 拐点 is the number of turns at the inflection point;

[0020] If the determination of the inflection point exceeds 70% of the optimal torque, it is determined as an over-inflection torque; if the difference in the number of turns after the inflection point determination is greater than 0.1 turn, it is determined as an over-number-of-turns difference.

[0021] Preferably, in the step S1, the inflection point torque is judged to be qualified by calculating the inflection point slope:

[0022]

[0023] Among them, T 最终 is the final torque value, T 台阶 is the step torque value, ΔN 圈数 is the difference between the total number of turns during make-up and the number of turns from the start of make-up to the inflection point torque position;

[0024] If the slope is greater than 5, the inflection point torque is qualified; otherwise, it is unqualified.

[0025] Preferably, in the step S2, the specific judgment formula includes:

[0026]

[0027] Preferably, in the step S3, the specific judgment formula is:

[0028]

[0029] Preferably, in the step S4, assuming that the torque data vector is T and the number-of-turns data vector is N, then the linear relationship is fitted by the least squares method:

[0030] T = N·A + B;

[0031] Among them, A is the slope matrix and B is the intercept matrix;

[0032] By solving the least squares problem:

[0033]

[0034] The optimal slope and intercept can be obtained, and then it can be determined whether the slope at the inflection point 1 is qualified.

[0035] The present invention has achieved the following technical effects compared with the prior art:

[0036] (1) Significantly improved judgment accuracy: Through clear judgment criteria and algorithms, the present invention automatically identifies key feature points (such as inflection points), avoiding the subjectivity and errors of manual judgment;

[0037] Traditional methods rely on the experience and subjective judgment of operators and are easily interfered by human factors, resulting in inaccurate and unstable judgment results; while the automated judgment method adopted by the present invention, based on precise mathematical models and algorithms, can consistently apply the same judgment criteria to ensure the accuracy and repeatability of each judgment;

[0038] For example, in terms of inflection point identification, the present invention can accurately identify the inflection point and determine whether it is qualified by setting the conditions for the establishment of the inflection point (such as torque value range and number of weeks difference limit) and combining the inflection point slope judgment formula; this precise identification method significantly improves the accuracy of classifying special and ordinary casing types, reducing the possibility of misjudgment and missed judgment;

[0039] (2) Greatly improved operation efficiency: The present invention reduces the manual operation time and improves the operation efficiency;

[0040] Traditional methods require operators to spend a lot of time and energy observing and analyzing torque - number of weeks curves. Especially in a high - intensity operation environment, manual judgment is not only inefficient but also prone to judgment errors due to fatigue; while the automated judgment method of the present invention can complete a comprehensive judgment of the curve quality in a short time, greatly shortening the operation time and improving the production efficiency;

[0041] For example, in practical applications, the present invention can complete the judgment of a torque curve in a few seconds, while manual judgment may take several minutes or even longer; this improvement in efficiency is particularly important for large - scale casing connection operations in oil extraction and drilling operations, which can significantly improve the overall operation progress;

[0042] (3) Effectively improved connection quality: By accurately identifying and classifying torque curves, the present invention can timely detect unqualified graphics and give an alarm, effectively ensuring the quality of casing connections;

[0043] In oil extraction and drilling operations, the sealing performance and stability of casing connections are crucial for ensuring the safety and efficiency of operations; unqualified connections may lead to oil leakage, environmental pollution, and even safety accidents; the present invention can monitor and judge the quality of torque curves in real time, promptly detect potential problems and issue alarms, preventing unqualified connections from entering subsequent operation processes, thereby effectively ensuring the high quality and high reliability of casing connections;

[0044] For example, when the system detects a questionable or unqualified graph, it will immediately issue an alarm, prompting the operator to conduct further inspections or take corrective measures; this real-time monitoring and alarm mechanism can significantly reduce the risks caused by unqualified connections and improve the safety and reliability of oil equipment operations. Brief Description of the Drawings

[0045] Figure 1 It is a flowchart of an automatic judgment method for the curve quality of a radar-vision fusion torque measurement and control system according to the present invention;

[0046] Figure 2 It is a prototype design diagram of a special thread type torque control device for an automatic judgment method for the curve quality of a radar-vision fusion torque measurement and control system according to the present invention;

[0047] Figure 3 It is a verification diagram of the torque standard curve of a common thread type for an automatic judgment method for the curve quality of a radar-vision fusion torque measurement and control system according to the present invention. Detailed Embodiment

[0048] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0049] As Figure 1 shown, the present invention discloses an automatic judgment method for the curve quality of a radar-vision fusion torque measurement and control system, including the following steps:

[0050] Step S1: Conduct inflection point identification

[0051] The torque value corresponding to the inflection point must be between 10% and 70% of the optimal torque, and the difference in the number of turns between the inflection point position and the end point position is not greater than 0.1 turn;

[0052] The specific judgment formula is:

[0053] T 拐点 ∈[0.1×T 最佳 ,0.7×T 最佳 , △N周数 = N 终点 -N 拐点 ≤0.1;

[0054] Wherein, T 拐点 is the torque value at the inflection point, T 最佳 is the optimal torque value, ΔN 周数 is the difference in the number of turns from the inflection point to the end point, N 终点 is the number of turns at the end point, N 拐点 is the number of turns at the inflection point;

[0055] If the inflection point determination exceeds 70% of the optimal torque, it is determined as an over-inflection-point torque; if the difference in the number of turns after the inflection point determination is greater than 0.1 turn, it is determined as an over-number-of-turns difference;

[0056] Judge whether the inflection point torque is qualified by calculating the inflection point slope:

[0057]

[0058] Wherein, T 最终 is the final torque value, T 台阶 is the step torque value, ΔN 圈数 is the difference between the total number of turns during makeup and the number of turns from the starting torque of makeup to the position of the inflection point torque;

[0059] If the slope is greater than 5, the inflection point torque is qualified; otherwise, it is unqualified;

[0060] Step S2: Perform a judgment on the questionable graph

[0061] If the number of turns from the starting torque of the graph to the actual torque is less than 0.25 turn, or during the operation of special connections, the starting torque exceeds 10% of the optimal torque and there is a slipping or translation phenomenon, or the actual starting torque is greater than 10% of the optimal torque, or a large bevel graph appears for special connection types, it is determined as a questionable graph;

[0062] The specific judgment formula includes:

[0063]

[0064] Step S3: Perform a judgment on special connection types and ordinary connection types

[0065] Special connection types have an inflection point, and the number of turns from the inflection point torque to the actual torque is within 0.3 turn and between 10% - 70% of the optimal torque, with a linear upward rush; ordinary connection types have no inflection point;

[0066] The specific judgment formula is:

[0067]

[0068] Step S4: Application of the matrix formula

[0069] The torque and number of cycles data are fitted using a matrix method;

[0070] Assume the torque data vector is T and the number of cycles data vector is N, then the linear relationship is fitted by the least squares method:

[0071] T = N·A + B;

[0072] where A is the slope matrix and B is the intercept matrix;

[0073] By solving the least squares problem:

[0074]

[0075] The optimal slope and intercept can be obtained, and then it can be judged whether the slope at the 1 inflection point is qualified.

[0076] Example 1:

[0077] The automatic judgment algorithm automatically identifies the inflection point in the torque - number of cycles curve according to the preset inflection point establishment condition. The specific judgment formula is:

[0078] T 拐点 ∈[0.1×T 最佳 , 0.7×T 最佳 , △N 周数 = N 终点 - N 拐点 ≤ 0.1;

[0079] where T 拐点 is the torque value at the inflection point, T 最佳 is the optimal torque value, ΔN 周数 is the difference in the number of cycles from the inflection point to the end point, N 终点 is the end - point number of cycles, N 拐点 is the inflection - point number of cycles;

[0080] If the inflection point determination exceeds 70% of the optimal torque, it is determined as an over - inflection - point torque. The specific formula is:

[0081] T 拐点 > 0.7×T 最佳 ;

[0082] If the difference in the number of cycles after inflection point judgment is greater than 0.1 turn, it is determined as an over - number - of - cycles difference. The specific formula is:

[0083] △N 周数 > 0.1;

[0084] Calculate the inflection - point slope and judge whether the inflection - point torque is qualified. The specific formula is:

[0085]

[0086] If the slope is greater than 5, the inflection point torque is qualified; otherwise, it is unqualified.

[0087] Wherein, T 最终 is the final torque value, T 台阶 is the step torque value, ΔN 圈数 is the difference between the total number of turns of makeup and the number of turns from the starting point of makeup to the position of the inflection point torque.

[0088] Implementation process:

[0089] In the feature point recognition and curve quality classification stage, according to the preset inflection point establishment conditions, automatically identify the inflection point in the torque - number of turns curve, calculate the inflection point slope, and determine whether the inflection point torque is qualified. At the same time, check whether the number of turns corresponding to the starting torque to the actual torque of the graph is less than 0.25 turns, whether the starting torque during special connection operations exceeds 10% of the best torque and there is slipping or translation phenomenon, whether the actual starting torque is greater than 10% of the best torque, and whether there is a large - angle graph for special connection types.

[0090] According to the inspection results, determine whether the graph is a questionable graph; check whether there is an inflection point in the curve. If there is an inflection point and it meets the special connection type conditions, it is determined as a special connection type; otherwise, it is determined as a common connection type. When a questionable graph or an unqualified graph is detected, an alarm prompt is issued to remind the operator to take measures in a timely manner, and data recording and analysis are carried out for subsequent query and analysis; by analyzing the recorded data, the operator can understand the working state of the hydraulic tongs and the changing trend of curve quality, providing a basis for quality control and equipment maintenance, and helping the operator to discover potential problems and take improvement measures in a timely manner.

[0091] Through the above implementation manner, the present invention can significantly improve the efficiency and reliability of the torque measurement and control system of the hydraulic tongs, provide efficient and accurate technical support for oil extraction and drilling operations, and effectively ensure the quality and safety of casing connections.

[0092] The above - mentioned is only a preferred embodiment of the present invention, and does not impose any limitation on the technical scope of the present invention. Therefore, any minor modification, equivalent change, and modification made to the above - mentioned embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for automatically judging the curve quality of a radar vision fusion torque measurement and control system, characterized in that: The steps include: Step S1: Identify inflection points The torque value corresponding to the inflection point must be between 10% and 70% of the optimal torque, and the difference in the number of turns from the inflection point position to the end position must not exceed 0.1 turns; Step S2: Make a judgment on the questionable graphic If the number of cycles from the starting torque of the graphic to the actual torque is less than 0.25 turns, or the starting torque exceeds 10% of the optimal torque during special buckle operation and slippage or translation occurs, or the actual starting torque is greater than 10% of the optimal torque, or a large oblique angle graphic appears in the special buckle type, it is judged as a questionable graphic; Step S3: Determine special button type and common button type The special buckle type has an inflection point, and the number of cycles from the inflection point torque to the actual torque is within 0.3 turns, between 10%-70% of the optimal torque, and it is linearly upward; the ordinary buckle type has no inflection point; Step S4: Matrix formula application The torque and cycle number data were fitted using a matrix method.

2. The method for automatically judging the curve quality of a radar vision fusion torque measurement and control system according to claim 1 is characterized in that: In step S1, the specific judgment formula is: T 拐点 ∈[0.1×T 最佳 ,0.7×T 最佳 ],ΔN 周数 =N 终点 -N 拐点 ≤0.1; Among them, T 拐点 is the torque value at the inflection point, T 最佳 is the optimal torque value, ΔN 周数 N is the difference in weeks from the turning point to the end point. 终点 is the end week number, N 拐点 is the inflection point week number; If the inflection point is judged to exceed 70% of the optimal torque, it is judged to be an over-inflection point torque; if the difference in the number of turns after the inflection point is judged to be greater than 0.1 turns, it is judged to be an over-turn difference.

3. The method for automatically judging the curve quality of a radar vision fusion torque measurement and control system according to claim 2 is characterized in that: In step S1, whether the inflection point torque is qualified is determined by calculating the inflection point slope: Among them, T 最终 is the final torque value, T 台阶 is the step torque value, ΔN 圈数 It is the difference between the total number of make-up cycles and the number of make-up starting cycles to the inflection point torque position; If the slope is greater than 5, the inflection point torque is qualified; otherwise, it is unqualified.

4. The method for automatically judging the curve quality of a radar vision fusion torque measurement and control system according to claim 1 is characterized in that: In step S2, the specific judgment formula includes:

5. The method for automatically judging the curve quality of a radar vision fusion torque measurement and control system according to claim 1 is characterized in that: In step S3, the specific judgment formula is:

6. The method for automatically judging the curve quality of a radar vision fusion torque measurement and control system according to claim 1 is characterized in that: In step S4, assuming that the torque data vector is T and the cycle data vector is N, the linear relationship is fitted by the least squares method: T = N·A+B; Among them, A is the slope matrix and B is the intercept matrix; By solving the least squares problem: The optimal slope and intercept can be obtained, and then whether the slope of the inflection point 1 is qualified can be determined.

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