Data signal transmission method for shaft maintenance

Abstract

The invention relates to a data signal transmission method for shaft maintenance, which relates to the technical field of mine signal transmission, and comprises the following steps: through first communication equipment arranged on a derrick and second communication equipment arranged on a cage in a shaft, carrying out maintenance data transmission in the shaft, obtaining a transmission data sequence and carrying out cage shake prediction; obtaining a predicted shake parameter; according to the predicted shake parameter, obtaining a communication deviation angle and shake time, and according to the communication deviation angle, carrying out data transmission quality influence prediction to obtain a transmission quality influence parameter; according to the transmission quality influence parameter, the shaking time and the transmission data sequence, transmission data supplementation in the shaking time is carried out, and a transmission data sequence is obtained and generated; and according to the transmission quality influence parameter, generating data identification information for identification, and performing data signal transmission within the shaking time. The technical problem that in the prior art, stability and transmission quality of shaft overhaul data transmission are affected is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of mine signal transmission, and in particular to a data signal transmission method for mine shaft maintenance. Background Art

[0002] Shaft maintenance is an important part of safe mine operation, involving shaft structure detection, equipment maintenance, signal monitoring and other aspects. During shaft maintenance, the cage is usually used as the main vertical transportation tool for the transportation of personnel, equipment and monitoring instruments. At the same time, in order to achieve remote monitoring and real-time data transmission, wireless communication technology is usually used during shaft maintenance, so that the cage in the shaft can transmit data with the derrick outside the shaft, and then communicate with the hoisting room. However, during the maintenance process, the quality of data transmission will be disturbed, affecting the stability and quality of data transmission in the shaft. Summary of the invention

[0003] The present invention aims to solve the technical problem in the prior art that the data transmission quality is disturbed during wellbore maintenance, which affects the stability and transmission quality of data transmission in the wellbore, and provides a data signal transmission method for wellbore maintenance to solve the problem.

[0004] The technical solution of the present invention to solve the above technical problems is as follows: In a first aspect, the present invention provides a data signal transmission method for wellbore maintenance, comprising: transmitting wellbore maintenance data through a first communication device arranged on a derrick and a second communication device arranged in a cage in the wellbore, obtaining a transmission data sequence, performing cage sway prediction, and obtaining predicted sway parameters, wherein the transmission data includes a transmission image; According to the predicted jitter parameters, a communication deviation angle and a jitter time of the first communication device and the second communication device are acquired, and a data transmission quality impact prediction is performed according to the communication deviation angle to obtain a transmission quality impact parameter; According to the transmission quality influencing parameter, the shaking time and the transmission data sequence, the transmission data within the shaking time is supplemented to obtain a generated transmission data sequence; According to the transmission quality influencing parameter, data identification information is generated, the generated transmission data sequence is identified, the generated data is displayed within the shaking time, and the data signal transmission is continued.

[0005] The beneficial effect of the present invention is that the present invention improves the stability and reliability of wellbore maintenance data transmission by predicting cage sway and supplementing and optimizing data. Through the first communication device arranged on the derrick and the second communication device arranged in the cage in the wellbore, the wellbore maintenance data transmission is carried out to obtain the transmission data sequence, and the cage sway prediction is carried out, so that the cage operation status and data transmission situation can be collected in real time. According to the predicted sway parameters, the communication deviation angle and sway time of the first communication device and the second communication device are obtained, and the data transmission quality impact prediction is carried out according to the communication deviation angle, and the transmission quality impact parameter is obtained, so that the data transmission impact under different sway conditions can be accurately analyzed. Further, according to the transmission quality impact parameter, the sway time and the transmission data sequence, the transmission data within the sway time is supplemented to obtain the generated transmission data sequence, and according to the transmission quality impact parameter, data identification information is generated, the generated transmission data sequence is identified, and data signal transmission is carried out within the sway time. Through the data identification, the data transmission impact situation can be known, so that the receiving end can intelligently adjust the data processing strategy to ensure the real-time and reliability of the maintenance operation. The present invention improves the stability of data transmission during wellbore maintenance through technical means such as cage sway prediction, communication deviation angle calculation, transmission quality impact assessment, data supplementation and identification optimization, reduces the problems of signal attenuation, data loss and transmission quality degradation caused by cage sway, and thus improves the efficiency and safety of wellbore maintenance work. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1 A schematic flow chart of a data signal transmission method for wellbore maintenance provided by the present invention; Figure 2 A schematic diagram of a flow chart of predicting and obtaining predicted sloshing parameters in a data signal transmission method for wellbore maintenance provided by the present invention. DETAILED DESCRIPTION

[0007] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0008] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0009] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0010] Embodiment 1, as Figure 1 As shown, an embodiment of the present invention provides a data signal transmission method for wellbore maintenance, which specifically includes the following steps: S10: Transmit maintenance data in the wellbore through a first communication device arranged on the derrick and a second communication device arranged in the cage in the wellbore, obtain a transmission data sequence, predict cage sway, and obtain predicted sway parameters, wherein the transmission data includes a transmission image.

[0011] In the embodiment of the present application, wireless transmission of maintenance data in the wellbore is performed by means of a first communication device arranged on the derrick and a second communication device arranged in the cage in the wellbore.

[0012] During the transmission process, the transmitted data can be recorded to form a transmission data sequence. The transmission data includes images to reflect and record the maintenance progress and maintenance data in the wellbore.

[0013] In the embodiment of the present application, the cage will inevitably shake, vibrate or even swing during operation, which will interfere with the signals of the first communication device and the second communication device, and affect the quality and stability of data transmission. The shaking of the cage will be reflected in the transmission image in the transmission data, such as the transmission image showing a shaking trend. Therefore, the embodiment of the present application predicts the amplitude and time of the cage shaking by predicting the cage shaking based on the transmission image in the transmission data sequence, and obtains the predicted shaking parameters as the data basis for subsequent data transmission processing.

[0014] like Figure 2 As shown, step S10 in the method provided in the embodiment of the present application includes: Through the first communication device arranged on the derrick and the second communication device arranged in the cage in the wellbore, the maintenance data in the wellbore is transmitted to the hoisting room to obtain a transmission data sequence, wherein each transmission data includes a transmission image and a transmission voice; extracting a transmission image sequence within the transmission data sequence; The cage sway prediction is performed according to the transmission image sequence to obtain the predicted sway parameters.

[0015] In the embodiment of the present application, the first communication device arranged on the derrick is, for example, a mobile wireless base station arranged on the derrick at the wellbore mouth, and a directional antenna arranged vertically downward is arranged, and the second communication device arranged on the cage in the wellbore is, for example, a mobile wireless base station arranged on the cage in the wellbore, and a directional antenna arranged vertically upward is arranged. In this way, the directional antennas on the derrick and the cage are opposite to each other, and wireless data transmission is realized. In addition, after the first communication device on the derrick obtains the maintenance data transmission data in the wellbore, it can transmit the maintenance data to the hoisting room to form remote data transmission, and data can be transmitted between the derrick and the hoisting room through wireless transmission or optical fiber communication. In this way, maintenance data transmission in the wellbore and video communication between maintenance personnel and ground personnel can be realized.

[0016] When the cage shakes, the direction of the directional antennas on the derrick and cage will change from vertical to a certain angle, which will affect the stability and quality of the transmitted data.

[0017] During the data transmission process, maintenance data is collected and transmitted in real time to form a transmission data sequence, which includes transmission images and transmission voice. The transmission image can be high-definition image data such as the internal structure of the wellbore, tank channel status, etc., such as image data with a resolution of 1920×1080 and a frame rate of 30 frames. The transmission voice is the voice communication data of the maintenance personnel, which is used for remote communication or voice command issuance, and the sampling rate is usually 16kHz. The transmitted transmission image and transmission voice data are arranged in chronological order to form a transmission data sequence. For example, the transmission image and transmission voice data within the last 3 seconds are arranged to form a transmission data sequence.

[0018] Furthermore, a transmission image sequence is extracted from the transmission data sequence, that is, image data is separated from continuous data packets for cage sway analysis. Since the cage will sway due to inertia, wire rope tension changes or external disturbances during the operation of the wellbore, the transmission image includes the characteristics before the cage sway occurs, such as the position change of fixed reference objects (such as tankways and guide rails) in the transmission image. Based on this, cage sway prediction can be performed according to the transmission image sequence to predict the angle and time of cage sway and form predicted sway parameters.

[0019] The step of "predicting cage sway according to the transmitted image sequence to obtain predicted sway parameters" in the method provided in the embodiment of the present application includes: Based on the wellbore maintenance transmission data in the historical time, a set of sample transmission image sequences is collected, and the maximum shaking angle and continuous shaking time of the cage shaking after different sample transmission image sequences are collected, which are marked as a sample shaking parameter set; Build a sway predictor based on convolutional neural network; Using the sample transmission image sequence set and the sample shake parameter set, supervised training and testing are performed on the shake predictor until the accuracy meets the requirement; The transmission image sequence is input into the jitter predictor, and the predicted jitter parameters are obtained by predicting the output.

[0020] In the embodiment of the present application, a convolutional neural network in deep learning is used to predict the sway parameters of the cage based on the transmitted image sequence.

[0021] First, in the transmission data of wellbore maintenance in the historical time, for example, in the transmission data collected and recorded during the wellbore maintenance in the past year, multiple sample transmission image sequences collected during the previous maintenance are collected to form a set of sample transmission image sequences. For example, each sample transmission image sequence includes 90 frames of transmission images for 3 seconds.

[0022] Further, the maximum shaking angle and continuous shaking time of the cage shaking within the preset time range after different sample transmission image sequences are collected. The preset time range is, for example, 5 seconds. That is, according to the data log recorded in the maintenance process in the historical time, the maximum shaking angle and continuous shaking time of the cage shaking within the preset time range after each sample transmission image sequence are obtained. The maximum shaking angle is the maximum angle between the axis and the vertical direction when the cage shakes within the preset time range, for example, 15 degrees. The continuous shaking time is, for example, the time from when the shaking angle of the cage is greater than the shaking angle threshold to when the shaking angle stops when the shaking angle is less than the shaking angle threshold, for example, 2s. The shaking angle threshold is, for example, 5°, that is, the maximum shaking angle that does not affect the data transmission quality, which can be obtained by performing a data transmission quality test when the cage shakes. In this way, the corresponding multiple maximum shaking angles and multiple continuous shaking times are collected and obtained, and are marked as a sample shaking parameter set. Each sample shaking parameter includes a maximum shaking angle and a continuous shaking time.

[0023] Furthermore, based on a convolutional neural network, a shake predictor is constructed, which includes an input layer, multiple convolutional layers, multiple pooling layers, a fully connected layer and an output layer. Exemplarily, the convolutional layer includes 3 layers, including 32, 64 and 128 3×3 convolution kernels respectively, for extracting features in the transmission image, the pooling layer includes 3, the pooling window size is 2×2, the fully connected layer structure is 256-128, the ReLU activation function is used, and the mean square error loss function is used during the training process. The output layer dimension is 2, which are the maximum shake angle and the continuous shake time in the shake parameters respectively. During the training process, the sample transmission image sequence is input, the output shake parameters are obtained, and the error with the actual shake parameters is calculated, for example, the square of the error of the maximum shake angle and the continuous shake time is calculated respectively as the loss, and the network parameters are optimized according to the loss to reduce the loss, and the iterative training is performed in this way. The data can be divided into 20% in the sample transmission image sequence set and the sample shake parameter set for testing. When the test loss is less than the requirement, for example, the maximum shake angle prediction error is < 0.5° and the continuous shake time prediction error is < 0.2s, the training is completed.

[0024] Based on the trained sway predictor, the current transmission image sequence is input to obtain the predicted sway parameters of the prediction output, including the predicted maximum sway angle and continuous sway time, to complete the sway prediction of the cage.

[0025] The embodiment of the present application realizes intelligent prediction of cage sway through historical data collection, deep learning model training and real-time prediction, which then serves as the data basis for subsequent optimization and adjustment of data transmission, thereby improving the stability and quality of wireless transmission of maintenance data in the wellbore.

[0026] S20: Acquire a communication deviation angle and a jitter time between the first communication device and the second communication device according to the predicted jitter parameter, and predict the impact on data transmission quality according to the communication deviation angle to obtain a transmission quality impact parameter.

[0027] In an embodiment of the present application, it is necessary to quantitatively analyze the impact on data transmission of the first communication device and the second communication device based on the predicted jitter parameters. Specifically, based on the predicted jitter parameters, the communication deviation angle and jitter time of the first communication device and the second communication device are obtained, and then the impact on data transmission quality is predicted based on the communication deviation angle, and the transmission quality impact parameters are obtained. The degree of impact on data transmission quality is quantified, and subsequent data transmission strategy adjustments are made.

[0028] Step S20 in the method provided in the embodiment of the present application includes: Obtaining a maximum shaking angle and a continuous shaking time within the predicted shaking parameters; The communication deviation angle between the first communication device and the second communication device is calculated according to the maximum shaking angle, and the continuous shaking time is used as the shaking time.

[0029] In the embodiment of the present application, based on the predicted shake parameters obtained in the above-mentioned prediction, the maximum shake angle and the continuous shake time are extracted, for example, 25° and 4s respectively.

[0030] Furthermore, it can be determined whether the maximum shaking angle is greater than or equal to the shaking angle threshold. If so, it means that the currently predicted shaking parameters will affect data transmission, and the next step is performed. If not, it means that the currently predicted shaking parameters will not affect data transmission, and the continuous shaking time output at this time is 0, and the next step is not performed, and data transmission and monitoring continue.

[0031] Furthermore, based on the maximum shaking angle, the communication deviation angle between the first communication device and the second communication device is calculated, wherein the shaking of the cage may cause the antenna direction of the communication device to change, thereby generating a communication deviation angle and affecting the signal quality.

[0032] The tank cage is in a vertical state under normal conditions. When it shakes and produces the maximum shaking angle, the directional antenna in the second communication device also shakes with it, which causes an angle between it and the direction of the directional antenna in the first communication device. This angle is the communication deviation angle. Since the second communication device shakes with the tank cage, the communication deviation angle is the maximum shaking angle, for example 25°.

[0033] Furthermore, the continuous shaking time within the predicted shaking parameters is taken as the shaking time. The communication deviation angle and shaking time are used as the data basis for subsequent analysis of the impact on data transmission quality and supplementary generation of transmission data.

[0034] Step S20 in the method provided in the embodiment of the present application further includes: According to the historical data of wellbore data transmission, a set of sample communication deviation angles is collected, and the data transmission quality impact amplitudes under different sample communication deviation angles are collected, which are marked as a set of sample transmission quality impact parameters; A feed-forward neural network is used to construct a data transmission impact predictor; Using the sample communication deviation angle set and the sample transmission quality impact parameter set, supervised training is performed on the data transmission impact predictor until the accuracy meets the requirement; The communication deviation angle is input into the data transmission impact predictor, and the prediction output is used to obtain the transmission quality impact parameter.

[0035] In the embodiment of the present application, the shaking of the cage will cause the change of the communication deviation angle, thereby affecting the quality of data transmission. In order to accurately predict the impact of the communication deviation angle on the quality of data transmission, a data transmission impact predictor is constructed based on the historical data of wellbore data transmission, so as to perform corresponding processing when the cage shakes, such as supplementing the generation of transmission data or issuing an early warning. Specifically, the impact of the currently predicted cage shaking on data transmission is analyzed based on the communication deviation angle.

[0036] Among them, according to the historical data transmission in the wellbore maintenance in the historical time, multiple communication deviation angles monitored when the cage sway occurred before are collected to obtain a sample communication deviation angle set. For example, the sample communication deviation angle is 10°, 15°, 17°, etc. The sample communication deviation angle can be obtained by installing a gyroscope in the cage to actually measure the cage sway angle.

[0037] Furthermore, the data transmission quality impact amplitude under different sample communication deviation angles is collected, for example, the bit error rate in data transmission is specifically collected, and marked as the sample transmission quality impact parameter to obtain a set of sample transmission quality impact parameters. For example, the sample transmission quality impact parameters are 1.02%, 3.87%, and 8.94%. The sample transmission quality impact parameters can be obtained by performing data transmission tests when the cage shakes at different angles to produce different sample communication deviation angles.

[0038] Furthermore, a feedforward neural network in machine learning is used to construct a data transmission impact predictor, which includes an input layer, a hidden layer, and an output layer. The hidden layer includes two layers, which contain 32 and 16 nodes respectively, and a ReLU activation function is used. During the training process, the sample communication deviation angle is input to obtain the output transmission quality impact parameter, and the difference with the corresponding sample transmission quality impact parameter is calculated. The loss is calculated by the mean square error loss function, and the network parameters such as the node weight are adjusted according to the loss to reduce the loss and perform training optimization. The training is completed until the loss of the test data transmission impact predictor is less than the requirement, for example, less than 0.01%.

[0039] Based on the trained data transmission impact predictor, the current communication deviation angle is input, the output transmission quality impact parameter is obtained, and the data transmission quality impact prediction based on the communication deviation angle is completed.

[0040] Through the above steps, the embodiment of the present application can achieve real-time prediction of changes in communication quality caused by cage shaking, and then provide a reference for decision-making when data transmission stability is affected, such as subsequent generation of supplementary data or abnormal data transmission warning, thereby improving the safety of mine equipment maintenance and the stability of data transmission.

[0041] S30: supplementing the transmission data within the jitter time according to the transmission quality influencing parameter, the jitter time and the transmission data sequence, to obtain a generated transmission data sequence.

[0042] In an embodiment of the present application, when the tank cage shakes and data transmission is affected, in order to repair the continuity of data transmission, for example, to repair the continuity of video communication, the transmission data within the shaking time is supplemented and generated according to the transmission quality influencing parameters, the shaking time and the transmission data sequence, to form a generated transmission data sequence, and the transmission data within the shaking time is supplemented, thereby improving the continuity and stability of data transmission.

[0043] Step S30 in the method provided in the embodiment of the present application includes: Construct a supplementary channel for transmitting data; The transmission data sequence, transmission quality influencing parameters and jitter time are input into the transmission data supplement channel to supplement and generate transmission data within the future jitter time range to obtain a transmission data sequence.

[0044] In the embodiment of the present application, a transmission data supplement channel for supplementing the generated transmission data is first constructed, wherein a generative adversarial network is preferably used to construct the transmission data supplement channel.

[0045] The step of "constructing a transmission data supplement channel" in the method provided in the embodiment of the present application includes: According to the local historical maintenance data and historical transmission data of the cage in the wellbore maintenance, a sample transmission data sequence set, a sample transmission quality influencing parameter set, and a sample shaking time set are collected, and a transmission data sequence within the sample shaking time after each sample transmission data sequence is collected and marked as a sample generated transmission data sequence set; Generative adversarial networks are used to construct generators and discriminators to obtain transmission data supplement channels; The sample transmission data sequence set, the sample transmission quality influencing parameter set, the sample shaking time set and the sample generated transmission data sequence set are used to perform supervised training on the transmission data supplement channel until the accuracy meets the requirements, wherein the generator and the discriminator are trained alternately.

[0046] In an embodiment of the present application, based on the local historical maintenance data and historical transmission data of the cage in the wellbore maintenance, that is, the historical maintenance image data collected by the local camera equipment of the cage and the transmitted historical transmission data, a sample transmission data sequence set, a sample transmission quality influencing parameter set, and a sample shaking time set are collected when the cage shook during the previous data transmission. The sample transmission quality influencing parameter set and the sample shaking time set can both be obtained by processing the above content.

[0047] Further, the transmission data sequence within the sample shaking time after each sample transmission data sequence is collected. For example, if the sample shaking time is 3s, the transmission data sequence within 3s after the sample transmission data sequence is collected and marked as the sample generated transmission data sequence to obtain the sample generated transmission data sequence. If the data transmission quality is lost due to shaking and the data transmission is lost, it can be collected in the local historical maintenance data of the cage in the wellbore maintenance.

[0048] Furthermore, a generative adversarial network is used to construct a generator and a discriminator to form a transmission data supplement channel. The sample transmission data sequence set, the sample transmission quality influencing parameter set, and the sample shaking time set are used as the supervised training data of the generator, and the sample generated transmission data sequence set is used as the supervised training data of the discriminator to perform supervised training of the transmission data supplement channel. During the training process, the generator and the discriminator are trained alternately.

[0049] Exemplarily, the generator is responsible for generating a transmission data sequence, compensating for the transmission data missing due to the influence of data transmission quality, using an LSTM network, and using ReLU as the activation function. The discriminator is used to distinguish between real data (transmission data sequence generated by samples) and generated data (transmission data sequence generated by the generator), and improve the authenticity of the transmission data supplement generation. During the training process, the learning rate is set to 0.0002, and the loss function of the generator is the mean square error loss function. The error between the generated transmission data sequence and the sample generated transmission data sequence is calculated to calculate the loss, and the network parameters are tuned to reduce the loss until convergence, for example, the accuracy reaches 95%. The loss of the discriminator is the error of discrimination, and the loss is calculated based on the binary cross entropy loss function. The network parameters are tuned according to the loss to reduce the loss until convergence, for example, the discrimination error is less than 5%. In alternating training, after training the generator for one round, the discriminator is trained, and the alternating training is completed in this way until both the generator and the discriminator converge, and a transmission data supplement channel with training is obtained.

[0050] Based on the trained transmission data supplement channel, the current transmission data sequence, transmission quality influencing parameters and shaking time are input to supplement the generated transmission data within the future shaking time range, forming a generated transmission data sequence, which serves as the transmission data to supplement the data transmission loss during the shaking time, so as to improve the stability and transmission quality of data transmission.

[0051] Among them, the methods provided in the embodiments of the present application are all processed in the hoisting room after data transmission, which has a large amount of computing power deployed, can execute the above steps, and generate the above-mentioned transmission data sequence during data transmission, and then display it to improve the continuity and stability of data transmission in the wellbore.

[0052] This method uses a generative adversarial network to supplement data when it is lost, and generates transmission data during the period when cage shaking affects data transmission. This solution can effectively improve the stability and integrity of shaft maintenance data transmission, reduce the impact of cage shaking on data quality, and ensure the safety and efficiency of mine maintenance operations.

[0053] S40: Generate data identification information according to the transmission quality influencing parameter, identify the generated transmission data sequence, display the generated data within the shaking time, and continue to transmit the data signal.

[0054] In the embodiment of the present application, when the transmission data sequence is generated by supplementary generation, since it is generated by the above-mentioned deep learning means, there may be some errors. Therefore, it is necessary to generate data identification information based on the transmission quality influencing parameters to identify the generated transmission data sequence, so as to remind the staff that this part of the generated transmission data sequence is obtained by supplementary generation, and remind the staff of the degree to which the current cage shaking affects the data transmission quality, and then collect corresponding measures, such as early warning or adjustment of data transmission strategy.

[0055] After marking the generated transmission data sequence, it is displayed during the shaking time to complete the supplement of data transmission during the shaking period, and after the shaking time, the data signal transmission is continued, and the prediction of the cage shaking and data transmission processing are continued based on the above method.

[0056] Step S40 in the method provided in the embodiment of the present application includes: generating data identification information according to the transmission quality influencing parameter; The data identification information is used to identify the generated transmission data sequence, the generated data is displayed within the shaking time, and the data signal transmission is continued.

[0057] In the embodiment of the present application, data identification information is generated according to the transmission quality impact parameter, for example, the transmission quality impact parameter is directly used as the data identification information. For example, if the transmission quality impact parameter includes a bit error rate of 3.5%, then for example, "the current data transmission bit error rate is 3.5%, and the transmission data within 3 seconds is auxiliary generated data" is used as the data identification information for identification.

[0058] Alternatively, the data transmission quality impact can be graded according to the bit error rate within the transmission quality impact parameters. For example, a bit error rate within 0-3% is a small impact, a bit error rate within 3-8% is a general impact, and a bit error rate above 8% is a serious impact. The data transmission quality impact parameters are graded according to the interval into which the bit error rate falls. For example, "the current data transmission quality impact is general, and the transmission data within 3 seconds is auxiliary generated data" is generated as data identification information.

[0059] Furthermore, the data identification information is used to identify the generated transmission data sequence, the generated data is displayed during the shaking time, and the data signal transmission continues after the shaking time.

[0060] The embodiment of the present application generates data identification information, marks the generated data sequence, and displays the data during the cage shaking time to ensure the continuity and stability of data transmission. At the same time, it can remind the staff of the extent of the impact of cage shaking on the data transmission quality, which can serve as a reference for decision-making and enhance the safety and reliability of mine maintenance.

[0061] The data signal transmission method for wellbore maintenance provided by the embodiment of the present invention has at least the following technical effects: The embodiment of the present invention improves the stability and reliability of wellbore maintenance data transmission by predicting cage sway and performing data supplementation and optimization. Through the first communication device arranged on the derrick and the second communication device arranged in the cage in the wellbore, the wellbore maintenance data transmission is carried out to obtain the transmission data sequence, and the cage sway prediction is performed, so that the cage operation status and data transmission situation can be collected in real time. According to the predicted sway parameters, the communication deviation angle and sway time of the first communication device and the second communication device are obtained, and the data transmission quality impact prediction is performed according to the communication deviation angle, and the transmission quality impact parameter is obtained, so that the data transmission impact under different sway conditions can be accurately analyzed. Further, according to the transmission quality impact parameter, the sway time and the transmission data sequence, the transmission data within the sway time is supplemented to obtain the generated transmission data sequence, and according to the transmission quality impact parameter, data identification information is generated, the generated transmission data sequence is identified, and data signal transmission is performed within the sway time. Through the data identification, the data transmission impact situation can be known, so that the receiving end can intelligently adjust the data processing strategy to ensure the real-time and reliability of the maintenance operation. The present invention improves the stability of data transmission during wellbore maintenance through technical means such as cage sway prediction, communication deviation angle calculation, transmission quality impact assessment, data supplementation and identification optimization, reduces the problems of signal attenuation, data loss and transmission quality degradation caused by cage sway, and thus improves the efficiency and safety of wellbore maintenance work.

[0062] Although preferred embodiments of the present invention have been described, additional changes and modifications may occur to these embodiments once those skilled in the art understand the basic inventive concepts.

[0063] 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 belong to the scope of the present invention and its equivalent technologies, the present invention is also intended to include these changes and variations.

Claims

1. A data signal transmission method for wellbore maintenance, characterized in that: The method comprises: Through the first communication device arranged on the derrick and the second communication device arranged in the cage in the wellbore, the wellbore maintenance data is transmitted to obtain the transmission data sequence, the cage sway is predicted, and the predicted sway parameters are obtained, wherein the transmission data includes the transmission image; According to the predicted jitter parameters, a communication deviation angle and a jitter time of the first communication device and the second communication device are acquired, and a data transmission quality impact prediction is performed according to the communication deviation angle to obtain a transmission quality impact parameter; According to the transmission quality influencing parameter, the shaking time and the transmission data sequence, the transmission data within the shaking time is supplemented to obtain a generated transmission data sequence; According to the transmission quality influencing parameter, data identification information is generated, the generated transmission data sequence is identified, the generated data is displayed within the shaking time, and the data signal transmission is continued.

2. The data signal transmission method for wellbore maintenance according to claim 1, characterized in that: Through the first communication device arranged on the derrick and the second communication device arranged in the cage in the wellbore, the wellbore maintenance data is transmitted, the transmission data sequence is obtained, the cage sway is predicted, and the predicted sway parameters are obtained, including: Through the first communication device arranged on the derrick and the second communication device arranged in the cage in the wellbore, the maintenance data in the wellbore is transmitted to the hoisting room to obtain a transmission data sequence, wherein each transmission data includes a transmission image and a transmission voice; extracting a transmission image sequence within the transmission data sequence; The cage sway prediction is performed according to the transmission image sequence to obtain the predicted sway parameters.

3. The data signal transmission method for wellbore maintenance according to claim 2, characterized in that: According to the transmission image sequence, cage sway prediction is performed to obtain predicted sway parameters, including: Based on the wellbore maintenance transmission data in the historical time, a set of sample transmission image sequences is collected, and the maximum shaking angle and continuous shaking time of the cage shaking after different sample transmission image sequences are collected, which are marked as a sample shaking parameter set; Build a sway predictor based on convolutional neural network; Using the sample transmission image sequence set and the sample shake parameter set, supervised training and testing are performed on the shake predictor until the accuracy meets the requirement; The transmission image sequence is input into the shake predictor, and the predicted shake parameter is obtained by predicting the output.

4. The data signal transmission method for wellbore maintenance according to claim 1, characterized in that: Acquiring a communication deviation angle and a shaking time of the first communication device and the second communication device according to the predicted shaking parameter, including: Obtaining a maximum shaking angle and a continuous shaking time within the predicted shaking parameters; The communication deviation angle between the first communication device and the second communication device is calculated according to the maximum shaking angle, and the continuous shaking time is used as the shaking time.

5. The data signal transmission method for wellbore maintenance according to claim 1, characterized in that: The impact on data transmission quality is predicted based on the communication deviation angle, and the transmission quality impact parameters are obtained, including: According to the historical data of wellbore data transmission, a set of sample communication deviation angles is collected, and the data transmission quality impact amplitudes under different sample communication deviation angles are collected, which are marked as a set of sample transmission quality impact parameters; A feed-forward neural network is used to construct a data transmission impact predictor; Using the sample communication deviation angle set and the sample transmission quality impact parameter set, supervised training is performed on the data transmission impact predictor until the accuracy meets the requirement; The communication deviation angle is input into the data transmission impact predictor, and the prediction output is used to obtain the transmission quality impact parameter.

6. The data signal transmission method for wellbore maintenance according to claim 1, characterized in that: According to the transmission quality influencing parameter, the jitter time and the transmission data sequence, the transmission data within the jitter time is supplemented to obtain a transmission data sequence, including: Construct a supplementary channel for transmitting data; The transmission data sequence, transmission quality influencing parameters and jitter time are input into the transmission data supplement channel to supplement and generate transmission data within the future jitter time range to obtain a transmission data sequence.

7. The data signal transmission method for wellbore maintenance according to claim 6, characterized in that: Construct a supplementary channel for transmitting data, including: According to the local historical maintenance data and historical transmission data of the cage in the wellbore maintenance, a sample transmission data sequence set, a sample transmission quality influencing parameter set, and a sample shaking time set are collected, and a transmission data sequence within the sample shaking time after each sample transmission data sequence is collected and marked as a sample generated transmission data sequence set; Generative adversarial networks are used to construct generators and discriminators to obtain transmission data supplement channels; The sample transmission data sequence set, the sample transmission quality influencing parameter set, the sample shaking time set and the sample generated transmission data sequence set are used to perform supervised training on the transmission data supplement channel until the accuracy meets the requirements, wherein the generator and the discriminator are trained alternately.

8. The data signal transmission method for wellbore maintenance according to claim 1, characterized in that: According to the transmission quality influencing parameter, data identification information is generated, the generated transmission data sequence is identified, the generated data is displayed within the shaking time, and the data signal transmission is continued, including: generating data identification information according to the transmission quality influencing parameter; The data identification information is used to identify the generated transmission data sequence, the generated data is displayed within the shaking time, and the data signal transmission is continued.

Images