An oil and gas station character interaction dynamic positioning method, system and device

Abstract

The application discloses an oil and gas station character interactive dynamic positioning method, system and device, relates to the technical field of data interaction analysis, and the oil and gas station character interactive dynamic positioning method comprises the following steps: acquiring observation data; detecting and repairing cycle slip of the observation data, and acquiring recovered cycle slip data; based on real-time dynamic differential positioning technology of high-precision carrier phase observation value, higher-precision unknown position coordinates are solved out; latitude and longitude data under a positioning terminal are acquired and are converted into station heart polar coordinate data; when the positioning terminal signal is weak or positioning information cannot be acquired, fusion positioning is carried out based on inertial navigation RTK technology, and position data of personnel are acquired; and according to the equipment type and task scene bound by the positioning terminal, behavior logic judgment is carried out on the person as the center. The application can effectively improve the problem that it is not easy to accurately position the distance of the character in the existing safety operation process, and real-time early warning is carried out.

Description

Technical Field

[0001] This invention relates to the field of data interaction and analysis technology, specifically to a method, system, and device for dynamic positioning of human interaction at oil and gas stations. Background Technology

[0002] In oilfield operations, numerous violations are caused by human error, and workers often lack safety awareness, unknowingly entering high-risk areas. While monitoring equipment is currently in place, the cameras themselves lack intelligent event analysis and distance recognition capabilities, meaning most violation detection still relies primarily on human observation. Furthermore, some systems employ computer vision-based intelligent recognition methods. These methods typically rely on two-dimensional images captured by monitoring cameras for subsequent intelligent recognition algorithm processing. However, images captured by traditional imaging devices often lose depth information of objects in three-dimensional space. This makes two-dimensional image-based processing often inadequate for handling spatially sensitive scenarios.

[0003] On the other hand, utilizing wireless technology for positioning has become a development trend in the field of positioning research. Currently, the mainstream positioning methods mainly include Bluetooth positioning, UWB positioning, GNSS positioning, and RTK positioning. In oilfield operation scenarios, the operating area is large and flexible, making it unsuitable to set up fixed base stations; the prevalence of steel structures in these scenarios severely obstructs and blocks signals. These factors result in numerous problems with the aforementioned positioning technologies, such as insufficient positioning range, insufficient positioning accuracy, easy loss and drift of positioning data, high deployment costs, and difficult maintenance, failing to meet the precise positioning needs of personnel interaction in oilfield scenarios.

[0004] Therefore, given the need for monitoring in large-scale, long-distance, and harsh environments, there is an urgent need for a high-precision positioning method to meet the positioning requirements for personnel interaction in oilfield scenarios. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to disclose a dynamic positioning method, system and device for personnel interaction at oil and gas stations, so as to achieve accurate positioning of personnel distance and real-time early warning during safe operation.

[0006] To achieve the above and other related objectives, this invention discloses a dynamic positioning method for human-person interaction at oil and gas stations, comprising:

[0007] Step S10: Obtain observation data;

[0008] Step S20: Detect and repair cycle slips in the observed data, and obtain recovered cycle slip data;

[0009] Step S30: Based on the real-time dynamic differential positioning technology of high-precision carrier phase observations, the coordinates of the unknown position with higher accuracy are calculated.

[0010] Step S40: Obtain latitude and longitude data from the positioning terminal and convert it into station-centered polar coordinate data;

[0011] Step S50: When the positioning terminal signal is weak or positioning information cannot be obtained, fusion positioning is performed based on inertial navigation RTK technology, and the location data of the personnel is obtained.

[0012] Step S60: Based on the device type and task scenario bound to the positioning terminal, perform behavioral logic judgment centered on the human.

[0013] In one aspect of the present invention, step S20, the detection of cycle slips in the observed data, includes:

[0014] 1) Start an interruption count at the epoch when the data is lost. Assume that the epoch is t1 and the epoch when it is recaptured is t2. Then the time of loss is Δt = t2 - t1.

[0015] 2) Set the sampling interval of the higher-order difference method to Δt to ensure equal-interval sampling;

[0016] 3) Interpolate the original data, interpolating carrier observations with a sampling interval of Δt to a sampling interval of 1s to construct high sampling rate data;

[0017] 4) The high-order difference method is used for fourth-order difference detection.

[0018] In one aspect of the present invention, step S20, which involves repairing the observed data, includes:

[0019] Ambiguity resolution is performed on the delayed observations, and the ambiguity resolution ratio values ​​of the current epoch and the previous epoch are compared.

[0020] If the addition of a new satellite causes the calculated Ratio value to drop below the threshold or to half of the Ratio value of the previous epoch, then the satellite will be disqualified from participating in the calculation and a recalculation will be performed.

[0021] In one aspect of the present invention, step S30 includes:

[0022] Based on the LAMBDA algorithm, and in this method, the double-difference integer ambiguity is fixed in the LAMBDA algorithm;

[0023] Delete the fuzzyness with the largest variance value from the set of fuzzynesses to be fixed;

[0024] The ambiguity is fixed by iterative loops, and as much carrier phase integer ambiguity as possible is fixed while ensuring the correctness of the fixation.

[0025] In one aspect of this invention, the integer ambiguity value is calculated based on an adaptive differential evolution algorithm, which includes:

[0026] Before fixing the ambiguity, the ambiguity is first reduced and the fitness function distribution is changed from a non-monotonic function to a monotonic function with only one extreme value.

[0027] The algorithm search is executed, and when the algorithm search is completed, the Ratio value of the fixed solution at this time is checked to determine whether the algorithm has gotten stuck in a local optimum.

[0028] The ratio of the sum of squared residuals of the suboptimal and optimal solutions in the fixed solution is used as the test value. It is compared with a set threshold, which is usually 2 or 3. When the ratio value is greater than the threshold, the fixed solution of ambiguity is determined to be correct.

[0029] In one aspect of this invention, the Ratio value verification includes the following steps:

[0030] The test is performed using the ratio of the residual quadratic form of the optimal solution to that of the suboptimal solution, expressed as:

[0031]

[0032] In the formula, a sec a min These represent the suboptimal and optimal solutions to the ambiguity, respectively, with c being the threshold. The ratio of these two solutions is set to a fixed empirical value, typically 2 or 3.

[0033] In one aspect of the present invention,

[0034] In step S50, when the positioning terminal signal is weak or positioning information cannot be obtained, the step of performing fusion positioning based on inertial navigation RTK technology and obtaining personnel position data includes a navigation parameter calculation method based on gyroscopes and accelerometers as sensing elements. This method includes:

[0035] The heading angle A can be obtained by integrating the angular velocity measured by the gyroscope. t , including A t =∫ωd t +A0;

[0036] The measurement information from the inertial measurement unit is converted into the navigation coordinate system, including:

[0037] The change in target velocity generates acceleration a in the IMU coordinate system. y acceleration a in the navigation coordinate system Nvia heading angle A t The measurement information from the inertial measurement unit is converted into the navigation coordinate system.

[0038] Among them, the IMU coordinate axes x and y have an angle θ with the navigation coordinate axes E and N, and the acceleration a E and acceleration a N Characterized as:

[0039] a E =a y sinθ+a x cosθ;

[0040] a N =a y cosθ-a x sinθ;

[0041] The matrix form is as follows:

[0042]

[0043] The velocity is obtained by integrating the acceleration in the navigation coordinate system:

[0044]

[0045] And, by integration, the position of the target in the navigation coordinate system is obtained:

[0046]

[0047] In one aspect of the present invention, step S60 further includes the step of:

[0048] When the device leaves the fixed solution mode of RTK, the system adaptively adopts the following adjustment strategy:

[0049] The system automatically adjusts the warning distance threshold, expanding it by 1 meter to ensure that the alarm is triggered earlier and to prioritize keeping personnel outside the danger zone.

[0050] RTK and inertial navigation technologies are used to correct positioning accuracy.

[0051] The present invention also provides a dynamic positioning and recognition system for human interaction at oil and gas stations, which applies the above-mentioned dynamic positioning and recognition method for human interaction at oil and gas stations, comprising:

[0052] The data acquisition module is used to acquire observation data;

[0053] The data repair module is used to detect and repair cycle slips in the observed data and obtain recovered cycle slip data.

[0054] The data parsing module is used for real-time dynamic differential positioning technology based on high-precision carrier phase observations to calculate the coordinates of unknown positions with high accuracy.

[0055] The coordinate transformation module is used to acquire latitude and longitude data from the positioning terminal and convert it into station-centered polar coordinate data.

[0056] The positioning fusion module is used to perform fusion positioning based on inertial navigation RTK technology and obtain personnel location data when the positioning terminal signal is weak or cannot obtain positioning information.

[0057] The judgment and early warning module is used to make judgments on human-centered behavioral logic based on the device type and task scenario bound to the positioning terminal.

[0058] The present invention also provides an oil and gas station human interaction dynamic positioning and recognition device that applies the above-mentioned oil and gas station human interaction dynamic positioning and recognition method, characterized in that it includes:

[0059] An integrated mobile receiver that connects to personnel and equipment;

[0060] The integrated mobile receiver consists of an alarm module, a positioning module, a communication module, a battery module, and a switch control module.

[0061] In summary, this invention provides a method, system, and device for dynamic positioning and identification of personnel and objects in oil and gas stations. It enhances the adaptability of RTK to the environment, shortens the time to reach a fixed solution, solves the positioning problem under extremely poor or no signal conditions, and successfully achieves intelligent identification and alarm for distance-related construction violations such as earthmoving, hoisting, and hot work in oilfield scenarios. Furthermore, it develops a portable positioning terminal and an oilfield positioning monitoring and early warning system. This effectively addresses the problem of existing safety procedures struggling to accurately locate personnel and objects at close range and provide real-time early warnings. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0063] Figure 1 This is a flowchart illustrating an embodiment of the dynamic positioning method for human interaction at an oil and gas station according to the present invention.

[0064] Figure 2 This is a schematic diagram of the improved high-order difference method detection process in one embodiment of the dynamic positioning method for human interaction at oil and gas stations according to the present invention.

[0065] Figure 3 This is a schematic diagram illustrating the process of solving integer ambiguity values ​​using an adaptive differential evolution algorithm in one embodiment of the dynamic positioning method for human interaction at oil and gas stations according to the present invention.

[0066] Figure 4 This is a schematic diagram of the station-center polar coordinate system in one embodiment of the dynamic positioning method for human interaction at an oil and gas station according to the present invention.

[0067] Figure 5 This is a schematic diagram of strapdown inertial navigation two-dimensional trajectory recursion in one embodiment of the dynamic positioning method for human interaction at oil and gas stations according to the present invention.

[0068] Figure 6 This is a schematic diagram illustrating the conversion from the inertial coordinate system to the navigation coordinate system in one embodiment of the dynamic positioning method for human interaction at an oil and gas station according to the present invention.

[0069] Figure 7 This is a modeling process for colored noise in an inertial sensor in one embodiment of a dynamic positioning method for human interaction at an oil and gas station according to the present invention.

[0070] Figure 8 This is a random error processing flow in one embodiment of the dynamic positioning method for human interaction at oil and gas stations according to the present invention;

[0071] Figure 9 This is a behavior judgment logic diagram in one embodiment of the dynamic positioning method for human interaction at oil and gas stations according to the present invention;

[0072] Figure 10 This is a schematic diagram of a module in one embodiment of the dynamic positioning system for human interaction at an oil and gas station according to the present invention.

[0073] Figure 11 This is a framework diagram of information acquisition, analysis and feedback in one embodiment of the dynamic positioning device for human interaction at an oil and gas station according to the present invention.

[0074] Figure 12 This is a schematic diagram of a module in one embodiment of the interactive dynamic positioning device for oil and gas stations according to the present invention.

[0075] Figure Labels

[0076] 10. Data acquisition module; 20. Data repair module; 30. Data parsing module; 40. Coordinate transformation module; 50. Positioning fusion module; 60. Judgment and early warning module. Detailed Implementation

[0077] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0078] Please see Figures 1 to 12 It should be noted that the structures, proportions, sizes, etc., shown in the accompanying drawings are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0079] Please see Figure 1 This invention discloses a dynamic positioning method for personnel interaction at oil and gas stations, which can be used to accurately locate the distance of personnel during safe operations and provide real-time early warnings. Specifically, this invention is based on a high-precision RTK (Real-Time Kinematic) positioning method. Specifically, this dynamic positioning method for personnel interaction at oil and gas stations may include the following steps.

[0080] First, step S10 is executed to acquire observation data. In this technical solution, this observation data is acquired based on satellite data. However, when satellite positioning is deployed in the field, it is often subject to unpredictable environmental disturbances, including electromagnetic signal interference and obstruction by vegetation and buildings. Therefore, without changing the hardware, this method also requires cycle slip detection and repair within the positioning model for complex environments.

[0081] Then, step S20 is executed to detect and repair cycle slips in the observed data and obtain the recovered cycle slip data.

[0082] Please refer to Figure 2. Specifically, in the process of detecting cycle slips in the observed data, the higher-order difference method is used as an improved method for detecting discontinuous epochs. The steps include:

[0083] 1) Start counting interruptions at the epoch when the data is lost. Assume that the epoch is t1 and the epoch when it is recaptured is t2. Then the time of loss is Δt = t2 - t1.

[0084] 2) Set the sampling interval of the higher-order difference method to Δt to ensure equal-interval sampling.

[0085] 3) Interpolate the original data, interpolating carrier observations with a sampling interval of Δt to a sampling interval of 1 second.

[0086] By sparse the data, a high sampling rate is constructed to ensure observation accuracy.

[0087] The fourth difference detection was performed using the higher difference method.

[0088] Please see Figure 3 As shown, during the cycle slip recovery process of observation data, a new cycle slip recovery strategy can be adopted, including an assessment of the impact of recovered cycle slip data on ambiguity resolution (ARRatio). Ambiguity resolution is performed on the delayed observations, comparing the ambiguity resolution Ratio values ​​of the current epoch with those of the previous epoch. If the addition of a new satellite causes the resolved Ratio value to drop below a threshold, or to half the Ratio value of the previous epoch, then that satellite is disqualified from participating in the resolution, and a re-resolution is performed.

[0089] Then, step S30 is executed, using real-time dynamic differential positioning technology based on high-precision carrier phase observations to calculate the coordinates of the unknown position with higher accuracy.

[0090] In the RTK positioning process, algorithms are needed to solve the integer ambiguity problem in the model in order to calculate the unknown position coordinates with higher accuracy.

[0091] LAMBDA (Least Squares Ambiguity Decorrelation) is designed to solve the correlation of integer estimation error vectors. As the most effective ambiguity in-flight fixed algorithm, its performance is easily affected by factors such as satellite failure and multipath effect.

[0092] This method fixes the double-difference integer ambiguity in the LAMBDA algorithm and deletes the ambiguity with the largest variance value in the set of ambiguities to be fixed. By fixing part of the ambiguity in this iterative way, the method can fix as many carrier phase integer ambiguities as possible while ensuring the correctness of the fixation.

[0093] This improved RTK positioning algorithm can significantly increase the success rate of ambiguity fixation and improve the positioning accuracy and reliability of differential satellite navigation systems.

[0094] Please see Figure 4 As shown, this invention uses an adaptive differential evolution algorithm to solve for integer ambiguity values.

[0095] To address integer ambiguity, a downcorrelation process is performed on the ambiguity before fixing it, thereby increasing the algorithm's search efficiency. After this process, the fitness function distribution changes from a non-monotonic function to a monotonic function with only one extreme value, thus reducing the possibility of the algorithm getting trapped in local optima.

[0096] At the start of the search, due to the larger mutation and crossover operators, larger crossover operators and populations allow for a wider global search range, and larger mutation operators enrich population diversity. However, in the later stages of iteration, when the fitness of all individuals in the population is high, smaller crossover and mutation operators lead to faster convergence, and a smaller population size allows for faster iteration.

[0097] Based on this, it is permissible to set variants. More generally, it can be written in the following form:

[0098]

[0099] In the formula, i and r represent individuals in the population, and g is the number of iterations; A i,g It is a weighting factor for individuals;

[0100] Therefore, regarding weighting factor A i,g and F i,g The proposed adaptive improvement is as follows:

[0101]

[0102] F i,g =0.5*(1.5-P) i,g )

[0103] Where i = [1, 2, Popsize], Popsize is the population size, g is the iteration number, and n i P is the number of times the i-th individual has not been updated, and max is the maximum allowed number of times an individual has not been updated. i,g The value is:

[0104]

[0105] Where maxF(X) g ) represents the fitness function value of the optimal individual in the g-th generation. Through P i,g This allows for the assessment of population fitness.

[0106] For weighting factor F i,g The changes in the mutation settings allow the algorithm to quickly iterate and obtain better mutant individuals when the overall fitness of the population is poor. Conversely, when the fitness of the population is good, the differences between the mutant individuals and the original individuals can be reduced, thus enabling the algorithm to converge quickly.

[0107] When the algorithm completes its search, a ratio value is performed on the fixed solution at this point to determine whether the algorithm has gotten stuck in a local optimum. The ratio of the sum of squared residuals of the suboptimal and optimal solutions in the fixed solution is used as the test value and compared with a set threshold, which is usually set to 2 or 3. When the ratio value is greater than the threshold, the ambiguity fixed solution is determined to be correct.

[0108] Finally, this invention uses the R-Ratio method to verify the ambiguity resolution results. The R-Ratio test method uses the ratio of the quadratic residual form of the optimal solution to that of the second-best solution for verification, expressed as:

[0109]

[0110] In the formula, a sec a min These represent the suboptimal and optimal solutions to the ambiguity, respectively, with c being the threshold. Their ratio is set to a fixed empirical value, typically 2 or 3.

[0111] Furthermore, step S40 is executed to obtain the latitude and longitude data from the positioning terminal and convert it into station-centered polar coordinate data.

[0112] Specifically, it allows latitude and longitude data in the 2000 coordinate system to be measured through positioning terminals, while in the test field, it is necessary to calculate the azimuth, distance, and pitch angle of two known points based on their latitude and longitude.

[0113] Please see Figure 4 As shown, given two points Po and S in space, where A represents the azimuth from S to Po, R represents the Earth's radius, and EL represents elevation, calculating the azimuth, distance, and elevation angle of these two points from their latitude and longitude involves converting their coordinates from the 2000 coordinate system to a station-centered polar coordinate system with one of the points as the origin. This conversion requires three steps: first, converting the 2000 coordinate system to a spatial rectangular coordinate system; second, converting the spatial rectangular coordinate system to a station-centered rectangular coordinate system; and finally, converting the station-centered rectangular coordinate system to station-centered polar coordinates. After the conversion, the final distance calculation formula is:

[0114] d=R*acos(cos(lat1)*cos(lat2)*cos(lng1-lng2)+sin(lat1)*sin(lat2)).

[0115] Furthermore, in step S50, when the positioning terminal signal is weak or positioning information cannot be obtained, fusion positioning is performed based on inertial navigation RTK technology, and the location data of the personnel is obtained.

[0116] In step S50, a navigation parameter calculation method is used based on gyroscopes and accelerometers as sensing elements.

[0117] In extreme cases where the positioning terminal receives extremely poor satellite signals and cannot obtain positioning information, the inertial navigation module of the positioning terminal can be used for assisted positioning. An inertial navigation system is a navigation parameter calculation system that uses gyroscopes and accelerometers as sensing elements and applies a trajectory recursion algorithm to provide information such as position, velocity, and attitude.

[0118] Please see Figure 5 As shown, the target can be viewed as moving in a two-dimensional plane (x, y), requiring the target's starting point (x0, y0) and initial heading angle A0 to be known. By real-time detection of the target's travel distance and heading angle changes in both the x and y directions, the target's two-dimensional position can be calculated in real time.

[0119] The diagram illustrates a two-dimensional recursive trajectory calculation for strapdown inertial navigation, approximating curvilinear motion as linear motion. Black dots represent the target position, θ represents the angle between the target and the north direction, and cylinders represent the accelerometer and gyroscope, with the gyroscope's sensitive axis perpendicular to the paper and outwards. Before performing integration calculations similar to those in one-dimensional trajectory calculations, the output of the inertial measurement unit needs to be converted to the navigation coordinate system. The target's turn will cause the gyroscope to generate an angular velocity ω relative to the navigation coordinate system. Combining this with the initial heading angle A0, integrating the angular velocity measured by the gyroscope yields the heading angle A. t :

[0120] A t =∫ωd t +A0

[0121] The change in the target velocity will produce an acceleration 'a' in the IMU coordinate system. y However, the calculation requires the acceleration 'a' in the navigation coordinate system. N Using heading angle A t The measurement information from the inertial measurement unit (IMU) can be converted to the navigation coordinate system. The coordinate system transformation is shown below. The IMU coordinate axes x and y have an angle θ with the navigation coordinate axes E and N; therefore, the acceleration a... E and acceleration a N It can be written as:

[0122] a E =a y sinθ+a x cosθ

[0123] a N =a y cosθ-a x sinθ

[0124] The matrix form is:

[0125]

[0126] Once the acceleration in the navigation coordinate system is obtained, its velocity can be obtained by integration:

[0127]

[0128] Then, integrate the results to obtain the target's position in the navigation coordinate system:

[0129]

[0130] Please see Figure 6 , Figure 7 and Figure 8 As shown, since the error of the inertial sensor is one of the main error sources of the RTK and inertial navigation integrated navigation system, in order to improve the performance of the integrated navigation system, in one embodiment, the present invention can also allow compensation for random errors in the inertial sensor. The random error modeling method proposed in this invention has the following steps:

[0131] (1) Based on the identification of random errors, modeling is carried out on the basis of determining the random error components in the inertial sensor, and Allan variance analysis is used to identify the random errors in the inertial sensor.

[0132] (2) In order to facilitate its application in Kalman filtering of integrated navigation, white noise, quantization noise and colored noise will be separated during modeling.

[0133] (3) The above three types of random errors can be processed according to the following steps.

[0134] First, random error identification. This can be achieved through Allan variance analysis of inertial sensors.

[0135] Secondly, white noise processing. Determine if white noise exists; if so, obtain the power spectral density function of the white noise and the process noise covariance matrix of the system.

[0136] Furthermore, quantization noise processing is performed. The presence of quantization noise is determined; if present, the power spectral density function of the quantization noise is calculated, the inertial navigation error equation is modified, and the system's process noise covariance matrix Q is enhanced.

[0137] Finally, colored noise processing is performed. The presence of colored noise is determined. If it exists, the power spectral density function of the colored noise is generated, and a colored noise model is established. The Kalman filter of the enhanced system is used to compensate for the random drift of the inertial sensor caused by the colored noise.

[0138] Execute step S60, and make a human-centered behavioral logic judgment based on the device type and task scenario bound to the positioning terminal.

[0139] Please see Figure 9As shown, for various operational scenarios in oilfield operations, the judgment logic for distance violations is summarized as follows: the human-centered judgment logic is based on the device type and task scenario bound to the positioning terminal, and the judgment rules are adaptively applied.

[0140] For example, in one implementation, the overall determination principle may include:

[0141] For earthmoving operations, the principles include: two workers digging manually need to be more than 2 meters apart to prevent injury from tools; and when mechanical excavation is being carried out, personnel must not enter the rotation radius.

[0142] For hoisting operations, the principles include: no passing or staying under the hoisted load.

[0143] For hot work operations, the principles include: the distance between acetylene cylinders / oxygen cylinders and the ignition source must be greater than 10m, and the distance between two cylinders must be greater than 5m. Furthermore, flammable gases must not be emitted within 30m of the hot work point; flammable liquids must not be emitted within 15m; flammable solvent cleaning or painting operations must not be carried out simultaneously within 10m of the hot work point or below it; and flammable dust must not be swept within 10m.

[0144] It is important to note that while the positioning accuracy reaches its highest level (centimeter-level) when the equipment operates in RTK fixed solution mode, field operations cannot guarantee that the equipment will always be in an open area. For example, if operating near a ceiling, satellite signals may be blocked, causing the equipment to exit fixed solution mode and enter floating or single-point solution mode. In this case, the positioning accuracy decreases to the meter level. To ensure that the system's early warning remains reliable after the equipment exits RTK fixed solution mode, the system adaptively adopts the following adjustment strategy:

[0145] The system automatically adjusts the warning distance threshold, expanding it by 1 meter to ensure that the alarm is triggered earlier and to prioritize keeping personnel outside the danger zone.

[0146] RTK and inertial navigation technologies are used to correct positioning accuracy.

[0147] Please refer to Figure 10 In one embodiment, the present invention also provides a dynamic positioning and recognition system for personnel interaction at oil and gas stations. This system has monitoring and alarm functions, and can monitor the online status of positioning terminals. The terminal location is displayed in real-time on a map area with centimeter-level accuracy, and alarm information, type, and statistical information can also be displayed.

[0148] It is important to note that after personnel and equipment IDs are bound, the positioning method of this invention is used to obtain the personnel's behavioral trajectory in the work scenario. The analysis system combines the acquired information with specific behavioral judgment logic methods to analyze and integrate the returned results to determine whether any violations have occurred. If a violation has occurred, the analysis system pushes an alarm message to the recognition device, which will then emit an audible alert to remind on-site workers to stay away from the hazard. Throughout this process, the on-site work progress is not affected, yet real-time alerts are provided to workers in case of dangerous situations, ensuring easy and efficient use of the on-site recognition equipment.

[0149] Specifically, the dynamic positioning and recognition system for human interaction at the oil and gas station includes a data acquisition module 10, a data repair module 20, a data parsing module 30, a coordinate transformation module 40, a positioning fusion module 50, and a judgment and early warning module 60.

[0150] The system includes the following modules: Data Acquisition Module 10 acquires observation data; Data Repair Module 20 detects and repairs cycle slips in the observation data and acquires recovered cycle slip data; Data Parsing Module 30 uses real-time dynamic differential positioning technology based on high-precision carrier phase observations to calculate high-precision unknown location coordinates; Coordinate Transformation Module 40 acquires latitude and longitude data from the positioning terminal and converts it into station-centered polar coordinate data; Positioning Fusion Module 50 performs fusion positioning based on inertial navigation RTK technology and acquires personnel location data when the positioning terminal signal is weak or positioning information cannot be acquired; and Judgment and Early Warning Module 60 performs behavioral logic judgments centered on the human based on the device type and task scenario bound to the positioning terminal.

[0151] Please see Figure 11 and Figure 12 In one embodiment, the present invention also provides a dynamic positioning and identification device for personnel interaction at oil and gas stations. The device includes an integrated mobile receiver, which is available in two forms: a back clip and a magnetic attachment, for attaching to personnel and equipment, respectively.

[0152] The integrated mobile receiver consists of five modules: an alarm module, a positioning module, a communication module, a battery module, and a switch control module. This device allows for the acquisition of specific target location information, interconnection with alarm systems, and real-time alarms for on-site violations.

[0153] Specifically, the positioning module features low current, high sensitivity, high accuracy, and strong anti-interference capabilities. It supports simultaneous reception of GPS, BDS, Galileo, GLONASS, and QZSS satellite signals, thereby significantly reducing multipath effects in urban canyons and improving positioning accuracy.

[0154] The communication module uses a 4G communication module to realize information transmission with the Beidou positioning platform and alarm platform. The ultra-small LTE Cat1 wireless communication module supports a maximum downlink rate of 10Mbps and a maximum uplink rate of 5Mbps. It has the advantages of beautiful appearance, strong metallic texture, better heat dissipation, less susceptibility to data erasure, and better adaptability to automation needs.

[0155] The alarm module allows for the use of industrial-grade buzzer alarm modules, which emit a loud buzzing sound to alert personnel based on alarm commands issued by the system, achieving real-time alarm functionality. The battery module utilizes safe, high-capacity batteries, reducing the number of charging cycles and simplifying operation.

[0156] By integrating the functions of the above five major modules, a high-density, highly integrated violation identification device was designed to meet the needs of oilfield production operations.

[0157] In summary, this invention provides a method, system, and device for dynamic positioning and identification of personnel and objects in oil and gas stations. It enhances the adaptability of RTK to the environment, shortens the time to reach a fixed solution, and solves the positioning capability problem under extremely poor or no signal conditions. It successfully achieves intelligent identification and alarm for distance-related construction violations such as earthmoving, hoisting, and hot work in oilfield scenarios, and has developed a portable positioning terminal and an oilfield positioning monitoring and early warning system. Therefore, it effectively improves the problem of difficulty in accurately locating personnel and objects at distances and providing real-time early warnings in existing safe operation processes. Thus, this invention effectively overcomes some practical problems in existing technologies and has high utilization value and practical significance.

[0158] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A dynamic positioning method for human interaction at oil and gas stations, characterized in that, include: Step S10: Obtain observation data; Step S20: Detect and repair cycle slips in the observed data, and obtain recovered cycle slip data; Step S30: Based on the real-time dynamic differential positioning technology of high-precision carrier phase observations, the coordinates of the unknown position with higher accuracy are calculated. Step S40: Obtain latitude and longitude data from the positioning terminal and convert it into station-centered polar coordinate data; Step S50: When the positioning terminal signal is weak or positioning information cannot be obtained, fusion positioning is performed based on inertial navigation RTK technology, and the location data of the personnel is obtained. Step S60: Based on the device type and task scenario bound to the positioning terminal, perform behavioral logic judgment centered on the human.

2. The dynamic positioning method for human interaction at oil and gas stations according to claim 1, characterized in that, In step S20, the detection of cycle slips in the observed data includes: 1) Start an interruption count at the epoch when the data is lost. Assume that the epoch is t1 and the epoch when it is recaptured is t2. Then the time of loss is Δt = t2 - t1. 2) Set the sampling interval of the higher-order difference method to Δt to ensure equal-interval sampling; 3) Interpolate the original data, interpolating carrier observations with a sampling interval of Δt to a sampling interval of 1s to construct high sampling rate data; 4) The high-order difference method is used for fourth-order difference detection.

3. The dynamic positioning method for human interaction at oil and gas stations according to claim 1, characterized in that, In step S20, the repair of the observed data includes: Ambiguity resolution is performed on the delayed observations, and the ambiguity resolution ratio values ​​of the current epoch and the previous epoch are compared. If the addition of a new satellite causes the calculated Ratio value to drop below the threshold or to half of the Ratio value of the previous epoch, then the satellite will be disqualified from participating in the calculation and a recalculation will be performed.

4. The dynamic positioning method for human interaction at oil and gas stations according to claim 1, characterized in that, Step S30 includes: Based on the LAMBDA algorithm, and in this method, the double-difference integer ambiguity is fixed in the LAMBDA algorithm; Delete the fuzzyness with the largest variance value from the set of fuzzynesses to be fixed; The ambiguity is fixed by iterative loops, and as much carrier phase integer ambiguity as possible is fixed while ensuring the correctness of the fixation.

5. The dynamic positioning method for human interaction at oil and gas stations according to claim 4, characterized in that, The calculation of integer ambiguity values ​​is based on an adaptive differential evolution algorithm, which includes: Before fixing the ambiguity, the ambiguity is first reduced and the fitness function distribution is changed from a non-monotonic function to a monotonic function with only one extreme value. The algorithm search is executed, and when the algorithm search is completed, the Ratio value of the fixed solution at this time is checked to determine whether the algorithm has gotten stuck in a local optimum. The ratio of the sum of squared residuals of the suboptimal and optimal solutions in the fixed solution is used as the test value. It is compared with a set threshold, which is usually 2 or 3. When the ratio value is greater than the threshold, the fixed solution of ambiguity is determined to be correct.

6. The dynamic positioning method for human interaction at oil and gas stations according to claim 5, characterized in that, The Ratio value test includes the following steps: The test is performed using the ratio of the residual quadratic form of the optimal solution to that of the suboptimal solution, expressed as: In the formula, a sec a min These represent the suboptimal and optimal solutions to the ambiguity, respectively, with c being the threshold. The ratio of these two solutions is set to a fixed empirical value, typically 2 or 3.

7. The dynamic positioning method for human interaction at oil and gas stations according to claim 1, characterized in that, In step S50, when the positioning terminal signal is weak or positioning information cannot be obtained, the step of performing fusion positioning based on inertial navigation RTK technology and obtaining personnel position data includes a navigation parameter calculation method based on gyroscopes and accelerometers as sensing elements. This method includes: The heading angle A can be obtained by integrating the angular velocity measured by the gyroscope. t Including A t =∫ωd t +A0; The measurement information from the inertial measurement unit is converted into the navigation coordinate system, including: The change in target velocity generates acceleration a in the IMU coordinate system. y acceleration a in the navigation coordinate system N via heading angle A t The measurement information from the inertial measurement unit is converted into the navigation coordinate system. Among them, the IMU coordinate axes x and y have an angle θ with the navigation coordinate axes E and N, and the acceleration a E and acceleration a N Characterized as: a E =a y sinθ+a x cosθ; a N =a y cosθ-a x sinθ; The matrix form is: The velocity is obtained by integrating the acceleration in the navigation coordinate system: And, by integration, the position of the target in the navigation coordinate system is obtained:

8. The dynamic positioning method for human interaction at oil and gas stations according to claim 1, characterized in that, Step S60 also includes the step of: When the device leaves the fixed solution mode of RTK, the system adaptively adopts the following adjustment strategy: The system automatically adjusts the warning distance threshold, expanding it by 1 meter to ensure that the alarm is triggered earlier and to prioritize keeping personnel outside the danger zone. RTK and inertial navigation technologies are used to correct positioning accuracy.

9. A dynamic positioning and recognition system for human interaction at oil and gas stations, employing the dynamic positioning and recognition method for human interaction as described in any one of claims 1 to 8, characterized in that, include: The data acquisition module is used to acquire observation data; The data repair module is used to detect and repair cycle slips in the observed data and obtain recovered cycle slip data. The data parsing module is used for real-time dynamic differential positioning technology based on high-precision carrier phase observations to calculate the coordinates of unknown positions with high accuracy. The coordinate transformation module is used to acquire latitude and longitude data from the positioning terminal and convert it into station-centered polar coordinate data. The positioning fusion module is used to perform fusion positioning based on inertial navigation RTK technology and obtain personnel location data when the positioning terminal signal is weak or cannot obtain positioning information. The judgment and early warning module is used to make judgments on human-centered behavioral logic based on the device type and task scenario bound to the positioning terminal.

10. An oil and gas station human interaction dynamic positioning and recognition device applying the dynamic positioning and recognition method for human interaction as described in any one of claims 1 to 8, characterized in that, include: An integrated mobile receiver that connects to personnel and equipment; The integrated mobile receiver consists of an alarm module, a positioning module, a communication module, a battery module, and a switch control module.

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