Laser target inertial navigation radar full working surface straight line fusion method and electronic equipment

Abstract

This invention relates to the field of intelligent detection technology for fully mechanized coal mining faces, and discloses a method and electronic equipment for linear fusion of the entire working face based on laser target inertial navigation radar. The method includes the following steps: establishing a physical benchmark using a mechanical limiting device at the end of the working face and simultaneously collecting multi-dimensional data such as the coordinates of the connection point, radar point cloud, and inertial navigation attitude; calculating the rotational deviation using the relative tilt angle fitted by the radar point cloud and the absolute pitch angle of the inertial navigation, and combining real-time temperature correction translation parameters to unify the data in the end area to the absolute coordinate system of the inertial navigation; dividing the fusion area according to the distance from the connection point, and performing differentiated weighted fusion and smoothing processing on the converted data and the measured data of the inertial navigation; generating a complete curve for the entire working face using piecewise fitting and calculating the maximum straightness deviation. This invention solves the problem of coordinate alignment of multiple source sensors underground through a physical limiting and dynamic-static combined calibration mechanism, achieving high-precision full-area monitoring of the straightness of the scraper conveyor.

Description

Technical Field

[0001] This invention relates to the field of intelligent detection technology for fully mechanized coal mining faces, specifically to a linear fusion method and electronic equipment for the entire working face based on laser target inertial radar. Background Technology

[0002] Straightness control of the scraper conveyor in a fully mechanized mining face is a key aspect of achieving automated coal cutting and automatic face straightening. Currently, the industry typically uses an inertial navigation system installed in the middle of the mining machine, along with an odometer, to monitor the machine's trajectory and thus determine the shape of the scraper conveyor.

[0003] However, existing monitoring technologies still have limitations in the complex and enclosed environment of underground mines. Due to the lack of absolute external positioning signals such as GPS underground, it is difficult for multi-source sensor systems to establish a unified and high-precision spatiotemporal reference.

[0004] When attempting to introduce external observation equipment such as lidar to assist the inertial navigation system, the lack of a reliable physical correlation mechanism between the two leads to difficulties in spatial alignment between the radar relative coordinate system and the inertial navigation absolute coordinate system, making it difficult to guarantee the consistency of multidimensional data in time and space.

[0005] Meanwhile, the harsh environment of the fully mechanized mining face, the frequent operation of the hydraulic support and the cutting vibration of the coal mining machine will cause slight changes in the installation posture of the sensor, and the temperature fluctuations underground will also cause deformation of the installation structure.

[0006] Existing coordinate transformation methods are often based on static calibration parameters, ignoring the dynamic rotational deviations and environmental thermal effects during equipment operation. This idealized assumption about the installation posture can lead to systematic errors in coordinate transformation, reducing the reliability of monitoring data.

[0007] Furthermore, single sensors have performance bottlenecks in full-face monitoring. Although inertial navigation systems can continuously monitor the operating trajectory, they accumulate drift errors over time, especially in the reversing areas where the coal mining machine moves to both ends for reverse cutting, where the detection accuracy often fails to meet the requirements for precise end-to-end docking. While lidar has high ranging accuracy, it is affected by the field of view and dust, making it difficult to cover the entire working face.

[0008] Existing technical solutions often use simple data splicing methods when processing these two types of data, without fully considering the accuracy differences of sensors in different areas. This results in the generated straightness curves breaking or jumping at the data source switching points, making it impossible to form a continuous, smooth, and industrially compliant full-work surface morphology model. Summary of the Invention

[0009] To address the shortcomings of existing technologies, this invention provides a linear fusion method and electronic equipment based on laser target inertial radar across the entire working face. This solves the problems in existing technologies, such as the lack of a unified high-precision spatiotemporal physical benchmark for multi-source sensors downhole, the lack of an effective compensation mechanism for dynamic installation attitude deviations and environmental thermal effects, and the failure to achieve smooth and accurate fusion of sensor data with different accuracy characteristics across the entire working face.

[0010] To address the aforementioned problems, the first aspect of this invention provides a method for linear fusion across the entire working face based on laser target inertial radar. This method is executed by electronic equipment and aims to solve the problems of difficulty in unifying multi-source data and insufficient end-point detection accuracy in the straightness monitoring of the scraper conveyor in a fully mechanized mining face. The method mainly includes the following steps:

[0011] A physical reference is established using a mechanical limiting device at the end of the machine, and a synchronous acquisition command is triggered to obtain the coordinates of the junction point in the radar relative coordinate system, radar point cloud data, end area data, absolute coordinates of the inertial navigation system at the junction point, absolute pitch angle of the coal mining machine body, and real-time ambient temperature. This step establishes a unified spatiotemporal reference for multi-source sensor data fusion by physically limiting the inertial navigation system and the lidar in spatial position.

[0012] The rotational deviation is calculated using the relative tilt angle obtained by fitting the radar point cloud data and the absolute pitch angle.

[0013] The initial translation parameters are calculated based on the coordinates of the junction point in the radar relative coordinate system, the inertial navigation absolute coordinates at the junction point, and the rotational deviation. The corrected translation parameters are obtained by combining the real-time ambient temperature with the initial translation parameters.

[0014] The end region data is unified to the inertial navigation absolute coordinate system using the coordinate transformation formula, the rotation deviation, and the corrected translation parameters to obtain the transformed inertial navigation absolute coordinates.

[0015] This step utilizes the high-precision attitude data from the inertial navigation system to calibrate the radar's installation rotation error and introduces temperature compensation to correct translation errors caused by environmental factors, thus achieving accurate mapping of radar data to the inertial navigation coordinate system.

[0016] Based on the distance from the junction point, the entire working surface is divided into an end fusion zone, a transition fusion zone, and a central independent zone. Differential data fusion is performed on the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device to obtain fused coordinates. The fused coordinates form a fused discrete point series, and the fused discrete point series is smoothed using a curve smoothing formula.

[0017] This step uses a partitioned weighting strategy to correct inertial navigation drift in the terminal region using radar data, and ensures the continuity of the curve at the junctions of different regions through weight transition processing.

[0018] The smoothed fused discrete point series is modeled using a piecewise fitting formula to generate a complete curve for the entire working surface. The maximum straightness deviation is calculated using the straightness deviation formula and index synthesis formula, with the design straight line as the reference.

[0019] This step transforms discrete monitoring data into a continuous mathematical model, and, combined with the correction of inherent system errors, outputs quantitative indicators that reflect the true form of the scraper conveyor.

[0020] In one specific implementation, the process of establishing the physical reference and collecting data is as follows: after the coal mining machine touches the end mechanical limit device, it stops and remains stationary. The stationary state of the coal mining machine is used as the physical reference. At this time, the position of the inertial navigation device in the stationary state is stable, forming the connection point.

[0021] It then sends synchronous acquisition commands to the lidar, inertial navigation system, odometer, and temperature sensor; receives the coordinates of the junction point in the radar relative coordinate system after the lidar performs scanning and center of gravity extraction on the reflector; receives the radar point cloud data output by the lidar scanning the stationary coal mining machine body, as well as the end area data output by scanning the end shape of the scraper conveyor.

[0022] It receives the absolute coordinates of the inertial navigation system at the junction point and the absolute pitch angle of the coal mining machine body from the output of the inertial navigation system; it also receives the real-time ambient temperature collected by the temperature sensor.

[0023] In one specific implementation, the process of calculating the rotational deviation involves: performing linear fitting on the radar point cloud data to extract the relative tilt angle; and calculating the rotational deviation using the rotational deviation formula, where the rotational deviation is equal to the difference between the relative tilt angle and the absolute pitch angle. This method uses the absolute attitude angle measured by the inertial navigation system as a reference true value to reverse-calculate the installation tilt angle of the lidar.

[0024] In one specific implementation, the process of correcting the translation parameters is as follows: using the temperature correction formula, a temperature correction coefficient is calculated based on the difference between the real-time ambient temperature and the reference temperature constant; using the translation correction formula, the initial translation parameters are multiplied by the temperature correction coefficient to obtain the corrected translation parameters.

[0025] In one specific implementation, the process of unifying coordinate data is as follows: using the coordinate transformation formula, the original radar relative coordinates of the terminal area data are rotated according to the rotation deviation; the rotated data is translated according to the corrected translation parameters, and the terminal area data is unified to the inertial navigation absolute coordinate system to obtain the transformed inertial navigation absolute coordinates.

[0026] In one specific implementation, the data fusion process is as follows: when the coordinate point in the converted inertial navigation absolute coordinates is located in the end-of-line fusion area, the weighting coefficients of the radar data and the inertial navigation data are used, and the end-of-line fusion formula is used to perform weighted fusion of the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device to obtain the fused coordinates.

[0027] The weighting coefficients of the radar data and the inertial navigation data are fixed values, and the weighting coefficient of the radar data is greater than that of the inertial navigation data. These fixed values ​​are preset based on the radar's superior ranging accuracy in the terminal area.

[0028] In one specific implementation, the data fusion process further includes: when the coordinate point in the converted inertial navigation absolute coordinates is located in the transition fusion zone, dynamically calculating the weighting coefficients of the radar data and the inertial navigation data using the transition weighting formula; and using the end-point fusion formula and the dynamically calculated weighting coefficients, performing weighted fusion of the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device to obtain the fused coordinates.

[0029] In the transition weight formula, the weight coefficient of the radar data decreases linearly as the distance between the current coordinate point and the junction point increases.

[0030] In one specific implementation, the smoothing process is as follows: for any target data point in the fused discrete point list, the smoothed ordinate of the target data point is calculated using the curve smoothing formula. The smoothed ordinate is equal to the arithmetic mean of the original ordinates of the target data point and its adjacent nodes in the neighborhood, thereby obtaining the smoothed fused discrete point list.

[0031] In one specific implementation, the process of generating curves and calculating deviations is as follows: for the data of the end fusion area and the transition fusion area, a quadratic polynomial is used for fitting; for the data of the middle independent area, a cubic polynomial is used for fitting; and piecewise equations are spliced ​​together to obtain the complete curve of the entire working surface.

[0032] The vertical distance of each sampling point relative to the designed straight line is calculated using the straightness deviation formula, and the maximum vertical distance is extracted. The root mean square error of the maximum vertical distance is then corrected using the index synthesis formula to obtain the maximum straightness deviation.

[0033] A second aspect of the present invention provides an electronic device, including a processor, a communication interface, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the linear fusion method based on the full working surface of laser target inertial navigation radar as described in the first aspect above.

[0034] This invention provides a method and electronic device for linear fusion across the entire working plane of laser-target inertial navigation radar. It offers the following advantages:

[0035] 1. This invention establishes a physical reference by utilizing the static state of the coal mining machine after it touches the mechanical limit device at the end, and associates the absolute position of the inertial navigation system with the relative observation coordinates of the lidar through a connection point. This method provides a unified external spatial reference for underground multi-source sensors, ensuring the consistency of the spatial reference between the lidar and the inertial navigation system during data fusion, and solving the technical problem of high-precision alignment of heterogeneous sensor coordinate systems.

[0036] 2. This invention can calculate and compensate for the rotational deviation of the lidar installation position by comparing the relative tilt angle fitted by the radar point cloud with the absolute pitch angle output by the inertial navigation system. At the same time, it can correct the structural translation error caused by changes in ambient temperature by combining temperature data. This scheme calibrates the rotational parameters while calibrating the translation parameters, reduces the coordinate transformation deviation caused by changes in the attitude of the hydraulic support or installation errors, and improves the accuracy of radar data in the inertial navigation coordinate system.

[0037] 3. This invention employs a segmented differentiated fusion strategy, using lidar ranging data to correct the cumulative error of inertial navigation in the end region, using a dynamic weighting algorithm to achieve smooth switching of data sources in the transition region, and using inertial navigation trajectory to maintain monitoring continuity in the middle region. By combining the performance advantages of different sensors, it avoids the performance limitations of a single sensor in a specific region, thereby generating a full working surface straightness curve that combines end accuracy and overall continuity. Attached Figure Description

[0038] Figure 1 This is a flowchart of the laser target inertial radar full-plane linear fusion method based on the present invention;

[0039] Figure 2 This is a flowchart of the junction point positioning and multi-dimensional data synchronous acquisition process of the present invention;

[0040] Figure 3 This is a flowchart of the pose calibration and coordinate transformation based on dynamic and static combination of the present invention;

[0041] Figure 4 This is a block diagram of the linear fusion electronic device and external sensing components based on the full working surface of laser target inertial radar according to the present invention. Detailed Implementation

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see the appendix Figure 1 This invention provides a linear fusion method based on the entire working plane of a laser target inertial navigation radar. This method is executed by electronic devices in coordination with the laser radar, inertial navigation device, odometer, and temperature sensor, and includes the following steps:

[0044] Step S1: Junction point positioning and multi-dimensional data synchronous acquisition. First, the physical benchmark is established using the end mechanical limit device. After the coal mining machine touches the limit, it stops and remains stationary to ensure that the position of the inertial navigation device converges and forms a junction point.

[0045] In this stable state, the electronic equipment triggers a synchronous acquisition command to obtain the coordinates of the junction point in the radar relative coordinate system, radar point cloud data, the inertial navigation absolute coordinates at the junction point, the absolute pitch angle of the coal mining machine body, and the real-time ambient temperature at the site.

[0046] Step S2: Pose calibration and coordinate transformation based on a combination of static and dynamic methods. Using the relative tilt angle obtained by fitting radar point cloud data and the absolute pitch angle provided by the inertial navigation system, the error in the lidar's installation attitude is calculated. The specific calculation is based on the rotation deviation formula:

[0047] ;

[0048] In the formula: This is rotational deviation; The relative tilt angle; This is the absolute pitch angle.

[0049] After determining the rotation parameters, the initial translation parameters are solved by using the radar relative coordinates and inertial navigation absolute coordinates at the junction point. Real-time ambient temperature is then introduced, and the temperature correction coefficient is calculated using the temperature correction formula.

[0050] ;

[0051] In the formula: This is a temperature correction factor; Real-time ambient temperature; The reference temperature constant; This is the preset thermal expansion influence factor.

[0052] Based on the calculated temperature correction coefficient, the initial translation parameters are compensated using the translation correction formula to obtain the corrected translation parameters:

[0053] ;

[0054] ;

[0055] In the formula: , These are the corrected translation parameters; , These are the initial translation parameters; This is the temperature correction factor.

[0056] Combining the rotational deviation calculated above with the corrected translation parameters, the coordinate transformation formula is used to batch unify the end-area data acquired by the lidar to the inertial navigation absolute coordinate system:

[0057] ;

[0058] ;

[0059] In the formula: , For inertial navigation absolute coordinates; , Relative coordinates for radar; This is rotational deviation; , These are the corrected translation parameters.

[0060] Step S3: Hyperbolic segmented fusion based on the junction point. The entire working surface is divided into an end fusion zone, a transition fusion zone, and a central independent zone according to the distance from the junction point, and differentiated processing is performed for each zone.

[0061] In the front-end fusion region, the converted radar data and inertial navigation measured data are weighted and calculated using the front-end fusion formula:

[0062] ;

[0063] ;

[0064] In the formula: , For fused coordinates; These are the weighting coefficients for radar data; , For inertial navigation absolute coordinates; These are the weighting coefficients for the inertial navigation data; , These are the absolute coordinates of the inertial navigation system (measured data from the inertial navigation system).

[0065] In the transition fusion zone, the weight allocation between radar and inertial navigation is dynamically calculated using a transition weight formula to achieve smooth data integration.

[0066] ;

[0067] ;

[0068] In the formula: These are the weighting coefficients for radar data; This represents the distance from the current data point to the junction point. These are the weighting coefficients for inertial navigation data.

[0069] After fusion, the discrete point sequence of the entire working surface is processed using a curve smoothing formula to eliminate high-frequency noise:

[0070] ;

[0071] In the formula: For the first The ordinate of each point after smoothing; This represents the original ordinate within the neighborhood.

[0072] Step S4: Generation and Output of the Full Working Surface Curve. A piecewise fitting formula is used to mathematically model the smoothed data, generating a complete curve for the entire working surface. The end and transition zones use a quadratic polynomial, while the independent central zone uses a cubic polynomial.

[0073] End and transition area:

[0074] ;

[0075] Central Independent District:

[0076] ;

[0077] In the formula: , The ordinate and abscissa of the fitted curve; The fitting coefficients of the quadratic polynomial; The fitting coefficients are those of a cubic polynomial.

[0078] Then, using the straight line of the design as a reference, the vertical distance of each sampling point relative to the reference is calculated using the straightness deviation formula:

[0079] ;

[0080] In the formula: Vertical distance; These are the ordinates and abscissas of the sampling points; To design the slope leading to a straight line; The offset value is used to design a straight line.

[0081] Finally, the maximum vertical distance is corrected using the index synthesis formula, and the final maximum straightness deviation is output:

[0082] ;

[0083] In the formula: This represents the maximum deviation in straightness. The maximum vertical distance among all sampling points; This is the system error correction term.

[0084] See appendix Figure 2 During step S1, the electronic equipment, in conjunction with the lidar, inertial navigation system, and odometer, performs specific physical reference establishment and data acquisition operations. This process includes the following sub-steps:

[0085] Step S101: Establish a physical reference using the end mechanical limit device. During the longwall mining process, the coal mining machine moves towards the end of the working face. The control system controls the coal mining machine to approach the end at a preset low speed (e.g., below 0.5 m / s). When the coal mining machine touches the end mechanical limit device, the rigid physical constraint characteristics of the limit device force the coal mining machine to stop moving.

[0086] As a type of physical hard limit, the end mechanical limit device maintains a relatively fixed or predictable position during the face advancement process, providing a unified spatial reference for multi-source sensors. After the coal mining machine triggers the limit stop, it remains stationary for 3 to 5 seconds.

[0087] This stationary operation aims to eliminate residual vibrations in the coal mining machine's traveling section and hydraulic system, bringing the physical position fluctuations of the inertial navigation device installed in the middle of the coal mining machine to within ±5mm.

[0088] At this point, the geometric center of the inertial navigation system is defined as the junction point, which serves as the only physical common point connecting the radar relative coordinate system and the inertial navigation absolute coordinate system.

[0089] Step S102: Execute time synchronization triggering for multiple sensors. After confirming that the coal mining machine is in a static and stable state, the data processing unit of the electronic equipment generates a synchronization acquisition command. This command is simultaneously sent to the lidar, inertial navigation device, odometer, and temperature sensor via hardwired connection or real-time industrial Ethernet.

[0090] The electronic device uses a unified clock source to timestamp the data streams from the aforementioned sensors, ensuring that the time deviation of the data collected by each sensor is controlled within 10ms, thereby guaranteeing the temporal consistency of subsequent spatial data fusion.

[0091] Step S103: Acquire multi-dimensional observation data of the junction point and environment. The lidar responds to the synchronization command and performs continuous scanning of the reflector (laser target) located on the side surface of the scraper machine's goaf area. The lidar operates at a scanning frequency of 10Hz, continuously acquiring 20 frames of point cloud data. The electronic equipment receives the scan data. For center positioning of the reflector, it first sets a reflection intensity threshold based on the reflector's high reflectivity characteristics, filters out background point clouds with reflection intensities below this threshold, and retains high-intensity point cloud clusters.

[0092] Subsequently, a centroid extraction algorithm was used to calculate the geometric center of each frame's point cloud cluster.

[0093] To eliminate interference from environmental dust or random noise, the electronic equipment calculates the mean of the center coordinates of 20 frames and removes abnormal frames that deviate from the mean by more than ±2 cm. The mean of the remaining valid frames is then used as the coordinates of the point in the radar relative coordinate system. .

[0094] Simultaneously, the lidar scans the stationary coal mining machine, acquiring radar point cloud data containing the machine's outline features. This point cloud data reflects the spatial attitude of the coal mining machine from the radar coordinate system perspective, and is used for extracting the relative tilt angle in subsequent steps.

[0095] The inertial navigation system works in conjunction with the odometer to output the absolute inertial coordinates of the middle of the coal mining machine (i.e., the junction point) based on the global coordinate system established at the initial moment of the working face mining. Simultaneously, the attitude calculation unit inside the inertial navigation system outputs the current absolute pitch angle of the coal mining machine. .

[0096] The temperature sensor collects the real-time ambient temperature around the lidar. This temperature data is used to compensate for the minor deformations caused by thermal expansion and contraction at the radar installation location.

[0097] Step S104: Data Validation and Storage. The electronic device performs logical verification on the collected data. This is based on the radar relative coordinates. Determine whether the value falls within the preset range of the scraper conveyor end area (e.g., 0.5m to 2.0m on the X-axis and 0.2m to 0.8m on the Y-axis).

[0098] For inertial navigation absolute coordinates The system checks whether the coordinates match the design coordinate range of the working face end. Only when all coordinate data passes verification and the attitude and temperature data are complete will the electronic device store the aforementioned data package in local memory as the raw input data for subsequent pose calibration and curve fusion. If the verification fails, the electronic device will trigger an alarm and prompt the user to re-execute the acquisition process.

[0099] See appendix Figure 3 Step S2 aims to eliminate attitude errors during lidar installation and structural deformation errors caused by environmental temperature changes, accurately mapping the relative coordinate data acquired by the lidar to the inertial navigation absolute coordinate system. The electronic device performing this step specifically includes the following sub-steps:

[0100] Step S201: Calculate the rotational deviation of the lidar. The electronic device retrieves the radar point cloud data obtained in step S1 and the absolute pitch angle of the coal mining machine body. For the radar point cloud data, the electronic device sets a three-dimensional region of interest (ROI) based on the preset spatial range when the coal mining machine stops at the end. Within this region, a point cloud segmentation algorithm is used to extract the surface contour point set of the coal mining machine body, and the least squares linear fitting is performed on this point set to calculate the relative tilt angle of the coal mining machine body in the radar relative coordinate system. .

[0101] This relative tilt angle reflects the attitude of the coal mining machine within the radar field of view. Since the inertial navigation system is installed inside the coal mining machine's fuselage, its output absolute pitch angle... This represents the actual physical posture of the coal mining machine relative to the horizontal plane.

[0102] The electronic device compares the relative tilt angle with the absolute pitch angle; the difference between the two represents the rotational deviation of the lidar's installation position relative to the absolute horizontal plane. This calculation is performed based on the rotational deviation formula:

[0103] ;

[0104] In the formula: The rotational deviation represents the rotation angle of the radar coordinate system relative to the inertial navigation coordinate system. The relative tilt angle is obtained by fitting radar point cloud data. It is the absolute pitch angle, measured by the inertial navigation system.

[0105] Step S202: Calculate the temperature correction factor and the corrected translation parameters. After determining the rotational deviation, the electronic equipment uses the coordinates of the junction point P in the radar relative coordinate system. Coordinates in the absolute coordinate system of the inertial navigation system Calculate the initial translation parameters.

[0106] Specifically, the radar relative coordinates are first determined based on the rotational deviation. Perform a rotation transformation, then calculate the difference between the transformed coordinates and the inertial navigation system's absolute coordinates to obtain the initial translation parameters. and .

[0107] Considering that changes in downhole ambient temperature can cause slight thermal expansion and contraction deformation of the lidar mounting bracket, thus affecting the accuracy of the translation parameters, the electronic equipment incorporates real-time ambient temperature data to compensate for the translation parameters. The electronic equipment calculates the temperature correction coefficient based on the temperature correction formula:

[0108] ;

[0109] In the formula: This is a temperature correction factor; The real-time ambient temperature is collected by a temperature sensor; The reference temperature constant; This is the preset thermal expansion influence factor.

[0110] Based on the calculated temperature correction coefficient, the electronic device uses a translation correction formula to linearly correct the initial translation parameters to obtain the final corrected translation parameters used for coordinate transformation:

[0111] ;

[0112] ;

[0113] In the formula: , These are the corrected X-axis and Y-axis translation parameters; , These are the initial translation parameters for the X and Y axes; This is the temperature correction factor.

[0114] Step S203: Perform batch coordinate transformation. The electronic device reads the end area data acquired by the lidar scan, which contains a large number of discrete coordinate points of the scraper conveyor end area in the radar relative coordinate system. Using the rotational deviation and corrected translation parameters calculated in the previous steps, the electronic device constructs a unified rigid body transformation model.

[0115] For any coordinate point in the end area data The coordinates are then unified to the inertial navigation absolute coordinate system using the coordinate transformation formula:

[0116] ;

[0117] ;

[0118] In the formula: , These are the converted absolute coordinates of the inertial navigation system. , Relative coordinates for radar; This is rotational deviation; , These are the corrected translation parameters.

[0119] After completing the batch conversion, the electronic device can further select fixed components with obvious features at the end area of ​​the scraper machine (such as end bolts) as verification points, compare their converted coordinates with the known absolute coordinates, and if the deviation is within the preset threshold (such as 4mm), the coordinate conversion model is determined to be effective and enters the subsequent data fusion process.

[0120] Step S3 primarily addresses the spatial fusion problem of multi-source heterogeneous data. The electronic device executes a segmented fusion strategy based on the accuracy characteristics of each data source in different regions. This step specifically includes the following sub-steps:

[0121] Step S301: Divide the entire working surface fusion region. The electronic device uses the inertial navigation absolute coordinates of the fusion point P determined in step S1. Establish a local measurement standard along the working surface inclination (i.e., the X-axis direction) with the origin as the origin.

[0122] Based on their distance from the junction point, the data points on the goaf side of the full-face scraper machine are divided into three regions with different processing logics:

[0123] End-to-end fusion zone: defined as the area within 0.5 meters of the junction point P along the X-axis. Within this area, lidar, due to its proximity to the reflector, offers the highest ranging accuracy and thus dominates the data fusion process.

[0124] Transition and fusion zone: defined as the area between 0.5 meters and 3 meters from the absolute coordinate X-axis of the junction point P, i.e. Within this region, as distance increases, the density of radar point clouds decreases, necessitating a gradual increase in the weight of inertial navigation data to achieve a smooth transition from the tip to the middle.

[0125] Central Independent Zone: Defined as the area more than 3 meters away from the junction point P in the X-axis direction, i.e. In this region, the line-of-sight of lidar is limited or its accuracy is reduced, and the system mainly relies on trajectory data from inertial navigation and odometers.

[0126] Step S302: Perform high-precision weighted calculation of the end-head fusion area. For each data point falling within the end-head fusion area, the electronic device extracts the radar coordinates (radar data in the inertial navigation absolute coordinate system) corresponding to that point after transformation in step S2 and the absolute coordinates measured by the inertial navigation device.

[0127] Given that the radar accuracy in this area is better than the cumulative error of inertial navigation, a weighting coefficient is set for the radar data. The weighting coefficient for inertial navigation data is 0.7. The value is 0.3. The merged coordinates are calculated using the end-merge formula:

[0128] ;

[0129] ;

[0130] In the formula: , These are the merged coordinates, i.e., the final position coordinates after fusion processing; This is the weighting coefficient for radar data, and it is set to a fixed value of 0.7 in this region. , The inertial navigation absolute coordinates (referring to the radar data after coordinate transformation in step S2); The weighting coefficient for the inertial navigation data is set to a fixed value of 0.3 in this region. , These are the absolute coordinates of the inertial navigation system (referring to the measured data directly measured by the inertial navigation device).

[0131] Step S303: Perform dynamic weighting calculation for the transition blending zone. For data points falling into the transition blending zone, the electronic device calculates the Euclidean distance or X-axis projection distance from that point to the junction point P. (satisfy ).

[0132] To avoid curve breaks or abrupt changes at region boundaries, electronic devices use linear interpolation to dynamically adjust weights. This adjustment is applied as distance increases. As the transition weight increases, the radar weight decreases linearly, while the inertial navigation weight increases linearly. This calculation process utilizes the transition weight formula:

[0133] ;

[0134] ;

[0135] In the formula: These are the weighting coefficients for radar data, which vary with distance. This represents the initial maximum weight value of the radar in the tip region; This represents the distance from the current data point to the junction point P. This represents the furthest boundary of the transition and integration zone. The length range of the transition and fusion zone; These are the weighting coefficients for inertial navigation data.

[0136] Substituting the calculated dynamic weights into the above weighted fusion formula, we obtain the fusion coordinates of the transition region.

[0137] Step S304: Perform full curve smoothing. After completing the fusion calculation of the end and transition areas, and combining the inertial navigation data of the central independent area to form a discrete point sequence of the entire working surface, the electronic equipment performs noise reduction processing on the sequence.

[0138] Because multi-source data splicing and sensor noise may cause slight fluctuations in local curves, the electronic device uses a 5-point moving average method to smooth all coordinate points. For the first... For each point, calculate its smoothed ordinate using the curve smoothing formula:

[0139] ;

[0140] In the formula: For the first The ordinate of each point after smoothing; For the first The original ordinates of each point (after fusion or original values ​​from inertial navigation); For the first The ordinates of the two points preceding the given point; For the first The ordinates of the two points after the given point; This is the size of the sliding window.

[0141] For regions with fewer than 5 points at the edge of the sequence, the electronic device uses a 3-point averaging method for downgrading to ensure the smoothness and continuity of the entire curve.

[0142] Step S4 aims to transform the smoothed discrete coordinate points into a continuous mathematical model that can describe the overall shape of the scraper conveyor, and to calculate the straightness index that meets industry standards. The electronic equipment performing this step specifically includes the following sub-steps:

[0143] Step S401: Construct a segmented fitting model for the entire working surface. The electronic device sorts all the coordinate points after smoothing in step S3 according to the working surface orientation (X-axis).

[0144] Given that the scraper conveyor often exhibits a relatively simple bending shape in the end area due to the influence of the pushing jack and the end support, while in the middle area it often exhibits a complex S-shaped bending due to the influence of the coal mining machine cutting reaction force and geological conditions, the electronic equipment adopts a piecewise polynomial fitting method to establish the curve equation.

[0145] For data points falling into the end fusion zone and transition fusion zone, the electronic device uses a quadratic polynomial model for fitting to accurately characterize the bending trend of the end:

[0146] ;

[0147] For data points falling into the central independent region, the electronic device uses a cubic polynomial model for fitting to accommodate potential higher-order fluctuations in the central region:

[0148] ;

[0149] In the formula: , The ordinates and abscissas of the corresponding positions on the fitted curve; The fitting coefficients of the quadratic polynomial are obtained by regression of the data in this region using the least squares method. The coefficients are the fitting coefficients of a cubic polynomial, obtained by regression analysis of the data in this region using the least squares method.

[0150] The electronic equipment splices the above piecewise fitting equations in space to form a complete curve equation describing the morphology of the goaf side of the scraper machine in the entire working face.

[0151] Step S402: Calculate the straightness deviation at each sampling point. The electronic equipment retrieves the design straightness parameters of the scraper conveyor during installation. This design straightness is the theoretical benchmark for measuring whether the scraper conveyor is straight.

[0152] The electronic device selects several sampling points along the X-axis at preset step sizes (e.g., 0.5 meters), and for each sampling point... Calculate its perpendicular distance relative to the designed straight line. This calculation is performed using the straightness deviation formula:

[0153] ;

[0154] In the formula: For the first The vertical distance of each sampling point relative to the design reference line; For the first The ordinate of each sampling point (derived from the fitted curve or smoothed data); For the first The x-coordinate of each sampling point; To design the slope leading to a straight line; The offset (intercept) is used to design the direction of the straight line.

[0155] Step S403: Calculate the final maximum straightness deviation index. The electronic device iterates through all vertical distances calculated in step S402. Extract the maximum value. Considering the inherent measurement noise and system errors in lidar and inertial navigation systems (e.g., radar ranging error is approximately ±10mm), to prevent a single maximum value from being overestimated or underestimated due to system errors, the electronic equipment introduces a root mean square error synthesis method to correct the maximum deviation. The final maximum straightness deviation is calculated using the index synthesis formula:

[0156] ;

[0157] In the formula: The maximum deviation of the straightness of the entire working face after correction is output to the fully mechanized mining control console as the final monitoring result. Vertical distance of all sampling points The maximum value in; This is the system error correction term, representing the inherent error threshold of the system set based on the sensor hardware characteristics.

[0158] See appendix Figure 4 The present invention also provides a linear fusion electronic device based on the full working surface of laser target inertial radar. This electronic device serves as the core of data processing and control and includes a memory, a processor, and a communication interface at the physical level.

[0159] The memory is used to store computer programs and intermediate data generated during the execution of the above methods, including but not limited to radar point cloud data, rotational deviation parameters, corrected translation parameters, and fitted curve equations.

[0160] The processor and memory are connected via a communication bus to execute the computer program in the memory, thereby implementing the various steps of the full-working-surface linear fusion method in the aforementioned embodiments.

[0161] This electronic device establishes a signal connection with external sensing components via a communication interface, thereby forming a complete straightness monitoring system. The physical deployment and spatial relationship of the external sensing components are the fundamental hardware conditions for realizing the method of this invention.

[0162] Specifically, the lidar is fixedly installed on a hydraulic support at the end of the working face, with its installation height set between 1.2 meters and 1.5 meters above the upper surface of the scraper conveyor. The lidar's scanning direction is directly facing the goaf side of the scraper conveyor, and its field of view is configured to cover the scraper conveyor end area, the laser target (reflector), and the coal mining machine body running to the end.

[0163] This installation method ensures that the lidar can both capture the junction point used for positioning and scan the outline of the coal mining machine to extract the relative tilt angle.

[0164] The inertial navigation system is fixedly installed at the geometric center of the coal mining machine body to measure the three-axis attitude and absolute position information of the coal mining machine in real time.

[0165] The odometer is mounted on the traveling section of the coal mining machine and works in conjunction with the inertial navigation system to provide high-precision displacement data.

[0166] Temperature sensors are deployed near the lidar to monitor temperature changes in the environment in real time.

[0167] As a key physical reference for the system, a highly reflective laser target (reflector) is affixed to the side surface of the scraper conveyor's goaf area. The affixing position of the laser target is precisely calibrated to ensure that when the coal mining machine touches the end mechanical limit device and stops moving, the inertial navigation device in the middle of the coal mining machine is directly aligned with the laser target in spatial physical position.

[0168] This physical spatial alignment forms a unique point of connection, providing an absolute physical basis for electronic devices to associate multiple source coordinate systems.

[0169] At the logical functional level, the processor of an electronic device is configured to run multiple functional modules.

[0170] The data acquisition module is used to send synchronization trigger signals to the lidar, inertial navigation system, odometer and temperature sensor through the communication interface, and to receive the coordinates of the docking point, radar point cloud, absolute pitch angle and temperature data.

[0171] The pose calibration module is used to calculate the rotational deviation based on the difference between the relative tilt angle fitted by the radar point cloud and the absolute pitch angle output by the inertial navigation device, and to correct the translation parameters by combining temperature data, thereby unifying the terminal data collected by the radar to the inertial navigation absolute coordinate system.

[0172] The data fusion module is used to divide the working face data into the end fusion area, the transition fusion area and the middle independent area according to the distance of the data points from the junction point, and performs weighted fusion, dynamic weighted transition and trajectory stitching operations respectively.

[0173] The index output module is used to smooth the fused data and perform piecewise polynomial fitting to generate the full working surface curve equation, and calculate and output the maximum straightness deviation index based on the design straight line.

[0174] These functional modules work together to automate the process from the acquisition of multi-source raw data to the final output of industrial indicators.

[0175] The laser target inertial radar-based full-face straight line fusion method and electronic equipment provided in this invention achieve full-domain accurate monitoring of the straightness of the scraper machine in the fully mechanized mining face through the collaborative work of the hardware system and the optimization of the data processing strategy.

[0176] This technical solution utilizes the physical characteristics of the mechanical limit device at the contact end of the coal mining machine to establish an absolute physical reference between the inertial navigation device and the lidar, effectively solving the technical problem of establishing a unified coordinate system for multiple source sensors in an underground environment without GPS.

[0177] Unlike traditional single-sensor monitoring or simple data overlay, this invention introduces a dynamic and static combined attitude calibration mechanism. Based on the translation parameters calibrated at a static reference point, the relative tilt angle of the fuselage scanned by the radar and the absolute pitch angle output by the inertial navigation system are dynamically compared to calculate and compensate for the rotational deviation of the radar installation position in real time.

[0178] This mechanism improves the accuracy of coordinate transformation and overcomes deviations in monitoring data caused by hydraulic support vibration or installation errors. Meanwhile, the ambient temperature correction strategy further enhances the system's adaptability and stability in complex downhole thermal environments.

[0179] At the data fusion level, the segmented fusion strategy fully leverages the performance advantages of different sensors. In the early-stage region, the high-precision ranging characteristics of lidar are used to correct the cumulative drift of the inertial navigation system (INS). In the transition region, a dynamic weighting algorithm eliminates the numerical jumps that may occur when switching data sources. In the middle region, the INS' ability to continuously monitor long-distance trajectories is preserved.

[0180] This regional and differentiated processing method ensures that the generated straightness curve of the entire working face remains continuous and smooth overall, while also possessing the detection accuracy required by industry in key local areas (such as both ends), providing reliable data support for the automated correction of the fully mechanized mining face and the planning and cutting of the coal mining machine.

Claims

1. A method for linear fusion across the entire working plane of laser target inertial navigation radar, characterized in that, Includes the following steps: S1. Establish physical reference and trigger synchronous acquisition command to obtain the coordinates of the junction point in the radar relative coordinate system, radar point cloud data, end area data, inertial navigation absolute coordinates at the junction point, absolute pitch angle of the coal mining machine body, and real-time ambient temperature. S2. Calculate the rotation deviation using the relative tilt angle and absolute pitch angle obtained by fitting the radar point cloud data; calculate the initial translation parameters based on the coordinates of the junction point in the radar relative coordinate system, the inertial navigation absolute coordinates at the junction point, and the rotation deviation; correct the initial translation parameters using the real-time ambient temperature to obtain the corrected translation parameters; unify the end area data to the inertial navigation absolute coordinate system using the coordinate transformation formula, the rotation deviation, and the corrected translation parameters to obtain the transformed inertial navigation absolute coordinates. S3. Based on the distance from the junction point, the entire working surface is divided into an end fusion zone, a transition fusion zone, and a middle independent zone. Differential data fusion is performed on the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device to obtain fused coordinates. The fused coordinates form a fused discrete point series, and the fused discrete point series is smoothed using a curve smoothing formula. S4. The smoothed fused discrete point series is modeled using the piecewise fitting formula to generate a complete curve for the entire working surface. The maximum straightness deviation is calculated using the straightness deviation formula and index synthesis formula, with the design straight line as the reference.

2. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 1, characterized in that, The S1 step specifically includes: After the coal mining machine touches the mechanical limit device at the end, it stops and remains stationary. The stationary state of the coal mining machine is used as the physical reference, and the position of the inertial navigation device in the stationary state is stabilized to form the connection point. Send synchronous acquisition commands to lidar, inertial navigation system, odometer and temperature sensor; The coordinates of the junction point in the radar relative coordinate system are output by the laser radar after scanning and extracting the centroid of the reflector; The system receives radar point cloud data output by the lidar scanning the stationary coal mining machine body, and end area data output by scanning the end shape of the scraper conveyor. The inertial navigation system outputs the absolute coordinates of the junction point and the absolute pitch angle of the coal mining machine body. Receive the real-time ambient temperature collected by the temperature sensor.

3. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 1, characterized in that, In step S2, calculating the rotation deviation using the relative tilt angle obtained by fitting the radar point cloud data and the absolute pitch angle specifically includes: The relative tilt angle is extracted by linear fitting of the radar point cloud data; The rotational deviation is calculated using the rotational deviation formula, and the rotational deviation is equal to the difference between the relative tilt angle and the absolute pitch angle.

4. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 1, characterized in that, In step S2, the process of correcting the initial translation parameters based on the real-time ambient temperature to obtain the corrected translation parameters specifically includes: The temperature correction coefficient is calculated using the temperature correction formula based on the difference between the real-time ambient temperature and the reference temperature constant. The initial translation parameter is multiplied by the temperature correction coefficient using the translation correction formula to obtain the corrected translation parameter.

5. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 4, characterized in that, In step S2, the data of the end region is unified to the inertial navigation absolute coordinate system using the coordinate transformation formula to obtain the transformed inertial navigation absolute coordinates. This specifically includes: Using the coordinate transformation formula, the original radar relative coordinates of the end area data are rotated and transformed according to the rotation deviation; The data after rotation transformation is translated according to the corrected translation parameters to unify the data of the end region to the inertial navigation absolute coordinate system, thereby obtaining the transformed inertial navigation absolute coordinates.

6. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 1, characterized in that, In step S3, performing differential data fusion between the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device to obtain fused coordinates specifically includes: When the coordinate point in the converted inertial navigation absolute coordinates is located in the end-point fusion area, the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device are weighted and fused using the weighting coefficients of the radar data and the inertial navigation data, and the end-point fusion formula, to obtain the fused coordinates. The weighting coefficients of the radar data and the inertial navigation data are fixed values, and the weighting coefficient of the radar data is greater than that of the inertial navigation data. These fixed values ​​are preset based on the radar's superior ranging accuracy in the terminal area.

7. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 6, characterized in that, In step S3, performing differential data fusion between the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device to obtain fused coordinates further includes: When the coordinate point in the converted inertial navigation absolute coordinates is located in the transition fusion region, the weighting coefficient of the radar data and the weighting coefficient of the inertial navigation data are dynamically calculated using the transition weighting formula. Using the aforementioned end-fusion formula and dynamically calculated weighting coefficients, the converted inertial navigation absolute coordinates and the measured coordinates of the inertial navigation device are weighted and fused to obtain the fused coordinates; In the transition weight formula, the weight coefficient of the radar data decreases linearly as the distance between the current coordinate point and the junction point increases.

8. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 1, characterized in that, In step S3, the smoothing process of the fused discrete point series using a curve smoothing formula specifically includes: For any target data point in the fused discrete point sequence, the smoothed ordinate of the target data point is calculated using the curve smoothing formula. The smoothed ordinate is equal to the arithmetic mean of the original ordinates of the target data point and its adjacent nodes in the neighborhood, thereby obtaining the smoothed fused discrete point sequence.

9. The method for linear fusion across the entire working plane of laser target inertial navigation radar according to claim 1, characterized in that, The S4 step specifically includes: For the data of the end fusion area and the transition fusion area, a quadratic polynomial is used for fitting, and for the data of the middle independent area, a cubic polynomial is used for fitting. The piecewise equations are then spliced ​​together to obtain the complete curve of the entire working surface. The vertical distance of each sampling point relative to the designed straight line is calculated using the straightness deviation formula, and the maximum vertical distance is extracted. The maximum vertical distance is corrected by the root mean square error synthesis using the index synthesis formula to obtain the maximum straightness deviation.

10. An electronic device, comprising a processor, a communication interface, a memory, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the linear fusion method based on the full working surface of laser target inertial navigation radar as described in any one of claims 1-9.

Images