A puncher posture sensing method

Abstract

The application relates to a punch posture sensing method, which collects multi-source sensor information including inertial measurement unit data and multiple ranging data in real time, performs real-time cleaning and preprocessing on the data to improve effectiveness, then calculates real-time posture information of the punch through a data fusion algorithm, and calculates real-time drilling depth based on the ranging data. By comparing the real-time posture with a preset target posture, posture deviation information is generated, and visual display and operation guidance are combined with depth data, so that accurate monitoring and prompting of the punching process are realized, and the accuracy and operation convenience of the punching operation are effectively improved.

Description

Technical Field

[0001] This application relates to the field of posture perception technology, and in particular to a posture perception method for a punching machine. Background Technology

[0002] In construction and interior decoration, using handheld drilling machines, such as impact drills, to drill vertically, horizontally, or at specific angles into walls or floors is a common task. The accuracy of this work directly affects the quality of embedded parts installation and pipeline laying.

[0003] Currently, the operation of handheld punching machines relies entirely on the worker's experience. When performing punching operations, it is difficult for workers to maintain a high degree of consistency in the machining axis, ensure accurate machining depth, and detect deviations in a timely manner. Summary of the Invention

[0004] Therefore, it is necessary to provide a punching machine posture sensing method to address the problems that traditional handheld punching machines make it difficult for workers to maintain a high degree of alignment and precision in the machining axis, as well as the inability to detect deviations in a timely manner during punching operations.

[0005] This application provides a method for sensing the posture of a punching machine, including: Real-time acquisition of multi-source sensor data during drilling machine operation, wherein the multi-source sensor data includes at least inertial measurement unit data, first ranging data, and second ranging data; The multi-source sensor data is cleaned and preprocessed in real time to obtain effective sensor data; Based on the effective sensor data, the real-time attitude information of the drilling machine is calculated through a data fusion algorithm, and the real-time depth information of the drilling operation is calculated based on at least one of the ranging data. The real-time attitude information is compared with the preset target attitude to generate attitude deviation information, which is then combined with the real-time depth information for visualization and operation guidance.

[0006] Furthermore, the real-time cleaning and preprocessing of the multi-source sensor data to obtain effective sensor data includes: Real-time compensation for zero bias and scale factor errors is performed on the gyroscope and accelerometer data in the inertial measurement unit; Outlier identification and removal are performed on the first ranging data and / or the second ranging data using a sliding window-based statistical filtering method. Based on the working state of the punching machine, an adaptive noise reduction filter is applied to the data of the inertial measurement unit; when the punching machine is detected to be in a high vibration working state, the weight of the accelerometer data in the subsequent attitude calculation is reduced.

[0007] Furthermore, the calculation of the real-time attitude information of the punching machine using a data fusion algorithm includes: An extended Kalman filter algorithm is used to fuse the preprocessed gyroscope angular velocity data, accelerometer data, and magnetometer data. The extended Kalman filter's state vector includes at least attitude quaternions and gyroscope zero bias, while the observation vector is constructed based on the gravity field and geomagnetic field directions calculated from accelerometer and magnetometer data.

[0008] Furthermore, the calculation of real-time depth information for the drilling operation based on at least one of the ranging data includes: At the instant the drill bit of the drilling machine contacts the working surface, the value of the first distance measurement data is recorded as the initial reference distance; During the drilling process, the current value of the first ranging data is acquired in real time, and the current value is corrected according to the real-time attitude information; The difference between the initial reference distance and the corrected current value is calculated to obtain the real-time depth information.

[0009] Furthermore, the step of comparing the real-time attitude information with a preset target attitude to generate attitude deviation information includes: Calculate the axial deviation angle between the real-time attitude information and the target attitude; The target posture is calibrated and stored on-site according to the actual working conditions.

[0010] Furthermore, the step of comparing the real-time attitude information with a preset target attitude to generate attitude deviation information, and combining it with the real-time depth information for visualization and operation guidance, also includes: A dynamic attitude deviation threshold associated with the real-time depth information is preset; as the drilling depth increases, the dynamic attitude deviation threshold is allowed to increase. When the attitude deviation information exceeds the dynamic attitude deviation threshold at the current depth, an alarm message is sent.

[0011] Furthermore, the step of calculating the real-time attitude information of the drilling machine based on the effective sensor data using a data fusion algorithm, and calculating the real-time depth information of the drilling operation based on at least one of the ranging data, further includes: Based on the difference between the second ranging data and the first ranging data, and the fixed installation geometry between the two, an auxiliary attitude angle is calculated. The auxiliary attitude angle is compared with the corresponding attitude angle in the real-time attitude information calculated by the data fusion algorithm. If the deviation exceeds the verification limit, the sensor is marked as abnormal.

[0012] Furthermore, the job guidance includes: During the positioning phase, the posture deviation information and the relative height between the drilling machine and the working surface are displayed; During the initial drilling phase, it was confirmed that the initial reference distance had been successfully calibrated, and attitude stability was monitored. During the drilling phase, the real-time depth information and attitude deviation information are displayed simultaneously. During the completion phase, the drilling status is automatically determined by analyzing sudden changes in motor current, and depth measurement is stopped.

[0013] Furthermore, the hole punching machine posture sensing method also includes: The inertial measurement unit is subjected to multi-position static calibration to estimate and store its zero bias, scaling factor and non-orthogonal error parameters; The distance to output characteristics of the first and second rangefinders are calibrated on a standard plane with known distances.

[0014] Furthermore, the hole punching machine posture sensing method also includes: The internal temperature of the drilling machine is monitored in real time, and dynamic temperature compensation is performed on the zero bias of the inertial measurement unit based on the pre-stored temperature-error curve. When strong magnetic interference is detected in the working environment, the magnetometer data is blocked, and the heading-keeping mode of the gyroscope and accelerometer is activated.

[0015] This application relates to a method for attitude perception of a drilling machine. It involves real-time acquisition of multi-source sensor information, including data from an inertial measurement unit and multiple ranging data points. The data is cleaned and preprocessed in real-time to improve its effectiveness. A data fusion algorithm is then used to calculate the real-time attitude information of the drilling machine, and the real-time drilling depth is calculated based on the ranging data. By comparing the real-time attitude with a preset target attitude, attitude deviation information is generated and combined with depth data for visualization and operation guidance. This enables precise monitoring and prompting of the drilling process, effectively improving the accuracy and ease of operation of the drilling operation. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a punching machine posture sensing method provided in an embodiment of this application. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0018] like Figure 1 As shown, in one embodiment of this application, the punching machine posture sensing method includes the following steps S100 to S400.

[0019] S100, real-time acquisition of multi-source sensor data during the operation of the drilling machine, wherein the multi-source sensor data includes at least inertial measurement unit data, first ranging data and second ranging data.

[0020] Specifically, the data from the inertial measurement unit is obtained by the inertial measurement unit, which is a sensor module that integrates a three-axis gyroscope, a three-axis accelerometer, and a three-axis magnetometer.

[0021] The first distance measurement data is obtained by the first distance measuring instrument, which is installed along the axis of the drill bit and directly measures the change in distance from the drill tip to the working face. The first distance measuring instrument is a laser distance measuring instrument.

[0022] The second ranging data is obtained by a second rangefinder, which is installed at a certain angle to the first rangefinder. Its functions are twofold: first, to serve as a backup for the first rangefinder; and second, to perform cross-verification by combining the readings from the first rangefinder with known geometric relationships, allowing for the independent calculation of an attitude angle to verify the reliability of the inertial measurement unit (IMU) data.

[0023] S200, the multi-source sensor data is cleaned and preprocessed in real time to obtain effective sensor data.

[0024] S300, based on the effective sensor data, calculates the real-time attitude information of the drilling machine through a data fusion algorithm, and calculates the real-time depth information of the drilling operation based on at least one of the ranging data.

[0025] S400, compare the real-time attitude information with the preset target attitude to generate attitude deviation information, and combine it with the real-time depth information for visualization display and operation guidance.

[0026] In this embodiment, multi-source sensor information, including inertial measurement unit data and multiple ranging data, is collected in real time. The data is then cleaned and preprocessed in real time to improve its effectiveness. A data fusion algorithm is then used to calculate the real-time attitude information of the drilling machine, and the real-time drilling depth is calculated based on the ranging data. By comparing the real-time attitude with a preset target attitude, attitude deviation information is generated and combined with depth data for visualization and operation guidance. This enables precise monitoring and prompting of the drilling process, effectively improving the accuracy and ease of operation of the drilling operation.

[0027] In one embodiment of this application, the real-time cleaning and preprocessing of the multi-source sensor data to obtain effective sensor data includes the following steps S201 to S203.

[0028] S201, perform real-time compensation for zero bias and scale factor errors of the gyroscope and accelerometer data in the inertial measurement unit.

[0029] Specifically, zero bias and scale factor compensation refers to estimating and storing the inherent zero-point error and proportional error of the sensor when the drilling machine is powered on or calibrated, and subtracting them during measurement to ensure measurement accuracy.

[0030] S202, outlier identification and removal are performed on the first ranging data and / or the second ranging data using a sliding window-based statistical filtering method.

[0031] Specifically, outlier removal employs a sliding window statistical method to identify and remove abnormal data points caused by momentary occlusion or electrical interference in real time, preventing them from interfering with subsequent calculations.

[0032] For example, using the sliding window statistical method with a window length of 10 sampling points, the mean μ and standard deviation σ of the data within the window are calculated.

[0033] If the current sampled value dt satisfies |dt−μ|>3σ, it is considered an outlier and replaced by the previous valid value or the median within the window.

[0034] Simultaneously, the number of consecutive invalid samples is detected. If it exceeds a threshold, such as 4 times, a sensor abnormality flag is triggered.

[0035] S203, based on the operating state of the punching machine, apply adaptive noise reduction filtering to the inertial measurement unit data. When the punching machine is detected to be in a high-vibration operating state, reduce the weight of the accelerometer data in subsequent attitude calculations.

[0036] Specifically, adaptive noise reduction filtering dynamically adjusts the filtering algorithm parameters based on the operating state determined by vibration sensor data. For example, during high-frequency drilling, a strong low-pass filter is applied to the accelerometer data to suppress severe vibration noise; while during static aiming, a weak filter is used to maintain response speed.

[0037] The vibration of the drilling machine is detected by a vibration sensor.

[0038] In this embodiment, a real-time sensor data processing workflow is constructed by integrating zero-bias compensation, outlier removal, and adaptive noise reduction filtering. This workflow significantly improves the quality and validity of the raw data, effectively suppresses various sensor errors and environmental interference, and is particularly adaptable to the high vibration conditions of the drilling machine, providing stable input for subsequent attitude and depth calculations. This is a key guarantee for the accuracy and robustness of the entire method.

[0039] In one embodiment of this application, the step of calculating the real-time attitude information of the punching machine using a data fusion algorithm includes: An extended Kalman filter algorithm is used to fuse the preprocessed gyroscope angular velocity data, accelerometer data, and magnetometer data.

[0040] The extended Kalman filter's state vector includes at least attitude quaternions and gyroscope zero bias, while the observation vector is constructed based on the gravity field and geomagnetic field directions calculated from accelerometer and magnetometer data.

[0041] In this embodiment, the Extended Kalman Filter (EKF) algorithm is used for state calculation. The state vector typically includes attitude quaternions and gyroscope zero bias; the observation vectors come from the accelerometer and magnetometer. Through iterative prediction and updating, the EKF algorithm optimally estimates the current attitude and simultaneously estimates the real-time zero bias of the gyroscope, thereby effectively suppressing long-term drift.

[0042] In one embodiment of this application, the calculation of real-time depth information for the drilling operation based on at least one of the ranging data includes the following steps S301 to S303.

[0043] S301, at the instant the drill bit of the drilling machine contacts the working surface, the value of the first distance measurement data is recorded as the initial reference distance.

[0044] Specifically, when the drill bit lightly touches the working surface, a sudden drop in the rate of change of the first rangefinder reading, for example, from 10 mm / s to 1 mm / s, is determined as the instant of contact. The reading of the first rangefinder at this moment is recorded as the initial reference distance and stored.

[0045] The instant the drill bit contacts the working surface can also be determined by detecting the motor current, because the motor load increases at the instant the drill bit contacts the working surface, and its load current value changes.

[0046] S302, during the drilling process, the current value of the first ranging data is acquired in real time, and the current value is corrected according to the real-time attitude information.

[0047] Specifically, during the drilling process, the current value of the first rangefinder is read in real time. Since a certain tilt occurs during drilling, the current value of the first rangefinder needs to be geometrically corrected according to the real-time attitude of the drilling machine. The corrected current value of the first rangefinder is obtained by multiplying the current value of the first rangefinder by the pitch angle and the yaw angle. Its physical meaning is to project the tilt measurement onto the drilling axis direction.

[0048] S303, calculate the difference between the initial reference distance and the corrected current value to obtain the real-time depth information.

[0049] Specifically, the real-time depth is obtained by subtracting the initial reference distance from the corrected current value of the first rangefinder.

[0050] In one embodiment of this application, the step of comparing the real-time attitude information with a preset target attitude to generate attitude deviation information includes the following step S304.

[0051] S304, Calculate the axial deviation angle between the real-time attitude information and the target attitude.

[0052] The target posture is calibrated and stored on-site according to the actual working conditions.

[0053] Specifically, the target attitude can be determined by aligning the punch with a preset direction, such as a perpendicular wall, and recording the current attitude as the target attitude, or by using a preset target pitch angle and yaw angle as the target attitude.

[0054] In this embodiment, high-precision, drift-resistant estimation of the drilling machine's real-time attitude is achieved by fusing multi-sensor data using an extended Kalman filter algorithm. Simultaneously, geometric correction is performed by combining ranging data and attitude information, enabling accurate, real-time measurement of drilling depth. Transforming multi-source information into key state quantities that can be directly used for monitoring and guidance, such as attitude angles and depth, represents a shift from perception to cognition.

[0055] In one embodiment of this application, the step of comparing the real-time attitude information with a preset target attitude to generate attitude deviation information, and combining the real-time depth information for visualization and operation guidance, further includes the following steps S401 to S402.

[0056] S401, a dynamic attitude deviation threshold associated with the real-time depth information is preset; as the drilling depth increases, the dynamic attitude deviation threshold is allowed to increase.

[0057] S402, when the attitude deviation information exceeds the dynamic attitude deviation threshold at the current depth, an alarm message is sent.

[0058] Specifically, the dynamic attitude deviation threshold is not a fixed value, but is dynamically adjusted according to the working conditions.

[0059] For example, in the drilling depth range of 0-20mm, the dynamic attitude deviation threshold is set more strictly, allowing pitch / yaw deviation of ±1.0° to ensure accurate drilling.

[0060] During the drilling depth range of 20-40mm, the allowable pitch / yaw deviation is ±1.5°.

[0061] During the drilling depth range of 40-80mm, the allowable pitch / yaw deviation is ±2.0°.

[0062] When the drilling depth is greater than 80mm, the allowable pitch / yaw deviation is ±2.5°.

[0063] In this embodiment, the dynamic attitude deviation threshold can be appropriately relaxed as the drilling depth increases, because the existing hole wall has a certain guiding effect, and the vibration is greater in deep holes, thus avoiding frequent false alarms.

[0064] Furthermore, by comparing real-time attitude with target attitude and generating deviation information, combined with depth data, comprehensive visual monitoring and phased intelligent guidance of the drilling process were achieved. By introducing dynamic deviation thresholds and multi-stage guidance logic, operational deviations can be indicated in real time and intuitively, and alarms can be triggered in case of anomalies, significantly reducing the difficulty of operation and improving the first-time success rate and process controllability of drilling operations.

[0065] In one embodiment of this application, the step of calculating the real-time attitude information of the drilling machine based on the effective sensor data using a data fusion algorithm, and calculating the real-time depth information of the drilling operation based on at least one of the ranging data, further includes the following steps S305 to S306.

[0066] S305, based on the difference between the second ranging data and the first ranging data, and the fixed installation geometry between the two, an auxiliary attitude angle is calculated.

[0067] Specifically, the installation baseline length of the first and second rangefinders is L, the included angle is α, and the reading difference between the first and second rangefinders is Δd = d2 − d1.

[0068] Under the assumptions of plane geometry and ignoring lateral offset, an estimated pitch angle can be calculated: ; S306, compare the auxiliary attitude angle with the corresponding attitude angle in the real-time attitude information calculated by the data fusion algorithm. If the deviation exceeds the verification limit, mark the sensor as abnormal.

[0069] Specifically, what will be obtained Compare the pitch angle output by the inertial measurement unit with the pitch angle output by the inertial measurement unit. If the absolute value of the difference between the two is greater than the preset upper limit of the verification, such as 3°, it is marked as an abnormality of the rangefinder or inertial measurement unit.

[0070] In this embodiment, the auxiliary attitude angle is independently calculated using the fixed geometric relationship between the two rangefinders, and then cross-validated with the results of the main fusion algorithm. A built-in sensor self-checking function is implemented, which can promptly detect sensor failures or data anomalies and trigger anomaly flags, enhancing the system's reliability and fault diagnosis capabilities.

[0071] In one embodiment of this application, the job guidance includes: During the positioning phase, the posture deviation information and the relative height between the drilling machine and the working surface are displayed.

[0072] Specifically, the display screen shows the attitude deviation arrow, value, and distance from the working surface in real time.

[0073] During the initial drilling phase, it was confirmed that the initial reference distance had been successfully calibrated, and attitude stability was monitored.

[0074] Specifically, once the reference distance is successfully calibrated, it indicates that drilling can begin. The system monitors attitude stability; if the attitude angle changes by more than 0.5° within 2 seconds, it indicates an unstable grip.

[0075] During the drilling phase, the real-time depth information and attitude deviation information are displayed simultaneously.

[0076] Specifically, during the drilling process, the data on real-time depth and posture deviation will be displayed.

[0077] During the completion phase, the drilling status is automatically determined by analyzing sudden changes in motor current, and depth measurement is stopped.

[0078] Specifically, by detecting sudden changes in motor current, for example, if the current value of the drilling machine motor drops by more than 40% within 10ms, it is determined that the hole is drilled through, the depth counting is automatically stopped, and a message indicating that the hole is drilled through is displayed.

[0079] In one embodiment of this application, the punching machine posture sensing method further includes: The inertial measurement unit is subjected to multi-position static calibration to estimate and store its zero bias, scaling factor and non-orthogonal error parameters.

[0080] Specifically, the drilling machine is fixed to a hexahedral fixture, and each axis is aligned sequentially in six directions: up, down, left, right, front, and back. Data is collected for 3 seconds at each position while the machine is stationary. The zero-bias, scaling factor, and non-orthogonal error matrices are then fitted using the least squares method.

[0081] The distance to output characteristics of the first and second rangefinders are calibrated on a standard plane with known distances.

[0082] Specifically, on the optical platform, the rangefinder is aimed at a standard distance target plate, for example, a distance from 50mm to 500mm, with the step distance set to 50mm, and the output value is recorded.

[0083] In one embodiment of this application, the punching machine posture sensing method further includes: The internal temperature of the drilling machine is monitored in real time, and dynamic temperature compensation is performed on the zero bias of the inertial measurement unit based on the pre-stored temperature-error curve.

[0084] Specifically, by installing a temperature sensor inside the drilling machine, the temperature of the inertial measurement unit is monitored in real time, and then the zero-bias temperature compensation of the inertial measurement unit is queried based on the detected temperature.

[0085] When strong magnetic interference is detected in the working environment, the magnetometer data is blocked, and the heading-keeping mode of the gyroscope and accelerometer is activated.

[0086] Specifically, the magnetic field modulus is calculated in real time. If the deviation from the typical value of the geomagnetic field exceeds 30%, it is judged as strong magnetic interference. The typical value of the geomagnetic field can be obtained through detection. The magnetometer data is shielded and converted to use gyroscopes and accelerometers for heading maintenance.

[0087] The technical features of the above embodiments can be combined arbitrarily, and the execution order of the method steps is not restricted. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0088] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A hole puncher posture sensing method for a handheld hole puncher, characterized in that, The punching machine posture sensing method includes: Real-time acquisition of multi-source sensor data during drilling machine operation, wherein the multi-source sensor data includes at least inertial measurement unit data, first ranging data, and second ranging data; The multi-source sensor data is cleaned and preprocessed in real time to obtain effective sensor data; Based on the effective sensor data, the real-time attitude information of the drilling machine is calculated through a data fusion algorithm, and the real-time depth information of the drilling operation is calculated based on at least one of the ranging data. The real-time attitude information is compared with the preset target attitude to generate attitude deviation information, which is then combined with the real-time depth information for visualization and operation guidance. The step of comparing the real-time attitude information with the preset target attitude to generate attitude deviation information, and combining it with the real-time depth information for visualization and operation guidance, includes: Calculate the axial deviation angle between the real-time attitude information and the target attitude; The target posture is calibrated and stored on-site according to the actual working conditions; A dynamic attitude deviation threshold associated with the real-time depth information is preset; as the drilling depth increases, the dynamic attitude deviation threshold is allowed to increase. When the attitude deviation information exceeds the dynamic attitude deviation threshold at the current depth, an alarm message is sent.

2. The punching machine posture sensing method according to claim 1, characterized in that, The real-time cleaning and preprocessing of the multi-source sensor data to obtain effective sensor data includes: Real-time compensation for zero bias and scale factor errors is performed on the gyroscope and accelerometer data in the inertial measurement unit; Outlier identification and removal are performed on the first ranging data and / or the second ranging data using a sliding window-based statistical filtering method. Based on the working state of the punching machine, an adaptive noise reduction filter is applied to the data of the inertial measurement unit; when the punching machine is detected to be in a high vibration working state, the weight of the accelerometer data in the subsequent attitude calculation is reduced.

3. The punching machine posture sensing method according to claim 1 or 2, characterized in that, The calculation of the real-time attitude information of the punching machine using a data fusion algorithm includes: An extended Kalman filter algorithm is used to fuse the preprocessed gyroscope angular velocity data, accelerometer data, and magnetometer data. The extended Kalman filter's state vector includes at least attitude quaternions and gyroscope zero bias, while the observation vector is constructed based on the gravity field and geomagnetic field directions calculated from accelerometer and magnetometer data.

4. The punching machine posture sensing method according to claim 3, characterized in that, The calculation of real-time depth information for the drilling operation based on at least one of the ranging data includes: At the instant the drill bit of the drilling machine contacts the working surface, the value of the first distance measurement data is recorded as the initial reference distance; During the drilling process, the current value of the first ranging data is acquired in real time, and the current value is corrected according to the real-time attitude information; The difference between the initial reference distance and the corrected current value is calculated to obtain the real-time depth information.

5. The punching machine posture sensing method according to claim 1, characterized in that, The step of calculating the real-time attitude information of the drilling machine based on the effective sensor data using a data fusion algorithm, and calculating the real-time depth information of the drilling operation based on at least one of the ranging data, further includes: Based on the difference between the second ranging data and the first ranging data, and the fixed installation geometry between the two, an auxiliary attitude angle is calculated. The auxiliary attitude angle is compared with the corresponding attitude angle in the real-time attitude information calculated by the data fusion algorithm. If the deviation exceeds the verification limit, the sensor is marked as abnormal.

6. The punching machine posture sensing method according to claim 4, characterized in that, The job guidance includes: During the positioning phase, the posture deviation information and the relative height between the drilling machine and the working surface are displayed; During the initial drilling phase, it was confirmed that the initial reference distance had been successfully calibrated, and attitude stability was monitored. During the drilling phase, the real-time depth information and attitude deviation information are displayed simultaneously. During the completion phase, the drilling status is automatically determined by analyzing sudden changes in motor current, and depth measurement is stopped.

7. The punching machine posture sensing method according to claim 1, characterized in that, The hole punching machine posture sensing method further includes: The inertial measurement unit is subjected to multi-position static calibration to estimate and store its zero bias, scaling factor and non-orthogonal error parameters; The distance-to-output characteristics of the first and second rangefinders are calibrated on a standard plane with known distances.

8. The punching machine posture sensing method according to claim 7, characterized in that, The hole punching machine posture sensing method further includes: The internal temperature of the drilling machine is monitored in real time, and dynamic temperature compensation is performed on the zero bias of the inertial measurement unit based on the pre-stored temperature-error curve. When strong magnetic interference is detected in the working environment, the magnetometer data is blocked, and the heading-keeping mode of the gyroscope and accelerometer is activated.

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