A method, system, medium, equipment and terminal for measuring posture of a roadheader

Abstract

The present invention belongs to the technical field of tunnel boring machine construction, and discloses a tunnel boring machine posture measurement method, system, medium, equipment and terminal. After measuring prism 1 to prism n-1, when measuring prism n, the coordinates of prism 1 to prism n-1 when measuring prism n are predicted; the three posture angles output by the angle sensor at this moment are read, and the predicted coordinates of prism 1 to prism n-1 and the measured coordinates of prism n are used as a simultaneous equation group to solve the tunnel boring machine posture. In order to solve the problem of low precision of multi-prism posture measurement in tunnel boring machine construction, the present invention proposes a tunnel boring machine posture measurement method based on multi-prism trajectory prediction. Compared with the unpredicted model, the tunnel boring machine posture measurement method based on multi-prism trajectory prediction of the present invention can significantly improve the measurement accuracy and measurement frequency. The present invention solves the position error caused by asynchronous prism measurement and improves the accuracy of posture measurement.

Description

Technical Field

[0001] The present invention belongs to the field of measurement and control technology, and in particular relates to a method, system, medium, equipment and terminal for measuring the posture of a roadheader. Background Art

[0002] At present, the multi-prism method is a common method for measuring the posture of tunnel boring machines. Before the start of tunnel construction, the tunnel boring machine manufacturer installs multiple prisms on the tunnel boring machine and measures the positional relationship between these prisms and the center of the tunnel boring machine in the factory. During the construction process, the positional relationship between these prisms and the center of the tunnel boring machine will not change. During the excavation process, the tunnel boring machine moves along the direction of the design axis. The person in charge of the survey of the tunnel construction project first installs a total station and a rear-view prism on a hanging basket with known coordinate positions; then uses the total station to measure multiple prisms in turn, and the three-dimensional coordinates of each prism can be calculated at this time; the prism coordinates obtained by these factory measurements and construction measurements are combined with the head and tail coordinates of the tunnel boring machine, and the coordinates of the center of the tunnel boring machine under the design route can be calculated by combining the equations.

[0003] However, there are the following problems in actual use: Due to the different hardness of the surrounding rock during the construction of the tunnel boring machine, the tunneling speed fluctuates within a range, and the tunneling speed is generally in the range of 10mm / min to 120mm / min. The total station measurement of prisms includes several steps such as searching, aiming, and measuring. Affected by ambient light, dust, and the rotation speed of the total station's own motor, it usually takes 10s to 30s to measure a prism. During the entire measurement process, the total station needs to be used to measure each prism in turn, which will bring three problems. The first problem is that the general multi-prism method in the tunnel only observes the coordinates of three prisms, lacks redundant observations, and once a certain coordinate measurement error is large, it will have a huge impact on the accuracy of the final posture solution. The second problem is that after measuring the first prism, the first prism will be displaced when measuring the second prism, which will cause the measured prism coordinates to have time and space mismatches. The third problem is that the overall measurement cycle is relatively long, generally 1min to 2min, resulting in untimely posture updates.

[0004] Through the above analysis, the problems and defects of the prior art are as follows:

[0005] (1) The general multi-prism method in the tunnel only observes the coordinates of three prisms and lacks redundant observations. Once the measurement error of a coordinate is large, it will have a huge impact on the accuracy of the final pose solution.

[0006] (2) After measuring the first prism, when measuring the second prism, the first prism will be displaced again, which will cause the measured prism coordinates to have a time-space mismatch. This will cause serious errors when solving the pose using these mismatched measurement data.

[0007] (3) The overall measurement cycle is relatively long, generally 1 to 2 minutes, resulting in untimely posture updates. Summary of the invention

[0008] In view of the problems existing in the prior art, the present invention provides a method, system, medium, equipment and terminal for measuring the posture of a tunnel boring machine, and in particular, relates to a method, system, medium, equipment and terminal for measuring the posture of a tunnel boring machine based on polygonal prism trajectory prediction.

[0009] The present invention is implemented in this way: a method for measuring the posture of a roadheader, the method comprising:

[0010] After measuring prism 1 to prism n-1, the coordinates of prism 1 to prism n-1 when measuring prism n are predicted when measuring prism n; read the three attitude angles output by the angle sensor at this moment, and use the predicted coordinates of prism 1 to prism n-1 and the measured coordinates of prism n as a simultaneous equation group to solve the posture of the tunnel boring machine.

[0011] Furthermore, the tunnel boring machine posture measurement method further includes:

[0012] N prisms and m attitude angle sensors are installed on the tunnel boring machine; the total station measures the coordinates of 1 to n prisms in sequence, and after completing the measurement of the nth prism, predicts the coordinates of prisms 1 to n-1 at the time of measuring prism n, and unifies the coordinates into the same coordinate system at the same time; the prediction algorithm adopts the segmented Kalman filter algorithm for prediction, and the prediction algorithm sequentially matches the linearity of the design route of the tunnel boring machine, establishes the state equation, and integrates it with the observation value to perform Kalman filter prediction.

[0013] Further, the tunnel boring machine posture measurement method comprises the following steps:

[0014] Step 1: Use a total station to measure the coordinates of multiple prisms on the tunnel boring machine in sequence, and use an angle sensor installed on the tunnel boring machine to measure multiple attitude angles;

[0015] Step 2: Use the segmented Kalman filter algorithm to predict the coordinates of multiple prisms at the same time;

[0016] Step three: Use the coordinate transformation model to establish the measurement equations and use the least squares method to solve the posture.

[0017] Furthermore, the plurality of prisms include two or more prisms, and preferably the number of prisms is three.

[0018] The angle sensor is a tilt sensor or a gyroscope or other sensors, and the attitude angle uses 1, 2 or 3 attitude angles, preferably 3 attitude angles.

[0019] The state equation is determined according to the line type of the design line segment where the tunnel boring machine is currently located, and is determined according to the straight line segment, the transition curve segment and the circular curve segment respectively.

[0020] Furthermore, the tunnel boring machine posture measurement method further includes:

[0021] (1) Constructing the equation of state

[0022] 1) Linear equation of state

[0023] X(k+1)=ΦX(k)+ΓW(k);

[0024] X=[NEH dl va] T ;

[0025]

[0026] 2) Easement curve state equation

[0027]

[0028] in,

[0029] X=[NEH l dl va θ dθ β] T ;

[0030]

[0031] M 11 =cos(θ k )·cos(β k )·cos(α)-sin(θ k )·cos(β k )·sin(α);

[0032] M 12 =-dl k ·sin(θ k )·cos(β k )·cos(α)-dl k ·cos(θ k )·cos(β k )·sin(α);

[0033] M 12 =-dl k ·cos(θ k )·sin(β k )·cos(α)+dl k ·cos(θ k )·sin(β k )·sin(α);

[0034] M 21 =cos(θ k )·cos(β k )·sin(α)+sin(θ k )·cos(β k )·cos(α);

[0035] M 22 =-dl k ·sin(θ k )·cos(β k )·cos(α)+dl k ·cos(θ k )·cos(β k )·cos(α);

[0036] M 23 =-dl k ·cos(θ k )·sin(β k )·cos(α)-dl k ·sin(θ k )·sin(β k )·cos(α);

[0037]

[0038]

[0039] 3) Circular curve state equation

[0040] The structure of circular curve is similar to that of transition curve, only the calculation of angle increment is different, so the formula is:

[0041] M 31 =0;

[0042]

[0043] Among them, N is the north coordinate, E is the east coordinate, H is the elevation, dL is the cylinder increment, α is the azimuth of the designed route, T is the measurement period, β is the pitch angle, α is the azimuth, and L is the forward distance; the velocity v and acceleration a are obtained through measurement.

[0044] (2) Constructing the observation equation

[0045] The forward distance of the tunnel boring machine is measured by the cylinder stroke sensor, and the coordinates of the prism are measured by the total station. The stroke of the cylinder stroke sensor and the coordinates of the prism measured by the total station are used as observation quantities.

[0046] The prism coordinates measured by the total station and the cylinder stroke measured by the cylinder stroke sensor are used as observation values, and the observation equation is listed:

[0047] Z=[NEHL] T ;

[0048]

[0049]

[0050] (3) Forecast update

[0051] 1) The straight line segment is directly predicted using Kalman filtering:

[0052]

[0053] P(k+1|k)=φ(k+1|k)P(k)φ T (k+1|k)+Q(k+1);

[0054] K(k+1)=P(k+1|k)H T (k+1)[H(k+1)P(k+1|k)H T (k+1)+R(k+1)] -1 ;

[0055]

[0056] P(k+1)=[IK(k+1)H(k+1)]P(k+1|k);

[0057] 2) For the transition curve and circular curve segments, due to the existence of nonlinear functions, the linearized model is predicted using the extended Kalman function. Then:

[0058]

[0059] P(k+1|k)=Φ(k+1|k)P(k)Φ T (k+1|k)+Q(k+1);

[0060] K(k+1)=P(k+1|k)H T (k+1)[H(k+1)P(k+1|k)H T (k+1)+R(k+1)] -1 ;

[0061]

[0062] P(k+1)=[IK(k+1)H(k+1)]P(k+1|k).

[0063] Furthermore, the tunnel boring machine posture measurement method further includes:

[0064] The angle sensor measures m attitude angles of the tunnel boring machine, and according to the predicted prism group coordinates and attitude angles, a group of equations is established; the least squares criterion is used as an estimation condition to find the optimal solution for error correction.

[0065] Another object of the present invention is to provide a tunneling machine posture measurement system using the tunneling machine posture measurement method, the tunneling machine posture measurement system comprising:

[0066] An attitude angle measurement module is used to sequentially measure the coordinates of multiple prisms on the tunnel boring machine using a total station, and to measure multiple attitude angles using an angle sensor installed on the tunnel boring machine;

[0067] A prism coordinate prediction module is used to predict the coordinates of multiple prisms at the same time using a segmented Kalman filter algorithm;

[0068] The posture measurement module is used to establish a measurement equation group using a coordinate transformation model and solve the posture using the least squares method.

[0069] Another object of the present invention is to provide a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and when the computer program is executed by the processor, the processor performs the following steps:

[0070] After measuring prism 1 to prism n-1, the coordinates of prism 1 to prism n-1 when measuring prism n are predicted when measuring prism n; read the three attitude angles output by the angle sensor at this moment, and use the predicted coordinates of prism 1 to prism n-1 and the measured coordinates of prism n as a simultaneous equation group to solve the posture of the tunnel boring machine.

[0071] Another object of the present invention is to provide a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the following steps:

[0072] After measuring prism 1 to prism n-1, the coordinates of prism 1 to prism n-1 when measuring prism n are predicted when measuring prism n; read the three attitude angles output by the angle sensor at this moment, and use the predicted coordinates of prism 1 to prism n-1 and the measured coordinates of prism n as a simultaneous equation group to solve the posture of the tunnel boring machine.

[0073] Another object of the present invention is to provide an information data processing terminal, which is used to implement the tunnel boring machine posture measurement system.

[0074] In combination with the above technical solutions and the technical problems solved, please analyze the advantages and positive effects of the technical solutions to be protected by the present invention from the following aspects:

[0075] First, in view of the technical problems existing in the above-mentioned prior art and the difficulty of solving the problems, the technical solutions to be protected by the present invention and the results and data during the research and development process are closely combined to analyze in detail and deeply how the technical solutions of the present invention solve the technical problems, and some creative technical effects brought about after solving the problems. The specific description is as follows:

[0076] In order to solve the problem of low precision of multi-prism attitude measurement during tunnel boring machine construction, the present invention proposes a tunnel boring machine attitude measurement method based on multi-prism trajectory prediction. According to the position of the tunnel boring machine on the designed line, the present invention respectively establishes state equations for straight line segments, gentle curve segments, and circular curve segments, and performs Kalman filtering with the measured prism coordinates to predict the prism coordinates at the same time. Then, with the goal of minimizing the prism error, the least squares attitude solution is performed for multiple prism coordinates and multiple attitude angles. Compared with the existing multi-prism method, the tunnel boring machine attitude measurement method based on multi-prism trajectory prediction provided by the present invention can significantly improve the measurement accuracy and measurement frequency.

[0077] Second, considering the technical solution as a whole or from the perspective of the product, the technical effects and advantages of the technical solution to be protected by the present invention are described in detail as follows:

[0078] The present invention solves the position error caused by asynchronous prism measurement and improves the accuracy of posture measurement.

[0079] Third, as auxiliary evidence of the inventiveness of the claims of the present invention, it is also reflected in the following important aspects:

[0080] (1) The technical solution of the present invention fills the technical gap in the industry at home and abroad:

[0081] The multi-prism guidance system equipped with existing tunnel boring machines at home and abroad has a large measurement error during tunnel boring machine construction, and accurate posture measurement can only be performed when the tunnel boring machine is stopped. The present invention can realize dynamic and accurate measurement of the posture of the tunnel boring machine during tunneling construction.

[0082] (2) Whether the technical solution of the present invention solves the technical problem that people have been eager to solve but have never succeeded in solving: in order to measure the accurate posture during construction of a tunnel boring machine using a multi-prism guidance system, it is often necessary to stop and perform posture measurement to ensure measurement accuracy, which seriously affects construction efficiency. Dynamic, real-time and accurate measurement of the posture of a tunnel boring machine is an important issue facing the posture measurement of a tunnel boring machine using the multi-prism method. The present invention solves the measurement error caused by the movement of the tunnel boring machine during multi-prism measurement, can realize real-time dynamic measurement of the posture of a tunnel boring machine using the multi-prism method, and can improve construction efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0084] Figure 1 is a flow chart of a method for measuring the posture of a roadheader provided by an embodiment of the present invention;

[0085] Figure 2 It is a schematic diagram of a method for measuring the posture of a roadheader provided by an embodiment of the present invention;

[0086] Figure 3 It is a structural block diagram of a roadheader posture measurement system provided by an embodiment of the present invention;

[0087] Figure 4 is a flowchart of segmented Kalman filter prediction provided by an embodiment of the present invention;

[0088] Figure 5 is a simulation result of the existing solution provided by the embodiment of the present invention;

[0089] Figure 6 It is the simulation result of the present invention provided by the embodiment of the present invention.

[0090] In the figure: 1. Attitude angle measurement module; 2. Prism coordinate prediction module; 3. Position and posture measurement module. DETAILED DESCRIPTION

[0091] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0092] In view of the problems existing in the prior art, the present invention provides a method, system, medium, equipment and terminal for measuring the posture of a roadheader. The present invention is described in detail below in conjunction with the accompanying drawings.

[0093] 1. Explanatory Examples In order to enable those skilled in the art to fully understand how to implement the present invention, this section provides an illustrative example that expands and describes the technical solution of the claims.

[0094] like Figure 1 As shown, the method for measuring the posture of a roadheader provided by an embodiment of the present invention comprises the following steps:

[0095] S101, using a total station to sequentially measure the coordinates of a plurality of prisms on the tunnel boring machine, and using an angle sensor installed on the tunnel boring machine to measure a plurality of attitude angles;

[0096] S102, predicting the coordinates of multiple prisms at the same time using a segmented Kalman filter algorithm;

[0097] S103, using the coordinate transformation model to establish a measurement equation group, and using the least squares method to solve the posture.

[0098] The principle diagram of the method for measuring the posture of a tunnel boring machine provided by the embodiment of the present invention is as follows: Figure 2 shown.

[0099] like Figure 3 As shown, the tunnel boring machine posture measurement system provided by the embodiment of the present invention includes:

[0100] The attitude angle measurement module 1 is used to sequentially measure the coordinates of multiple prisms on the tunnel boring machine using a total station, and to measure multiple attitude angles using an angle sensor installed on the tunnel boring machine;

[0101] The prism coordinate prediction module 2 is used to predict the coordinates of multiple prisms at the same time using a segmented Kalman filter algorithm;

[0102] The posture measurement module 3 is used to establish a measurement equation group using a coordinate transformation model and solve the posture using the least square method.

[0103] The flowchart of the segmented Kalman filter prediction provided by the embodiment of the present invention is as follows: Figure 4 shown.

[0104] The technical solution of the present invention is further described below in conjunction with specific embodiments.

[0105] Example 1: Using a total station to measure the prism coordinates and a tilt sensor to measure the attitude angle

[0106] The invention provides a method for measuring the posture of a roadheader based on a polygonal prism trajectory prediction, which is used to solve the technical problem of low measurement accuracy of the existing polygonal prism of a roadheader.

[0107] The technical solution of the present invention to solve the above technical problems is as follows:

[0108] The tunnel boring machine is equipped with three prisms and two angle sensors for attitude angles. The total station measures the coordinates of prisms 1 to 3 in sequence. After completing the measurement of the nth prism, it predicts the coordinates of prisms 1 to n-1 at the time of measuring prism n, and unifies their coordinates into the same coordinate system at the same time. The prediction algorithm can use the segmented Kalman filter algorithm for prediction. The prediction algorithm sequentially matches the linearity of the design line where the tunnel boring machine is located, establishes the state equation, and then merges it with the observation value to perform Kalman filter prediction. Among them,

[0109] 1. Equation of state

[0110] 1) Linear equation of state

[0111] X(k+1)=ΦX(k)+ΓW(k) (1)

[0112] X=[NEH dl va] T (2)

[0113]

[0114] 2) Easement curve state equation

[0115]

[0116] in,

[0117] X=[NEH l dl va θ dθ β] T (5)

[0118]

[0119] M 11 =cos(θ k )·cos(β k )·cos(α)-sin(θ k )·cos(β k )·sin(α) (7)

[0120] M 12 =-dl k ·sin(θ k )·cos(β k )·cos(α)-dl k ·cos(θ k )·cos(β k )·sin(α) (8)

[0121] M 12 =-dl k ·cos(θ k )·sin(βk )·cos(α)+dl k ·cos(θ k )·sin(β k )·sin(α) (9)

[0122] M 21 =cos(θ k )·cos(β k )·sin(α)+sin(θ k )·cos(β k )·cos(α) (10)

[0123] M 22 =-dl k ·sin(θ k )·cos(β k )·cos(α)+dl k ·cos(θ k )·cos(β k )·cos(α) (11)

[0124] M 23 =-dl k ·cos(θ k )·sin(β k )·cos(α)-dl k ·sin(θ k )·sin(β k )·cos(α) (12)

[0125]

[0126]

[0127] 3) Circular curve state equation

[0128] The circular curve has a similar structure to the transition curve, only the angle increment calculation is different. Therefore, for formula 4, we have:

[0129] M 31 =0 (15)

[0130]

[0131] Among them, N is the north coordinate, E is the east coordinate, H is the elevation, dL is the cylinder increment, α is the azimuth of the designed route, T is the measurement period, β is the pitch angle, α is the azimuth angle, and L is the forward distance. The velocity v and acceleration a can be obtained by measurement.

[0132] 2. Observation equation

[0133] The forward distance of the tunnel boring machine can be measured by the cylinder stroke sensor, and the coordinates of the prism can be measured by the total station. Therefore, the stroke of the cylinder stroke sensor and the coordinates of the prism measured by the total station are used as the observed quantities.

[0134] The prism coordinates measured by the total station and the cylinder stroke measured by the cylinder stroke sensor are used as observation values. The observation equation can be listed as follows:

[0135] Z=[NEHL] T (17)

[0136]

[0137]

[0138] 3. Forecast Update

[0139] 1) Straight line segments can be predicted directly using Kalman filtering

[0140]

[0141] P(k+1|k)=φ(k+1|k)P(k)φ T (k+1|k)+Q(k+1) (21)

[0142] K(k+1)=P(k+1|k)H T (k+1)[H(k+1)P(k+1|k)H T (k+1)+R(k+1)] -1 (twenty two)

[0143]

[0144] P(k+1)=[IK(k+1)H(k+1)]P(k+1|k) (twenty four)

[0146] 2) For the transition curve and circular curve segments, because of the nonlinear functions, the linearized model is predicted using the extended Kalman:

[0147]

[0148] P(k+1|k)=Φ(k+1|k)P(k)Φ T (k+1|k)+Q(k+1) (26)

[0149] K(k+1)=P(k+1|k)H T (k+1)[H(k+1)P(k+1|k)H T(k+1)+R(k+1)] -1 (27)

[0150]

[0151] P(k+1)=[IK(k+1)H(k+1)]P(k+1|k) (29)

[0152] This method takes into account the changes in velocity and acceleration of the trajectory and can accurately predict the coordinates of the prism.

[0153] At the same time, the inclination sensor measures the two attitude angles of the tunnel boring machine. According to the predicted prism group coordinates and attitude angles, a set of equations is established. The least squares criterion is used as an estimation condition to find the optimal solution for error correction.

[0154] In order to solve the problem of low precision of polygonal prism posture measurement in tunnel boring machine construction, the present invention proposes a tunnel boring machine posture measurement method based on polygonal prism trajectory prediction. Compared with the unpredicted model, the method can improve the measurement accuracy and measurement frequency.

[0155] Example 2: Using a total station to measure prism coordinates and a gyroscope to measure attitude angles

[0156] This example Figure 2 As shown, a total station is used to measure three prisms and a gyroscope is used to measure three attitude angles.

[0157] 1. The total station first measures the coordinates of prism No. 1 at position 1, then measures prism No. 2 at position 2, and then measures the coordinates of prism No. 3 at position 3. When measuring the coordinates of prism No. 3, read the three attitude angles output by the gyroscope.

[0158] The segmented Kalman filter prediction method is used to predict the coordinates of prisms 1 and 2 when measuring prism 3. Then the predicted coordinates of prisms 1 and 2 and the measured coordinates of prism 3 are combined to form a system of equations to solve the position of the tunnel boring machine.

[0159] 2. The total station measures the coordinates of prism 1 at position 4 and reads the three attitude angles output by the gyroscope. The segmented Kalman filter prediction method is used to predict the coordinates of prisms 2 and 3 when measuring prism 1. Then the predicted coordinates of prisms 2 and 3 and the measured coordinates of prism 1 are combined to form a set of equations to solve the position of the tunnel boring machine.

[0160] 3. The total station measures the coordinates of prism No. 2 at position 5 and reads the three attitude angles output by the gyroscope. The segmented Kalman filter prediction method is used to predict the coordinates of prism No. 1 and prism No. 3 when measuring prism No. 2. Then the predicted coordinates of prism 1 and prism 3 and the measured coordinates of prism 2 are combined to form a set of equations to solve the position and attitude of the tunnel boring machine.

[0161] 4. Correct the error of the gyroscope that diverges over time. Position 6 is the state where the tunnel boring machine stops excavating. At this moment, the coordinates of prism 1, prism 2 and prism 3 are measured in sequence to solve the tunnel boring machine posture, and the calculated attitude angle is recalibrated to the gyroscope angle.

[0162] 5. Continue to the next measurement cycle.

[0163] 2. Application Examples: In order to prove the creativity and technical value of the technical solution of the present invention, this section provides application examples of the technical solution of the claims on specific products or related technologies.

[0164] Application Examples

[0165] Measuring prism coordinates using only a total station

[0166] This example uses a total station to measure the coordinates of three prisms.

[0167] 1. The total station first measures the coordinates of prism No. 1 at position 1, then measures prism No. 2 at position 2, and then measures the coordinates of prism No. 3 at position 3. The segmented Kalman filter prediction method is used to predict the coordinates of prism No. 1 and prism No. 2 when measuring prism No. 3. Then the predicted coordinates of prism 1 and prism 2 and the measured coordinates of prism 3 are combined to solve the position of the tunnel boring machine.

[0168] 2. The total station measures the coordinates of prism 1 at position 4. The segmented Kalman filter prediction method is used to predict the coordinates of prisms 2 and 3 when measuring prism 1. Then the predicted coordinates of prisms 2 and 3 and the measured coordinates of prism 1 are combined to form a set of equations to solve the position of the tunnel boring machine.

[0169] 3. The total station measures the coordinates of prism No. 2 at position 5. The segmented Kalman filter prediction method is used to predict the coordinates of prism No. 1 and prism No. 3 when measuring prism No. 2. Then the predicted coordinates of prism 1 and prism 3 and the measured coordinates of prism 2 are combined to form a set of equations to solve the position of the tunnel boring machine.

[0170] 4. Continue to the next measurement cycle.

[0171] 3. Evidence of the effects of the embodiments. The embodiments of the present invention have achieved some positive effects during the development or use process, and indeed have great advantages over the prior art. The following content is described in conjunction with the data, charts, etc. of the test process.

[0172] In order to verify the effect of the present invention, the simulation experiment is carried out as follows:

[0173] The sample data of three prisms and three attitude angles is simulated and generated, including a straight line segment, a transition curve segment and a circular curve segment. The straight line segment is 29m long, the transition curve segment is 50m long, the circular curve segment is 40m long, and the turning radius is 200m. The results of the existing scheme and the present invention are compared. Figure 5 Figure 6 .

[0174] It can be seen that the error of the existing solution is always large, especially in the curve section, the error gradually increases. However, the error of the solution of the present invention is smaller overall.

[0175] (1) In the existing scheme, the N coordinate deviation is about 0mm at the beginning when the speed is not high, but it quickly increases to 20-30mm; the E coordinate deviation is about 5mm in the straight section, and increases to 8-12mm after the curve section; the H coordinate deviation has been fluctuating between -4-5mm. The azimuth and pitch angles fluctuate between -0.2 and 0.2°, and the roll angle fluctuates between -0.15 and 0.15.

[0176] (2) In the solution of the present invention, the deviations of the N coordinate, E coordinate, and H coordinate are all less than 2 mm. The deviations of the azimuth and pitch angles fluctuate by about 0.05°, and the deviations of the roll angles are all less than 0.1°.

[0177] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. It can be understood by a person of ordinary skill in the art that the above-mentioned devices and methods can be implemented using computer executable instructions and / or contained in a processor control code, such as a carrier medium such as a disk, CD or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on the carrier medium. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0178] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with the technical field within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A method for measuring the posture of a roadheader, characterized in that: The method for measuring the posture of a roadheader comprises: After measuring prism 1 to prism n-1, the coordinates of prism 1 to prism n-1 when measuring prism n are predicted; the two attitude angles output by the angle sensor at this moment are read, and the predicted coordinates of prism 1 to prism n-1 and the measured coordinates of prism n are used to solve the posture of the tunnel boring machine; The method for measuring the posture of a roadheader comprises the following steps: Step 1: Use a total station to measure the coordinates of multiple prisms on the tunnel boring machine in sequence, and use an angle sensor installed on the tunnel boring machine to measure multiple attitude angles; Step 2: Use the segmented Kalman filter algorithm to predict the coordinates of multiple prisms at the same time; Step 3: Use the coordinate transformation model to establish the measurement equations and use the least squares method to solve the posture; The method for measuring the posture of a roadheader further comprises: n prisms and m attitude angle sensors are installed on the roadheader; the total station measures the coordinates of prisms 1 to n in sequence, and after completing the measurement of the nth prism, predicts the coordinates of prisms 1 to n-1 at the time of measuring prism n, and unifies the coordinates into the same coordinate system at the same time; the prediction algorithm uses the segmented Kalman filter algorithm for prediction, which sequentially matches the linearity of the design line where the roadheader is located, establishes the state equation, and fuses it with the observation value to perform Kalman filter prediction; Multiple prisms use 2 or more prisms; The angle sensor adopts an inclination sensor or a gyroscope sensor, and the attitude angle uses 2 attitude angles; The state equation is determined according to the line type of the design line segment where the roadheader is currently located, and is determined according to the straight line segment, the transition curve segment and the circular curve segment; The method for measuring the posture of a roadheader further comprises: (1) Constructing the equation of state 1) Linear equation of state X(k+1)=ΦX(k)+ΓW(k); X=[N E H dl v a] T ; 2) Easement curve state equation in, X=[NEH l dl va θ dθ β] T ; M 11 =cos(θ k )·cos(β k )·cos(α)-sin(θ k )·cos(β k )·sin(a); M 12 =-dl k ·sin(θ k )·cos(β k )·cos(α)-dl k ·cos(θ k )·cos(β k )·sin(a); M 13 =-dl k ·cos(θ k )·sin(β k )·cos(α)+dl k ·cos(θ k )·sin(β k )·sin(a); M 21 =cos(θ k )·cos(β k )·sin(α)+sin(θ k )·cos(β k )·cos(α); M 22 =-dl k ·sin(θ k )·cos(β k )·cos(α)+dl k ·cos(θ k )·cos(β k )·cos(α); M 23 =-dl k ·cos(θ k )·sin(β k )·cos(α)-dl k ·sin(θ k )·sin(β k )·cos(α); 3) Circular curve state equation The structure of circular curve is similar to that of transition curve, only the calculation of angle increment is different, so the formula is: M 31 ＝0； Among them, N is the north coordinate, E is the east coordinate, H is the elevation, dL is the cylinder increment, α is the azimuth of the designed route, T is the measurement period, β is the pitch angle, and L is the forward distance; the velocity v and acceleration a are obtained by measurement; (2) Constructing the observation equation The forward distance of the roadheader is measured by the cylinder stroke sensor, and the coordinates of the prism are measured by the total station. The stroke of the cylinder stroke sensor and the coordinates of the prism measured by the total station are used as the observed quantities. The prism coordinates measured by the total station and the cylinder stroke measured by the cylinder stroke sensor are used as observation values, and the observation equation is listed: Z=[N E H L] T ; (3) Forecast update 1) The straight line segment is directly predicted using Kalman filtering: P(k+1|k)=φ(k+1|k)P(k)φ T (k+1|k)+Q(k+1); K(k+1)=P(k+1|k)H T (k+1)[H(k+1)P(k+1|k)H T (k+1)+R(k+1)] -1 ; P(k+1)=[IK(k+1)H(k+1)]P(k+1|k); 2) For the transition curve and circular curve segments, due to the existence of nonlinear functions, the linearized model is predicted using the extended Kalman function. Then: P(k+1|k)=Φ(k+1|k)P(k)Φ T (k+1|k)+Q(k+1); K(k+1)=P(k+1|k)H T (k+1)[H(k+1)P(k+1|k)H T (k+1)+R(k+1)] -1 ; P(k+1)=[IK(k+1)H(k+1)]P(k+1|k).

2. The method for measuring the posture of a roadheader according to claim 1, characterized in that: The method for measuring the posture of a roadheader further comprises: The angle sensor measures two attitude angles of the roadheader, and according to the predicted prism group coordinates and attitude angles, a group of equations is established simultaneously; the least squares criterion is used as an estimation condition to find the optimal solution for error correction.

3. A tunnel boring machine posture measurement system using the tunnel boring machine posture measurement method according to any one of claims 1 to 2, characterized in that: The roadheader posture measurement system comprises: An attitude angle measurement module is used to sequentially measure the coordinates of multiple prisms on the tunnel boring machine using a total station, and to measure multiple attitude angles using an angle sensor installed on the tunnel boring machine; A prism coordinate prediction module is used to predict the coordinates of multiple prisms at the same time using a segmented Kalman filter algorithm; The posture measurement module is used to establish a measurement equation group using a coordinate transformation model and solve the posture using the least squares method.

4. A computer device, characterized in that: The computer device includes a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the tunnel boring machine posture measurement method as described in any one of claims 1 to 2.

5. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the processor executes the steps of the method for measuring the posture of a tunnel boring machine as claimed in any one of claims 1 to 2.

6. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the tunnel boring machine posture measurement system as described in claim 3.

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