A straddle carrier factory positioning system

Abstract

The present application discloses a straddle carrier in-plant positioning system, which relates to the technical field of positioning system, including a radar signal detection module to obtain a first signal set and a second signal set; a signal preliminary classification module to filter out an abnormal signal set and a normal signal set from the second signal set; a normal signal selection module to filter out a reference data set to be analyzed from a normal signal data set; a reference signal extraction module to combine and process the normal signal data in the reference data set to be analyzed to obtain a normal signal group set to be analyzed, and filter out a reference verification signal data set from the reference signal data set to be analyzed; a compensation difference analysis module to determine the compensation difference of the environmental impact signal loss; a signal abnormal misjudgment analysis module to determine the misjudged abnormal signal and the confirmed abnormal signal; and a position coordinate positioning module to evaluate the position coordinates of the straddle carrier. The present invention provides a straddle carrier in-plant positioning system, which displays data in different forms of comparison.

Description

Technical Field

[0001] The present application relates to the technical field of positioning systems, and in particular to a positioning system for a straddle carrier in a factory building. Background Art

[0002] Through the real-time positioning system, enterprises can achieve real-time and continuous tracking of factory equipment, AGVs (automatic guided vehicles), personnel, workpieces, materials, etc., generate trajectory roadmaps, and send positioning data to the upper-level software system. In dangerous areas or specific environments, the real-time positioning system can provide early warning and post-disaster rescue support, thereby reducing the risk of safety accidents. In general, the positioning system of the transport vehicle in the factory is not only of great significance for improving production efficiency, reducing costs, and ensuring safety, but also one of the key factors in promoting the digital transformation and intelligent upgrading of the manufacturing industry.

[0003] In traditional technology, the signal data detected by the lidar is only denoised and filtered to improve the data quality, without further analysis of whether there are any misjudgments in the detected signal data, which leads to large errors in the final indoor space graphics and reduces the efficiency of the entire positioning processing. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present application provides a straddle carrier in-plant positioning system.

[0005] In the first aspect, the present application provides a straddle carrier in-plant positioning system, which adopts the following technical solution:

[0006] A straddle carrier in-plant positioning system, comprising:

[0007] A radar signal detection module, used to obtain a first signal set and a second signal set of a 360° rotating single-line laser radar at a first moment and a second moment;

[0008] A signal preliminary classification module, used for screening out an abnormal signal set and a normal signal set from the second signal set according to a difference data set compared between the first signal set and the second signal set;

[0009] A normal signal selection module is used to select a reference data set to be analyzed from the normal signal data set according to the interval data between every two abnormal signal data in the abnormal signal set;

[0010] A reference signal extraction module, used for combining and processing the normal signal data in the reference data set to be analyzed to obtain a normal signal group set to be analyzed, and screening out a reference verification signal data set from the reference signal data set to be analyzed;

[0011] A compensation difference analysis module is used to perform difference processing on the data in the normal signal group to be analyzed after averaging to obtain a first difference set, perform difference processing on the data in the reference verification signal data group to obtain a second difference set, and compare the first difference set and the second difference set with a preset difference determination interval value to determine a compensation difference of the environmental impact signal loss;

[0012] A signal abnormal misjudgment analysis module is used to compensate for the compensation difference of the environmental impact signal loss for all signals in the abnormal signal data set to obtain a compensated signal set, and to judge misjudged abnormal signals and confirmed abnormal signals based on a comparison process of a third difference set obtained by comparing the compensated signal set with the first signal set and a preset difference judgment interval value;

[0013] The position coordinate positioning module is used to re-acquire the third signal set according to the confirmed abnormal signal, fit the position of the factory wall according to the third signal set, the first signal set and the second signal set, obtain the posture and angle information of the current IMU to evaluate the zero point coordinates of the IMU, and evaluate the position coordinates of the straddle carrier according to the factory wall position and the zero point coordinates.

[0014] Preferably, all signals detected by a 360° rotating single-line laser radar at a preset first moment are acquired, and all first signals are output;

[0015] Acquire all signals detected by the 360° rotating single-line laser radar at a preset second moment, output all second signals, and the strength of all second signals is greater than that of all first signals;

[0016] All the first signals and all the second signals are filtered and denoised to obtain a processed first signal set and a processed second signal set.

[0017] Preferably, the first signal set and the second signal set are compared in a one-to-one correspondence to obtain a difference data set;

[0018] A difference threshold is preset, and an abnormal signal data set corresponding to data whose difference data set is greater than the preset difference threshold is screened out from the second signal set;

[0019] A normal signal data set corresponding to data whose difference data set is less than or equal to a preset difference threshold is screened out from the second signal set.

[0020] Preferably, the position interval between every two abnormal signal data in the abnormal signal data set is evaluated, and the interval data set is output;

[0021] A preset reference interval judgment value is used to filter out the interval data set to be processed, which is smaller than the preset reference interval judgment value;

[0022] According to the interval data to be processed, normal signal data located between abnormal signal data belonging to the interval data to be processed are removed from the normal signal data set, and a reference signal data set to be analyzed is output.

[0023] Preferably, the normal signal data located between every two abnormal signal data in the reference signal data set to be analyzed is taken as a group of data to be analyzed, and a normal signal group set to be analyzed is output;

[0024] The maximum interval is extracted from the interval data set. According to the maximum interval, the normal signal data between the abnormal signal data with the maximum interval in the reference signal data set to be analyzed are used as a group of reference verification signal data, and the reference verification signal data group is output.

[0025] Preferably, the difference data sets to which each normal signal group to be analyzed belongs in the normal signal group set to be analyzed are averaged to obtain a first average difference set;

[0026] Performing difference statistics between respective average differences in the first average difference set to obtain a first difference set;

[0027] A preset difference determination interval value is set, and when the first difference sets are all within the preset difference determination interval value, the first average difference set is further averaged to obtain a pre-verified average difference value;

[0028] averaging the difference data sets to which the normal signal data in each reference verification signal data set belong to obtain a second average difference;

[0029] Perform one-to-one difference statistics on the second average difference and the first average difference set to obtain a second difference set;

[0030] When the second difference sets are all within the preset difference determination interval value, the pre-verified average difference value is determined to be the compensation difference value for the environmental impact signal loss.

[0031] Preferably, the pre-verified average difference and all signals in the abnormal signal data set are respectively compensated to obtain a compensated signal set;

[0032] Performing a one-to-one comparison of the difference values ​​between the compensation signal set and the first signal set to obtain a third difference set;

[0033] Determine the abnormal signal data corresponding to the difference in the third difference set that is within the preset difference determination interval value as a misjudged abnormal signal;

[0034] The abnormal signal data corresponding to the differences in the third difference set that are outside the preset difference determination interval value are determined as confirmed abnormal signals.

[0035] Preferably, according to the confirmed abnormal signal, all third signals detected by the 360° rotating single-line laser radar at different positions and at a preset third moment are obtained, and all the third signals are filtered and denoised to obtain a processed third signal set, and all the third signals are re-collected from the confirmed abnormal signal;

[0036] Comprehensively processing the third signal set, the first signal set and the second signal set to obtain a comprehensive signal set, and fitting the position of the factory wall according to the comprehensive signal set;

[0037] Obtaining the current IMU's attitude and angle information, and evaluating the IMU's zero point coordinates based on the current IMU's attitude and angle information;

[0038] The position coordinates of the straddle carrier are evaluated based on the position of the plant wall and the zero point coordinates.

[0039] Compared with the prior art, the present invention has the following characteristics and beneficial effects:

[0040] 1. By collecting the lidar signals at the first moment and the second moment, and comparing the signal data sets collected at these two moments, it is easy to preliminarily judge which signal data are most likely to be abnormal and which signal data are normal, and further process the abnormal signal data preliminarily judged, so as to improve the accuracy of radar signal analysis, and avoid the large error in the fitting result of the factory wall position caused by the traditional technology of directly evaluating the factory wall position after the signal data collected by the lidar is subjected to unified signal denoising.

[0041] 2. By evaluating and processing the interval between every two abnormal signal data positions, the normal signal data preliminarily determined above can be orderly combined and processed. In order to reduce the interference between normal signal data with smaller effects, some normal signal data are eliminated to facilitate the subsequent analysis of large amounts of data and improve the efficiency and reliability of the entire signal processing work. Furthermore, by using a part of the normal signal data as a reference verification signal data group, the above-mentioned normal signal group to be analyzed can be further verified to reduce the probability of misjudgment.

[0042] 3. The compensation signal set is obtained by analyzing and evaluating the reference verification signal data set and the normal signal data set to be analyzed, and the compensation signal set is compensated for the abnormal signal data set in a one-to-one correspondence. Then, the false abnormal signal judgment and confirmed abnormal signal judgment are performed on the abnormal signal data set initially judged above, so as to achieve the secondary abnormal judgment verification of the abnormal signal data set, and the corresponding radar signal re-detection is performed on the confirmed abnormal signal. Finally, the first signal set and the second signal set detected above are comprehensively processed to evaluate the position of the factory wall. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flowchart of a straddle carrier in-plant positioning system mainly embodied in this embodiment;

[0044] Figure 2 This embodiment mainly embodies waveform data collected by a laser radar of a straddle carrier factory building positioning system;

[0045] Figure 3 This is waveform data with an IMU angle of 0° for a positioning system in a straddle carrier plant, which is mainly reflected in this embodiment.

[0046] Figure numerals: S1, radar signal detection module; S2, signal preliminary classification module; S3, normal signal selection module; S4, reference signal extraction module; S5, compensation difference analysis module; S6, signal abnormality misjudgment analysis module; S7, position coordinate positioning module. DETAILED DESCRIPTION

[0047] The present invention is further described in detail below in conjunction with the following examples.

[0048] Reference Figure 1 , a straddle carrier in-plant positioning system, comprises a radar signal detection module, a signal preliminary classification module, a normal signal selection module, a reference signal extraction module, a compensation difference analysis module, a signal abnormal misjudgment analysis module and a position coordinate positioning module.

[0049] The radar signal detection module is used to obtain the first signal set and the second signal set of the 360° rotating single-line laser radar at the first moment and the second moment.

[0050] Among them, the specific implementation method of the radar signal detection module is as follows:

[0051] Acquire all signals detected by a 360° rotating single-line laser radar at a preset first moment, and output all first signals.

[0052] All signals detected by the 360° rotating single-line laser radar at a preset second moment are acquired, and all second signals are output, wherein the intensities of all second signals are greater than those of all first signals.

[0053] All the first signals and all the second signals are filtered and denoised to obtain a processed first signal set and a processed second signal set.

[0054] The signal preliminary classification module is used to screen out abnormal signal sets and normal signal sets from the second signal set based on a difference data set compared between the first signal set and the second signal set.

[0055] Among them, the specific implementation method of the signal preliminary classification module is as follows:

[0056] The signal difference values ​​of the first signal set and the second signal set are compared one by one to obtain a difference data set.

[0057] A difference threshold is preset, and an abnormal signal data set corresponding to data whose difference data set is greater than the preset difference threshold is screened out from the second signal set.

[0058] A normal signal data set corresponding to data whose difference data set is less than or equal to a preset difference threshold is screened out from the second signal set.

[0059] Specifically, the first signal set (if a part of it is taken as an example: the signals at the twenty positions a, b, c, d, e, f, g, h to t, and a and t form a cycle) and the second signal set (if it includes the signals at the twenty positions A, B, C, D, E, F, G, H to T, these twenty positions correspond to the above positions A, B, C, D, E to T, and the difference is the detected signal waveform data) are smoothed to obtain waveform data, and the steps of smoothing to obtain waveform data include: denoising, model selection and decomposition, parameter initialization and optimization, waveform reconstruction, visualization and analysis. Difference data set (such as Figure 2 , calculate the difference between the A signal waveform data: MdB and the a signal waveform data: mdB: (Mm)dB if it is equal to m1, where M and m are both numerical values, and so on, perform the same steps on the remaining four signal waveform data collected at the two moments, if they are respectively obtained as: m2, m3, m4, m5, m6, m7, m8 to m20), preset difference threshold (if it is between Nn), abnormal signal data set (if m2 and m5 are both greater than the range of Nn, then the corresponding B, E, I, N are abnormal signal data), normal signal data set (then the remaining A, C, D, FH, JM, OT are all less than or equal to the range of Nn, then they are all normal signal data).

[0060] The normal signal selection module is used to select a reference data set to be analyzed from the normal signal data set according to the interval data between every two abnormal signal data in the abnormal signal set.

[0061] Among them, the specific implementation method of the normal signal selection module is as follows:

[0062] The position interval between every two abnormal signal data in the abnormal signal data set is evaluated, and the interval data set is output.

[0063] A reference interval judgment value is preset, and the interval data to be processed that is less than the preset reference interval judgment value is screened out from the interval data set.

[0064] According to the interval data to be processed, normal signal data located between the abnormal signal data belonging to the interval data to be processed are removed from the normal signal data set, and a reference signal data set to be analyzed is output.

[0065] Specifically, such as the interval data set (such as the interval between B and E is: 2 / 20=0.1, which is 10%, there are two normal signal data between B and E, then the ratio of the number of normal signal data between the two abnormal signal data to the total number of signal data is the interval), the preset reference interval judgment value (if it is 15%), the interval data to be processed (such as the interval between B and E is 10%), and the reference signal data set to be analyzed (C and D are eliminated, because the difference in signal change amplitude between signal data with more adjacent positions is not much different, the subsequent difference analysis processing is more accurate, and the signal loss values ​​of signal data with adjacent positions are relatively stable due to environmental influences. At this time, the remaining A, FH, JM, and OT are the reference signal data sets to be analyzed).

[0066] The reference signal extraction module is used to combine the normal signal data in the reference data set to be analyzed to obtain a normal signal group set to be analyzed, and to filter out a reference verification signal data set from the reference signal data set to be analyzed.

[0067] The specific implementation of the reference signal extraction module is as follows:

[0068] The normal signal data between every two abnormal signal data in the reference signal data set to be analyzed is taken as a group of data to be analyzed, and a normal signal group set to be analyzed is output.

[0069] The maximum interval is extracted from the interval data set. According to the maximum interval, the normal signal data between the abnormal signal data with the maximum interval in the reference signal data set to be analyzed are used as a group of reference verification signal data, and the reference verification signal data group is output.

[0070] Specifically, for the normal signal group to be analyzed (such as F, G, H as a group, and JM as a group), the maximum interval (i.e. OA, because O and A form a cycle, the maximum interval is: 7 / 20=0.35, i.e. 35%), the normal signal data between the abnormal signal data with the maximum interval in the reference signal data set to be analyzed are used as a set of reference verification signal data (i.e. OA, as a verification reference comparison object for the subsequent analysis results of the two groups of signal data F, G, H as a group, and JM as a group, because the difference in signal change amplitude between signal data with a large number of adjacent positions is relatively stable, that is, the detection accuracy is higher).

[0071] The compensation difference analysis module is used to perform difference processing on the data in the normal signal group to be analyzed after averaging the average value to obtain a first difference set, perform difference processing on the data in the reference verification signal data group to obtain a second difference set, and compare the first difference set and the second difference set with the preset difference judgment interval value to determine the compensation difference of the environmental impact signal loss.

[0072] Among them, the specific execution method of the compensation difference analysis module is as follows:

[0073] The difference data sets to which each of the normal signal groups to be analyzed belongs in the normal signal group to be analyzed are averaged to obtain a first average difference set.

[0074] The first difference set is obtained by performing difference statistics between the respective average differences in the first average difference set.

[0075] A preset difference determination interval value is set. When the first difference set is within the preset difference determination interval value, the first average difference set is averaged to obtain a pre-verified average difference value.

[0076] The second average difference is obtained by averaging the difference data sets to which the normal signal data in the reference verification signal data set belong.

[0077] The second average difference and the first average difference set are statistically analyzed in one-to-one correspondence to obtain a second difference set.

[0078] When the second difference sets are all within the preset difference determination interval value, the pre-verified average difference value is determined to be the compensation difference value for the environmental impact signal loss.

[0079] Specifically, such as the first average difference set (i.e., if the average value between m6, m7, and m8 is X, the average value between m10-m13 is Y), the first difference set (i.e., if the difference between X and Y is y6), the preset difference determination interval value (if it is y5-y8), the pre-verified average difference (y6 is within the y5-y8 interval value, then y6 is the pre-verified average difference: the preliminary evaluation calculation is the compensation difference for the environmental impact signal loss, and in order to improve the accuracy, further verification is performed later), the second average difference (i.e., averaging all the differences between m15-m1 corresponding to OA Calculation and processing, if it is Z), the second difference set (that is, calculate the difference between Z and Y, if it is y7), when the second difference set is within the preset difference judgment interval value, then the pre-verified average difference is determined to be the compensation difference of the environmental impact signal loss (y7 is in the y5-y8 interval value, indicating that the signal loss value of OA is very close to the signal loss value of m6-m8 and m10-m13, and they are all relatively stable, then it can be judged that it is the signal value loss caused by the environment, because if the signal value loss is caused by other factors, then the difference in the signal loss value between them is relatively large).

[0080] The signal anomaly misjudgment analysis module is used to compensate for the compensation difference of the environmental impact signal loss for all signals in the abnormal signal data set to obtain a compensated signal set, and to judge the misjudged abnormal signals and confirmed abnormal signals based on the comparison processing of the third difference set obtained by comparing the compensated signal set with the first signal set and the preset difference judgment interval value.

[0081] Among them, the specific execution method of the signal abnormality misjudgment analysis module is as follows:

[0082] The pre-verified average difference and all signals in the abnormal signal data set are compensated to obtain a compensated signal set.

[0083] A one-to-one difference comparison is performed between the compensation signal set and the first signal set to obtain a third difference set.

[0084] The abnormal signal data corresponding to the differences in the third difference set that are within the preset difference determination interval value are determined as misjudged abnormal signals.

[0085] The abnormal signal data corresponding to the differences in the third difference set that are outside the preset difference determination interval value are determined as confirmed abnormal signals.

[0086] Specifically, such as the compensation signal set (such as superimposing the compensation values ​​of y6 with the abnormal signal data of B, E, I, and N respectively, if the B signal data is B1, then the compensated signal data is B1+y6, and the same applies to E, I, and N), the third difference set (that is, performing corresponding signal difference calculations between the compensated abnormal signal data and the normal signal data of b, e, i, and n, and if the results are y4, y6, y7, and y4 respectively), misjudged abnormal signals (it can be judged that E and I are misjudged abnormal signal data, but are actually normal signal data), confirmed abnormal signals (then B and N are confirmed abnormal signal data, indicating that in addition to the signal value loss caused by environmental influences, it is also affected by signal value loss such as multipath effects).

[0087] The position coordinate positioning module is used to re-acquire the third signal set according to the confirmed abnormal signal, fit the position of the factory wall according to the third signal set, the first signal set and the second signal set, obtain the posture and angle information of the current IMU to evaluate the zero point coordinates of the IMU, and evaluate the position coordinates of the straddle carrier according to the factory wall position and the zero point coordinates.

[0088] Among them, the specific execution method of the position coordinate positioning module is as follows:

[0089] According to the confirmed abnormal signal, all third signals detected by the 360° rotating single-line laser radar at different positions and at a preset third moment are obtained, and all third signals are filtered and denoised to obtain a processed third signal set. All third signals are re-collected of the confirmed abnormal signal.

[0090] The third signal set, the first signal set and the second signal set are comprehensively processed to obtain a comprehensive signal set, and the position of the factory wall is fitted according to the comprehensive signal set.

[0091] Get the current IMU's attitude and angle information, and evaluate the IMU's zero point coordinates based on the current IMU's attitude and angle information.

[0092] The position coordinates of the straddle carrier are evaluated based on the position of the factory wall and the zero point coordinates.

[0093] Specifically, such as re-acquiring the third signal set (i.e., making changes to the B and N positions that are different from the positions where the laser radar signal is detected at the second moment, so as to reduce the great possibility of the multipath effect, and the detection moment is the third moment, because the single-line laser radar can only send and receive one signal at a time), the third signal set (i.e., performing the same signal removal process as the first signal set and the second signal set to improve the signal quality), fitting the position of the factory wall (i.e., replacing the signal data of some positions in the first signal set and the second signal set with the third signal set, and selecting high-quality signal data, and passing the finally selected comprehensive signal set through the variable component Gaussian mixture model algorithm: This algorithm assumes that the waveform data obeys a mixed Gaussian distribution, and establishes an ideal waveform model to control the degree of waveform decomposition. Use Bayesian theorem and Markov chain Monte Carlo method to simulate the posterior probability model, determine the number of waveform decompositions and complete the waveform decomposition. To fit the position of the factory wall), fuse the position of the factory wall and the zero point coordinates, that is, use multi-sensor data fusion technology. This fusion can be achieved through Kalman filter or other advanced data fusion algorithms. Finally, the position coordinates of the straddle carrier are obtained. It should be noted that when the IMU angle is 0°, the distance to the left of the radar is directly calculated as the X coordinate of the world coordinate system, and the distance to the bottom of the radar is the Y coordinate of the world coordinate system; when the IMU angle is between 0-360°, assuming it is set to ang°, the data collected by the radar needs to be rotated in the corresponding direction by ang°. After rotation, it can be calculated according to the calculation method of 0° above, such as Figure 3 .

[0094] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A straddle carrier in-plant positioning system, characterized in that: include: A radar signal detection module, used to obtain a first signal set and a second signal set of a 360° rotating single-line laser radar at a first moment and a second moment; A signal preliminary classification module, used for screening out an abnormal signal set and a normal signal set from the second signal set according to a difference data set compared between the first signal set and the second signal set; A normal signal selection module is used to select a reference data set to be analyzed from the normal signal data set according to the interval data between every two abnormal signal data in the abnormal signal set; A reference signal extraction module, used for combining and processing the normal signal data in the reference data set to be analyzed to obtain a normal signal group set to be analyzed, and screening out a reference verification signal data set from the reference signal data set to be analyzed; A compensation difference analysis module is used to perform difference processing on the data in the normal signal group to be analyzed after averaging to obtain a first difference set, perform difference processing on the data in the reference verification signal data group to obtain a second difference set, and compare the first difference set and the second difference set with a preset difference determination interval value to determine a compensation difference of the environmental impact signal loss; A signal abnormal misjudgment analysis module is used to compensate for the compensation difference of the environmental impact signal loss for all signals in the abnormal signal data set to obtain a compensated signal set, and to judge misjudged abnormal signals and confirmed abnormal signals based on a comparison process of a third difference set obtained by comparing the compensated signal set with the first signal set and a preset difference judgment interval value; The position coordinate positioning module is used to re-acquire the third signal set according to the confirmed abnormal signal, fit the position of the factory wall according to the third signal set, the first signal set and the second signal set, obtain the posture and angle information of the current IMU to evaluate the zero point coordinates of the IMU, and evaluate the position coordinates of the straddle carrier according to the factory wall position and the zero point coordinates.

2. The in-plant positioning system for straddle carriers according to claim 1, characterized in that: The specific implementation method of the radar signal detection module is as follows: Acquire all signals detected by a 360° rotating single-line laser radar at a preset first moment, and output all first signals; Acquire all signals detected by the 360° rotating single-line laser radar at a preset second moment, output all second signals, and the strength of all second signals is greater than that of all first signals; All the first signals and all the second signals are filtered and denoised to obtain a processed first signal set and a processed second signal set.

3. The in-plant positioning system for straddle carrier according to claim 1, characterized in that: The specific implementation method of the signal preliminary classification module is as follows: Comparing the signal difference values ​​of the first signal set and the second signal set in a one-to-one correspondence to obtain a difference data set; A difference threshold is preset, and an abnormal signal data set corresponding to data whose difference data set is greater than the preset difference threshold is screened out from the second signal set; A normal signal data set corresponding to data whose difference data set is less than or equal to a preset difference threshold is screened out from the second signal set.

4. The in-plant positioning system for straddle carriers according to claim 1, characterized in that: The specific implementation method of the normal signal selection module is as follows: Evaluate the positional interval between every two abnormal signal data in the abnormal signal data set, and output the interval data set; A preset reference interval judgment value is used to filter out the interval data set to be processed, which is smaller than the preset reference interval judgment value; According to the interval data to be processed, normal signal data located between abnormal signal data belonging to the interval data to be processed are removed from the normal signal data set, and a reference signal data set to be analyzed is output.

5. The in-plant positioning system for straddle carriers according to claim 1, characterized in that: The specific implementation method of the reference signal extraction module is as follows: Taking the normal signal data between every two abnormal signal data in the reference signal data set to be analyzed as a group of data to be analyzed, and outputting a normal signal group set to be analyzed; The maximum interval is extracted from the interval data set. According to the maximum interval, the normal signal data between the abnormal signal data with the maximum interval in the reference signal data set to be analyzed are used as a group of reference verification signal data, and the reference verification signal data group is output.

6. The in-plant positioning system for straddle carriers according to claim 1, characterized in that: The specific implementation method of the compensation difference analysis module is as follows: averaging the difference data sets to which the respective normal signal groups to be analyzed belong in the normal signal group sets to be analyzed to obtain a first average difference set; Performing difference statistics between respective average differences in the first average difference set to obtain a first difference set; A preset difference determination interval value is set, and when the first difference sets are all within the preset difference determination interval value, the first average difference set is further averaged to obtain a pre-verified average difference value; averaging the difference data sets to which the normal signal data in each reference verification signal data set belong to obtain a second average difference; Perform one-to-one difference statistics on the second average difference and the first average difference set to obtain a second difference set; When the second difference sets are all within the preset difference determination interval value, the pre-verified average difference value is determined to be the compensation difference value for the environmental impact signal loss.

7. The in-plant positioning system for straddle carriers according to claim 6, characterized in that: The specific implementation method of the signal abnormality misjudgment analysis module is as follows: Performing compensation processing on the pre-verified average difference and all signals in the abnormal signal data set to obtain a compensated signal set; Performing a one-to-one comparison of the difference values ​​between the compensation signal set and the first signal set to obtain a third difference set; Determine the abnormal signal data corresponding to the difference in the third difference set that is within the preset difference determination interval value as a misjudged abnormal signal; The abnormal signal data corresponding to the differences in the third difference set that are outside the preset difference determination interval value are determined as confirmed abnormal signals.

8. The in-plant positioning system for straddle carriers according to claim 1, characterized in that: The specific implementation method of the position coordinate positioning module is as follows: According to the confirmed abnormal signal, all third signals detected by the 360° rotating single-line laser radar at different positions and at a preset third moment are obtained, and all the third signals are filtered and denoised to obtain a processed third signal set, where all the third signals are re-collected from the confirmed abnormal signal; Comprehensively processing the third signal set, the first signal set and the second signal set to obtain a comprehensive signal set, and fitting the position of the factory wall according to the comprehensive signal set; Obtaining the current IMU's attitude and angle information, and evaluating the IMU's zero point coordinates based on the current IMU's attitude and angle information; The position coordinates of the straddle carrier are evaluated based on the position of the plant wall and the zero point coordinates.

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