High-precision measuring system for track construction based on total station

Abstract

The present application relates to the field of track measurement technology, and more particularly to a high-precision measurement system for track construction based on a total station, which comprises an acquisition module, an overrun determination module, an analysis module, an identification module, a calculation module, an adjustment module and an execution module. The present application uses multi-dimensional parameter joint analysis to identify preliminary overruns using an allowable deviation threshold, and then merges sections with relevant geometric features into measurement and control units through an analysis model to improve the aggregation of abnormal positioning. Subsequently, combined with the mutation characteristics, it distinguishes between linear anomalies and local deformation, and further through a threshold feedback mechanism that can be dynamically adjusted with the observation period, it realizes the adaptive evaluation transition of abnormal detection from static threshold judgment to the evolution of the line state, making the measurement results more accurately reflect the real deformation characteristics of the track, and effectively solving the problem of the difficulty in timely and accurate identification of small deviations in the track caused by sensor cumulative error and data response lag.

Description

Technical Field

[0001] This invention relates to the field of track measurement technology, and in particular to a high-precision measurement system for track construction based on a total station. Background Technology

[0002] With the rapid development of high-speed railway and urban rail transit construction, the requirements for track construction accuracy and operational safety are becoming increasingly stringent. Small deviations in track geometry can significantly affect train operation stability and passenger comfort. At the same time, the complex track structure, dynamic changes in the construction environment, and the accumulation of measurement errors during construction pose enormous challenges to the real-time monitoring and anomaly identification of track geometry.

[0003] Chinese Patent Application Publication No. CN103821054A discloses a track geometry state measurement system and method based on an INS and a total station combination. The system includes: a measurement unit, which includes a measurement device and a moving support; the measurement device includes a total station measurement system, an inertial measurement unit, an odometer, and a displacement sensor, which are mounted on the moving support; the total station measurement system includes a total station and a reflective surface, with the total station placed on or outside the moving support, and the reflective surface mounted on the moving support or placed on the top surface of the track rail.

[0004] Therefore, the track geometry measurement system based on the combination of INS and total station has the following problems: The system relies on the combination of INS and total station to measure track geometry. The cumulative error of inertial measurement and the data synchronization problem between various sensors may lead to a decrease in measurement accuracy, making it difficult to reflect small track deviations in a timely and accurate manner; The system mainly relies on moving supports to collect data along the track. The continuous response to changes in track state during the measurement process is limited, making it difficult to perform real-time and continuous dynamic monitoring of the rapidly changing track geometry during the construction phase, thus limiting the ability to quickly determine and intervene in potential over-limit sections. Summary of the Invention

[0005] To address this, the present invention provides a high-precision measurement system for track construction based on a total station, which overcomes the problem in the prior art that small track deviations are difficult to identify in a timely and accurate manner due to cumulative sensor errors and data response lag by using continuous high-precision dynamic measurement and multi-parameter joint analysis of the total station network.

[0006] To achieve the above objectives, the present invention provides a high-precision measurement system for track construction based on a total station, comprising:

[0007] The acquisition module is used to acquire in real time the coordinate sequence of each track segment to be measured in the coordinate system of each station within the total station network, the coordinate matching difference between adjacent stations, the relative azimuth of the track centerline, the track gauge, the horizontal superelevation, and the longitudinal smoothness of the track surface.

[0008] The over-limit determination module is used to determine several preliminary over-limit sections based on the coordinate deviation between the coordinate sequence and the preset reference axis and the preset allowable deviation threshold.

[0009] The analysis module is used to analyze several measurement and control sections based on a preset analysis model, according to the spatial correlation of the track gauge, the horizontal superelevation, and the coordinate deviation of the preliminary over-limit section.

[0010] The identification module is used to identify the measurement and control section as a linearly abnormal section or a locally deformed section based on the abrupt changes in the longitudinal smoothness of the track surface and the continuity of the relative azimuth angle of each measurement and control section.

[0011] The calculation module is used to calculate the linear smoothness index based on the coordinate sequence in each of the linear anomaly sections, and to calculate the local stability index based on the track gauge and the horizontal superelevation in each of the local deformation sections.

[0012] The adjustment module is used to adjust the preset allowable deviation threshold according to the distribution and evolution trend of the linear smoothness index and the local stability index within a preset observation period.

[0013] An execution module is used to output a measurement report based on the coordinate mismatch of the measurement and control section after adjusting the allowable deviation threshold.

[0014] Furthermore, the over-limit determination module is used to construct a multi-dimensional feature tensor from the coordinate sequence within a preset over-limit determination period in history and the coordinate deviation of the preset reference axis, and to standardize the feature tensor to obtain a standard feature tensor. It also performs independent component analysis on the standard feature tensor to extract independent feature components, maps the coordinate deviation at the current moment to the independent feature components to calculate the reconstruction error and the contribution of independent features, and determines several preliminary over-limit sections based on the reconstruction error, the contribution of independent features, and the preset allowable deviation threshold.

[0015] Furthermore, the over-limit determination module is used to determine that the track segment under test has a systematic over-limit when the reconstruction error is greater than the preset allowable deviation threshold and the independent feature contribution is less than or equal to the preset contribution threshold, and to mark the track segment under test as the preliminary over-limit section.

[0016] Furthermore, the analysis module is used to calculate the comprehensive change rate of the section based on the change gradient of the track gauge, the horizontal superelevation, and the coordinate deviation along the direction of the track centerline, and to perform curve fitting and smoothing on the comprehensive change rate based on the preset analysis model to obtain the section correlation parameters.

[0017] Furthermore, the parsing module is used to determine the preliminary over-limit section as the measurement and control section when the correlation parameter is greater than the preset correlation threshold, so as to parse out several measurement and control sections.

[0018] Furthermore, the identification module is used to perform wavelet packet transform on all the longitudinal smoothness of the track surface to extract specific frequency band energy as the feature index value of the abrupt change feature, and to calculate the standard deviation of the first-order difference value of all the relative azimuth angles to obtain the continuous index value of continuity, and to construct a two-dimensional feature vector based on the feature index value and the continuous index value, and to identify the linear abnormal section or local deformation section based on the two-dimensional feature vector.

[0019] Furthermore, the identification module is used to determine that the measurement and control section is the linear anomaly section when the Euclidean distance between the two-dimensional feature vector and the preset linear standard center point is less than or equal to the Euclidean distance between the two-dimensional feature vector and the preset local standard center point; and to determine that the measurement and control section is the local deformation section when the Euclidean distance between the two-dimensional feature vector and the preset linear standard center point is greater than the Euclidean distance between the two-dimensional feature vector and the preset local standard center point.

[0020] Furthermore, the calculation module is used to calculate the linear smoothness index based on the projection deviation of the coordinate sequence in each of the linear anomaly segments within a preset calculation time along the normal direction of the preset reference axis, and to calculate the local stability index based on the coordinated change rate of the gauge and the horizontal superelevation in each of the local deformation segments within a preset calculation time.

[0021] Furthermore, the adjustment module is used to calculate the mean and standard deviation of all the linear smoothness indices and all the local stability indices within the preset observation period, and to calculate an adjustment judgment value based on the mean of all the linear smoothness indices and the mean of all the local stability indices, and to adjust the preset allowable deviation threshold based on the mean and standard deviation of all the linear smoothness indices and all the local stability indices when the adjustment judgment value is less than the preset adjustment judgment threshold.

[0022] Furthermore, the execution module is used to calculate the average coordinate matching difference of the measurement and control section after adjusting the allowable deviation threshold, and to output the measurement report when the average coordinate matching difference is less than or equal to the preset matching difference threshold.

[0023] Compared with the prior art, the beneficial effect of the present invention is that, within the framework of the total station network, multiple geometric quantities such as track gauge, superelevation, coordinate deviation, relative azimuth, and track surface smoothness are analyzed in a spatially consistent manner, so that the judgment of track condition no longer depends on a single parameter, but is based on the inherent constraints between the quantities in the track structure: track gauge and superelevation together reflect the lateral attitude of the sleepers, coordinate deviation reflects the overall alignment of the line, longitudinal smoothness reveals the continuity of the track surface, and azimuth ensures the rationality of the directional extension of adjacent sections. The system first identifies preliminary exceedances using the permissible deviation threshold, then merges sections with relevant geometric features into measurement and control units through an analytical model, improving the aggregation degree of anomaly location. Subsequently, it distinguishes between linear anomalies (overall geometric deviation) and local deformations (local structural instability) by combining abrupt change characteristics, and further quantifies the degree of anomalies through smoothness index and local stability index, forming a threshold feedback mechanism that can be dynamically adjusted with the observation cycle. This realizes the transformation of anomaly detection from static threshold judgment to adaptive evaluation with the evolution of track status, making the measurement results more accurately reflect the true deformation characteristics of the track, significantly improving the automation and precision of track construction measurement and control, and effectively solving the problem that small track deviations are difficult to identify in a timely and accurate manner due to cumulative sensor errors and data response lag.

[0024] Furthermore, by constructing a multidimensional feature tensor from the historical coordinate sequence and the deviation from the reference axis, and through standardization and independent component analysis, the intrinsic correlation of multiple source parameters such as track gauge, superelevation, and coordinate deviation can be separated and quantified, and mutually independent change patterns can be extracted. At the same time, by measuring the degree of deviation of the current track state from the historical pattern through reconstruction error and feature contribution, systematic over-limit sections can be accurately identified, and sporadic measurement noise can be effectively distinguished from real geometric anomalies. This makes the determination of track geometric anomalies reflect both local parameter mutations and overall structural state changes, thereby significantly improving the accuracy and reliability of preliminary over-limit section identification.

[0025] Furthermore, by combining reconstruction error with independent feature contribution to determine systematic over-limit, this embodiment can effectively distinguish between overall track structural anomalies and local measurement fluctuations, so that the identification of preliminary over-limit sections reflects both the true deviation of track geometry and avoids misjudgment due to single-point noise. By utilizing the coordinated spatial variation law of track gauge, superelevation, and coordinate deviation, high-precision locking of abnormal sections can be achieved, improving the reliability and scientific nature of track construction quality control and early maintenance decisions.

[0026] Furthermore, by comprehensively analyzing the gradient changes in track gauge, superelevation, and coordinate deviation along the track centerline using the analytical module, the overall geometric fluctuation of each measurement and control section can be quantified. A preset analytical model is used to perform curve fitting and smoothing of the change trends, effectively filtering out measurement noise interference while preserving the actual geometric change characteristics of the track. This allows the section correlation parameters to reflect the coupling relationship between the sleeper's lateral attitude, the longitudinal elevation changes of the track, and the overall alignment offset, thereby improving the accuracy and stability of abnormal section identification and achieving a refined and continuous assessment of the track's geometric state.

[0027] Furthermore, by comparing the correlation parameters of the initial out-of-limit sections with preset correlation thresholds, the analysis module can automatically identify sections with high correlation to geometric fluctuations and classify them as measurement and control sections. This integrates the spatial variation characteristics of track gauge, superelevation, and coordinate deviation, so that the section division not only reflects the anomaly of a single quantity, but also reflects the mutual coupling and coordinated changes between various parameters. This ensures that the measurement and control sections cover the areas with the most significant changes in the overall geometric state, providing a reliable foundation for the accurate identification of subsequent linear anomalies and local deformations, while improving the aggregation and stability of anomaly detection.

[0028] Furthermore, by extracting specific frequency band energy through wavelet packet transform of the longitudinal smoothness of the track surface, it is possible to sensitively capture the abrupt changes in the longitudinal undulations of the track. At the same time, the standard deviation of the first-order difference of the relative azimuth angle is used to quantify the continuity of the track direction. The two-dimensional feature vector unifies the amplitude abrupt change and the continuity of direction, enabling the system to accurately distinguish between abnormal sections of overall linear deviation and deformation sections of local structural instability, thereby achieving refined identification and reliable quantification of track geometric anomalies.

[0029] Furthermore, by statistically analyzing and performing second-order difference processing on the projection deviation of the track coordinate sequence in the normal direction of the reference axis within the linear anomaly section, the smoothness of the overall track curve is quantified. At the same time, by combining the analysis of the coordinated changes in gauge and superelevation in the local deformation section, the coupling relationship between the track's lateral attitude and longitudinal continuity can be accurately reflected, thereby generating quantifiable linear smoothness index and local stability index. This enables the system to achieve an integrated evaluation of the overall geometric orientation and local structural stability when a single index is insufficient to comprehensively assess the track state, thus improving the sensitivity and accuracy of anomaly section identification.

[0030] Furthermore, by comparing the two-dimensional feature vector with the Euclidean distance between the standard center point of the track and the local standard center point, the system can accurately distinguish between the linear anomaly segment of the overall linear deviation and the local deformation segment of the local structural deformation based on the comprehensive difference in the longitudinal fluctuation amplitude and directional continuity of the track. This enables fine classification of different types of geometric anomalies, while ensuring that the judgment results are highly consistent with the actual change amplitude and spatial distribution characteristics of the track geometry, thereby improving the reliability and pertinence of anomaly segment identification.

[0031] Furthermore, by dynamically adjusting the preset allowable deviation threshold by combining the mean and standard deviation of the linear smoothness index and the local stability index, an adaptive response to fluctuations in track geometry is achieved. Specifically, when the local stability index deviates from the benchmark value or the standard deviation of the linear smoothness index increases abnormally, the threshold is automatically adjusted. This ensures that the system is neither overly sensitive to identify abnormal sections to avoid noise-induced misjudgments, nor overly sensitive to reflect the actual minute deformations of the track. This guarantees that the judgment results for track gauge, superelevation, and coordinate deviations are reasonable and reliable under the adjusted thresholds, effectively balancing monitoring sensitivity and data robustness, and improving the accuracy and practicality of measurement and control decisions.

[0032] Furthermore, by calculating the average coordinate coincidence difference of the newly divided control sections under the adjusted allowable deviation threshold, the overall degree of fit between the actual track geometry and the reference axis of each section can be quantified. When the average coordinate coincidence difference does not exceed the preset coincidence difference threshold, the system automatically generates a measurement report, summarizing the geometric deviation, smoothness index, and local stability index of each section, thereby achieving a comprehensive evaluation of the track construction or maintenance effect. This method fully utilizes the mutual constraints between parameters such as gauge, superelevation, and coordinate deviation to ensure that the division of control sections and threshold adjustment are verified in terms of spatial consistency, structural integrity, and directional continuity, thereby improving the reliability of measurement conclusions and their engineering guidance value. Attached Figure Description

[0033] Figure 1 This is a schematic diagram of the high-precision measurement system for track construction based on a total station, as described in this embodiment.

[0034] Figure 2 This embodiment provides a logic diagram for determining the initial out-of-limit section using the out-of-limit determination module.

[0035] Figure 3 This is the logic diagram for determining the control and measurement section in the parsing module of this embodiment;

[0036] Figure 4 This is a logic diagram for identifying linear abnormal sections or local deformation sections in this embodiment. Detailed Implementation

[0037] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0038] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0039] Please see Figure 1 As shown, this is a schematic diagram of a high-precision measurement system for track construction based on a total station, as described in this embodiment. This embodiment provides a high-precision measurement system for track construction based on a total station, comprising:

[0040] The acquisition module is used to acquire in real time the coordinate sequence of each track segment to be measured in the coordinate system of each station within the total station network, the coordinate matching difference between adjacent stations, the relative azimuth of the track centerline, the track gauge, the horizontal superelevation, and the longitudinal smoothness of the track surface.

[0041] An over-limit determination module, which is connected to the acquisition module, is used to determine several preliminary over-limit sections based on the coordinate deviation of the coordinate sequence and the preset reference axis and the preset allowable deviation threshold.

[0042] The analysis module is connected to the acquisition module and the over-limit determination module respectively, and is used to analyze several measurement and control sections based on a preset analysis model according to the spatial correlation of the track gauge, the horizontal superelevation and the coordinate deviation of the preliminary over-limit section.

[0043] The identification module is connected to the acquisition module and the analysis module respectively, and is used to identify the measurement and control section as a linear anomaly section or a local deformation section based on the abrupt change characteristics of the longitudinal smoothness of the track surface and the continuity of the relative azimuth angle of each measurement and control section.

[0044] The calculation module, which is connected to the acquisition module and the identification module respectively, is used to calculate the linear smoothness index based on the coordinate sequence in each of the linear anomaly sections, and to calculate the local stability index based on the track gauge and the horizontal superelevation in each of the local deformation sections.

[0045] An adjustment module, which is connected to the calculation module and the over-limit determination module respectively, is used to adjust the preset allowable deviation threshold according to the distribution and evolution trend of the linear smoothness index and the local stability index within a preset observation period;

[0046] An execution module, which is connected to the acquisition module and the parsing module respectively, is used to output a measurement report based on the coordinate matching difference of the measurement and control section after adjusting the allowable deviation threshold.

[0047] In this embodiment, the acquisition module performs continuous and high-precision dynamic measurements of the track geometry of the track construction section using a total station network. During construction, construction trains or surveyors set up stations along the track. At each station, the total station acquires the spatial three-dimensional coordinates of key measuring points on the track through angle and distance measurements, forming a coordinate sequence for each track segment in the coordinate system of each station. The coordinate matching difference between adjacent stations refers to the difference between the coordinates of measuring points obtained from different stations on the same track segment under test, used to evaluate the registration accuracy and data continuity between stations. The relative azimuth of the track centerline represents the change in direction of the line connecting adjacent measuring points along the track direction, used to describe the characteristics of the track curve; the track gauge is the lateral distance between the two rails; the superelevation is the elevation of the outer rail relative to the inner rail, used to control the mechanical conditions of the curve; the longitudinal smoothness of the track surface is used to quantify the longitudinal undulations of the track, and can be obtained through elevation difference and filtering processing. Through continuous observation with a total station and automatic data acquisition software, data from each station is transmitted to the central processing module in real time. Combined with coordinate system transformation, data registration, and noise filtering algorithms, high-precision track geometric parameters are automatically generated. This provides basic data for subsequent identification of over-limit sections, analysis of control sections, and stability analysis, enabling continuous, dynamic monitoring and quantitative evaluation of track geometric status during construction.

[0048] In this embodiment, the preset reference axis refers to the spatial reference curve of the ideal track centerline determined according to the track design drawings and construction specifications, serving as a benchmark for evaluating deviations in the actual track's geometric state. This axis is generated before construction using a 3D modeling method and mapped to the coordinate system of the total station network to ensure that the measurement data remains consistent with the design trajectory. The preset reference axis includes a continuous sequence of spatial points, describing the longitudinal elevation, lateral curve radius, and directional changes of the track. It is used to calculate the normal deviation, gauge deviation, and superelevation deviation of each measuring point relative to the ideal track, thus providing a unified reference framework for judging over-limit sections, analyzing alignment anomalies, and assessing local stability, ensuring the comparability and repeatability of measurement results.

[0049] In this embodiment, the measurement report is a comprehensive track geometry status assessment document generated based on the dynamic reference network and the results of geometric coupling analysis. It is automatically generated when the coordinate matching difference of the measurement and control section after the system confirms that the allowable deviation threshold is adjusted meets the preset accuracy requirements. The report fully records the spatial positioning information of each measurement and control section, the measured values ​​of track geometry parameters (including track gauge, superelevation, and longitudinal smoothness) and the deviation from the design reference axis, the calculation results of the linear smoothness index and local stability index, and their safety level classification in the preset evaluation system. By comparing the trends of multi-cycle data, it automatically identifies sections with significantly deteriorated geometry and generates a maintenance plan based on industry standards, including specific maintenance measures (such as coordinate adjustment, track alignment priority, and fastener inspection recommendations) and the degree of urgency. Finally, it is output in a structured PDF / A format with digital signature and timestamp, ensuring the complete traceability of measurement data to maintenance decisions and the engineering guidance value.

[0050] The preset allowable deviation threshold is a critical value used to judge the deviation of track geometric parameters from the design benchmark. It depends on the track design level, train operating speed, construction accuracy, and safety requirements, and is usually set between 1-5mm. In this embodiment, it is set to 3mm, which can take into account both early anomaly identification and measurement error tolerance, and ensure the reliability of the initial over-limit section judgment. The preset observation period is the time or measurement segment length used to calculate the alignment smoothness index and local stability index. It depends on the track segment length, train operating frequency, and track geometric state change rate, and is usually set between 1 day and 7 days. In this embodiment, it is set to 3 days, which can balance monitoring sensitivity and data stability, and ensure timely identification of abnormal sections.

[0051] By combining and analyzing multiple geometric quantities such as track gauge, superelevation, coordinate deviation, relative azimuth, and track surface smoothness in a spatially consistent manner within the framework of a total station network, track condition judgment no longer relies on a single parameter, but is based on the inherent constraints between these quantities within the track structure: track gauge and superelevation together reflect the lateral attitude of the sleepers, coordinate deviation reflects the overall alignment of the line, longitudinal smoothness reveals the continuity of the track surface, and azimuth ensures the rationality of directional extension between adjacent sections. The system first identifies preliminary exceedances using the permissible deviation threshold, then merges sections with relevant geometric features into measurement and control units through an analytical model, improving the aggregation degree of anomaly location. Subsequently, it distinguishes between linear anomalies (overall geometric deviation) and local deformations (local structural instability) by combining abrupt change characteristics, and further quantifies the degree of anomalies through smoothness index and local stability index, forming a threshold feedback mechanism that can be dynamically adjusted with the observation cycle. This realizes the transformation of anomaly detection from static threshold judgment to adaptive evaluation with the evolution of track status, making the measurement results more accurately reflect the true deformation characteristics of the track, significantly improving the automation and precision of track construction measurement and control, and effectively solving the problem that small track deviations are difficult to identify in a timely and accurate manner due to cumulative sensor errors and data response lag.

[0052] Specifically, the over-limit determination module is used to construct a multi-dimensional feature tensor from the coordinate sequence within a preset over-limit determination period in history and the coordinate deviation of the preset reference axis, and to standardize the feature tensor to obtain a standard feature tensor. It also performs independent component analysis on the standard feature tensor to extract independent feature components, maps the coordinate deviation at the current moment to the independent feature components to calculate the reconstruction error and the contribution of independent features, and determines several preliminary over-limit sections based on the reconstruction error, the contribution of independent features, and the preset allowable deviation threshold.

[0053] In this embodiment, the multidimensional feature tensor construction, standardization processing, and independent component analysis methods used by the over-limit determination module are existing mature data analysis technologies. They can stably extract the independent variation patterns of track geometric parameters, map and calculate the current coordinate deviation to reconstruct the error and feature contribution, thereby identifying the preliminary over-limit section. There is no need to go into excessive detail about the basic principles and calculation process of the analysis method.

[0054] By constructing a multidimensional feature tensor from the historical coordinate sequence and the deviation from the reference axis, and through standardization and independent component analysis, the intrinsic correlation of multiple source parameters such as track gauge, superelevation, and coordinate deviation can be separated and quantified, and mutually independent change patterns can be extracted. At the same time, the degree of deviation of the current track state from the historical pattern can be measured by reconstruction error and feature contribution. This enables the accurate identification of systematic over-limit sections and effectively distinguishes between occasional measurement noise and real geometric anomalies. The determination of track geometric anomalies reflects both local parameter mutations and overall structural state changes, thereby significantly improving the accuracy and reliability of preliminary over-limit section identification.

[0055] Please see Figure 2 As shown, this is the judgment logic diagram of the over-limit determination module in this embodiment for determining the preliminary over-limit section. In this embodiment, the over-limit determination module is used to determine that the track segment to be tested has a systematic over-limit when the reconstruction error is greater than the preset allowable deviation threshold and the independent feature contribution is less than or equal to the preset contribution threshold, and to mark the track segment to be tested as the preliminary over-limit section.

[0056] The preset contribution threshold is a reference value used to determine the contribution of independent feature components to the current coordinate deviation. It depends on the noise level, historical deformation amplitude, and track grade of the track measurement data. It is usually set between 0.05 and 0.30. In this embodiment, it is set to 0.15, which can distinguish between systematic over-limit and occasional measurement fluctuations, and ensure the accuracy and stability of anomaly judgment.

[0057] By combining reconstruction error with independent feature contribution to determine systematic over-limit, this embodiment can effectively distinguish between overall track structural anomalies and local measurement fluctuations. This allows the initial identification of over-limit sections to reflect the true deviation of track geometry while avoiding misjudgment due to single-point noise. By utilizing the coordinated spatial variation of track gauge, superelevation, and coordinate deviation, high-precision locking of abnormal sections can be achieved, improving the reliability and scientific nature of track construction quality control and early maintenance decisions.

[0058] Specifically, the analysis module is used to calculate the comprehensive change rate of the section based on the change gradient of the track gauge, the horizontal superelevation, and the coordinate deviation along the direction of the track centerline, and to perform curve fitting and smoothing on the comprehensive change rate based on the preset analysis model to obtain the section correlation parameters.

[0059] The calculation process for the comprehensive change rate of the section is as follows:

[0060] ,

[0061] Ri is the overall change rate of the section, a dimensionless scalar used to quantify the overall drastic change in the track geometry at that point; ∇Gi is the gradient of the i-th gauge change, calculated as the gauge change per unit arc length along the track centerline (unit: mm / m); ∇Gi is the gradient of the i-th superelevation change, calculated as the superelevation change per unit arc length along the track centerline (unit: mm / m); ∇Di is the gradient of the i-th coordinate deviation change, calculated as the change in the normal deviation of the measurement point relative to the preset reference axis per unit arc length along the track centerline (unit: mm / m); wg, wh, and wd are the gauge values, respectively. The preset weighting coefficients for horizontal superelevation and coordinate deviation are as follows: In this embodiment, the preset track gauge weighting coefficient depends on the degree of influence of track gauge changes on train safety and operational stability, the reliability of track gauge measurement (noise level), and the design sensitivity of the project. It is typically set between 0.30 and 0.60; in this embodiment, it is set to 0.45, which emphasizes the high sensitivity of track gauge changes to safety while also considering the discrimination ability of other quantities. The preset superelevation weighting coefficient depends on the sensitivity of the track curve radius and train speed to superelevation deviation, as well as the stability of superelevation measurement. It is typically set between 0.15 and 0.40; in this embodiment, it is set to 0.35, which balances the high... The high requirements for superelevation and fluctuations in on-site measurements; the preset coordinate deviation weighting coefficient corresponding to the coordinate deviation depends on the station registration accuracy, the reliability of the reference axis definition, and the degree of influence of the coordinate deviation on the alignment (curvature, tangential error). It is usually set between 0.10 and 0.40. In this embodiment, it is set to 0.2, which can reflect the importance of the coordinate deviation but will not be judged due to registration noise amplification. G0 is the preset allowable gauge variation rate, which depends on the track design level, train speed, and train operation safety requirements. It is usually set between 0.5 and 2 mm / m. In this embodiment, it is set to 1 mm / m, which can ensure that the gauge variation in the section is within the safe allowable range, while being sensitive to abnormal gauge changes. The system uses a total station to measure the coordinate deviation, which is determined by the total station's measurement accuracy, the density of the station network, and the accuracy of the reference axis. This is typically set between 0.1-1 mm / m, and in this embodiment, it is set to 0.5 mm / m. This effectively controls the impact of track curve superelevation changes on passenger comfort and driving safety, while also ensuring robustness in measurement noise control. The system also uses a coordinate deviation tolerance rate, which depends on the total station's measurement accuracy, the density of the station network, and the accuracy of the reference axis. This is typically set between 0.05-0.5 mm / m, and in this embodiment, it is set to 0.2 mm / m. This reflects the actual deviation of the track alignment from the reference axis while avoiding excessive influence of measurement noise on anomaly detection.

[0062] The process of performing curve fitting and smoothing on the comprehensive rate of change based on the preset analytical model to obtain the segment correlation parameters is as follows:

[0063] ;

[0064] Ri' represents the new sequence obtained by smoothing and fitting the sequence formed by the comprehensive change rate of the segments using a preset analytical model. In this embodiment, the preset analytical model adopts the Savitzky-Golay filter, which can smooth measurement noise while preserving the abrupt change characteristics of the track geometry, thereby improving the accuracy and robustness of identifying linear anomaly segments and local deformation segments. C is the segment correlation parameter, N is the total number of comprehensive change rates of segments, minR' is the minimum value of the comprehensive change rate of all segments, and maxR' is the maximum value of the comprehensive change rate of all segments. In this embodiment, the Savitzky-Golay filter is a mature digital filtering technology widely used in signal smoothing and noise suppression. It achieves data smoothing by performing polynomial fitting within a local sliding window, which can preserve the peak and abrupt change characteristics of the signal. Its principle, implementation method, and parameter selection have been fully verified in existing literature and engineering applications, and need not be elaborated in this embodiment.

[0065] By comprehensively analyzing the gradient changes in track gauge, superelevation, and coordinate deviation along the track centerline using the analytical module, the overall geometric fluctuation of each measurement and control section can be quantified. Furthermore, by using a preset analytical model to perform curve fitting and smoothing of the change trend, the interference of measurement noise is effectively filtered out, while retaining the actual geometric change characteristics of the track. This allows the section correlation parameters to reflect the coupling relationship between the sleeper's lateral attitude, the longitudinal elevation changes of the track, and the overall alignment deviation, thereby improving the accuracy and stability of abnormal section identification and achieving a refined and continuous assessment of the track's geometric state.

[0066] Please see Figure 3 As shown, it is the judgment logic diagram of the parsing module in this embodiment for determining the measurement and control section. In this embodiment, the parsing module is used to determine the preliminary over-limit section as the measurement and control section when the correlation parameter is greater than the preset correlation threshold, so as to parse out several measurement and control sections.

[0067] The preset correlation threshold is a reference value used to determine the correlation degree of the comprehensive change rate of the section. It depends on the natural fluctuation amplitude of the track geometric parameters, the measurement accuracy, and the construction tolerance requirements. It is usually set between 0.3 and 0.7. In this embodiment, it is set to 0.5, which can effectively distinguish between highly correlated measurement and control sections and normal fluctuation sections, and ensure the accuracy and stability of abnormal section identification.

[0068] By comparing the correlation parameters of the initial out-of-limit sections with preset correlation thresholds, the analysis module can automatically identify sections with high correlation to geometric fluctuations and classify them as measurement and control sections. It integrates the spatial variation characteristics of track gauge, superelevation, and coordinate deviation, so that the section division not only reflects the anomaly of a single quantity, but also reflects the mutual coupling and coordinated changes between various parameters. This ensures that the measurement and control sections cover the areas with the most significant changes in the overall geometric state, providing a reliable foundation for the accurate identification of subsequent linear anomalies and local deformations, while improving the aggregation and stability of anomaly detection.

[0069] Specifically, the identification module is used to perform wavelet packet transform on all the longitudinal smoothness of the track surface to extract specific frequency band energy as the feature index value of the abrupt change feature, and to calculate the standard deviation of the first difference value of all the relative azimuth angles to obtain the continuous index value of continuity, and to construct a two-dimensional feature vector based on the feature index value and the continuous index value, and to identify the linear abnormal section or local deformation section based on the two-dimensional feature vector.

[0070] By extracting specific frequency band energy through wavelet packet transform of the longitudinal smoothness of the track surface, the system can sensitively capture the abrupt changes in the longitudinal undulations of the track. At the same time, the standard deviation of the first-order difference of the relative azimuth angle is used to quantify the continuity of the track direction. The two-dimensional feature vector unifies the amplitude abrupt change and the direction continuity, enabling the system to accurately distinguish between abnormal sections of overall linear deviation and deformation sections of local structural instability, thereby achieving refined identification and reliable quantification of track geometric anomalies.

[0071] Please see Figure 4 As shown, this is a logic diagram for identifying linearly abnormal sections or locally deformed sections in this embodiment. In this embodiment, the identification module is used to determine that the measurement and control section is the linearly abnormal section when the Euclidean distance between the two-dimensional feature vector and the preset linear standard center point is less than or equal to the Euclidean distance between the two-dimensional feature vector and the preset local standard center point; and to determine that the measurement and control section is the locally deformed section when the Euclidean distance between the two-dimensional feature vector and the preset linear standard center point is greater than the Euclidean distance between the two-dimensional feature vector and the preset local standard center point.

[0072] In this embodiment, the preset alignment standard center point refers to a typical feature vector pre-defined in the two-dimensional feature space of the alignment anomaly section, which represents the idealized characteristic state of systematic and continuous deviation of the track alignment. The setting of this center point is based on big data analysis of historical alignment anomaly cases. Specifically, it is formed by collecting no less than 1,000 sets of manually confirmed typical alignment anomaly sections, the longitudinal smoothness change feature energy values ​​and relative azimuth continuity index of the track surface, forming a two-dimensional feature sample set. The K-means clustering algorithm is used to perform cluster analysis on this sample set, and the centroid of the densest sample distribution area is selected as the preset alignment standard center point. Its numerical range is usually: the longitudinal smoothness change feature energy value ranges between [0.15, 0.35], and the relative azimuth continuity index ranges between [0.08, 0.20]. In this embodiment, the preset local standard center point refers to a typical feature vector pre-defined in the two-dimensional feature space of the local deformation section, which represents the idealized characteristic state of local isolated deformation of the track. The establishment of this center point is based on statistical analysis of historical local deformation cases. It involves collecting no fewer than 800 sets of track surface longitudinal smoothness abrupt change characteristic energy values ​​and relative azimuth continuity indices from typical local deformation sections verified in the field. A Gaussian mixture model is used to model the probability density of the characteristic sample set, and the feature vector corresponding to the probability density peak is selected as the preset local standard center point. The numerical ranges are typically: the track surface longitudinal smoothness abrupt change characteristic energy value ranges between [0.45, 0.75], and the relative azimuth continuity index ranges between [0.25, 0.50]. The clustering effect of both center points is verified using the silhouette coefficient method to ensure they can effectively distinguish different types of track anomalies.

[0073] By comparing the two-dimensional feature vector with the Euclidean distance between the standard center point of the track and the local standard center point, the system can accurately distinguish between the overall track deviation anomaly segment and the local deformation segment of the local structural deformation based on the comprehensive difference in the longitudinal fluctuation amplitude and directional continuity of the track. This enables fine classification of different types of geometric anomalies, while ensuring that the judgment results are highly consistent with the actual change amplitude and spatial distribution characteristics of the track geometry, thus improving the reliability and pertinence of anomaly segment identification.

[0074] Specifically, the calculation module is used to calculate the linear smoothness index based on the projection deviation of the coordinate sequence in each of the linear anomaly sections within a preset calculation time along the normal direction of the preset reference axis, and to calculate the local stability index based on the coordinated change rate of the gauge and the horizontal superelevation in each of the local deformation sections within a preset calculation time.

[0075] The process of calculating the linear smoothness index based on the projection deviation of the coordinate sequence within each linear anomaly segment onto the normal direction of the preset reference axis is as follows:

[0076]

[0077] d i For the i-th projection deviation, σ d μ is the standard deviation of all projection biases. d The mean of all projection deviations, Δ 2 di is the second-order difference of the projection bias, ϵ is a small constant to prevent division by zero error, L is the linear smoothness exponent with a value range of [0, 1], and n is the total number of projection biases.

[0078] The process of calculating the local stability index based on the coordinated change rate of the track gauge and the horizontal superelevation in each of the aforementioned local deformation sections is as follows:

[0079]

[0080] S is the local stability index, CVg is the coefficient of variation of track gauge, CVg=σg / μg, σg is the standard deviation of all track gauges, μg is the mean of all track gauges, CVg is the coefficient of variation of all track gauges, CVh=σh / μh, σh is the standard deviation of all horizontal superelevation, μh is the mean of all horizontal superelevation, ρ is the Pearson correlation coefficient between all track gauges and all horizontal superelevation, and CVh is the coefficient of variation of all horizontal superelevation.

[0081] In this embodiment, the preset calculation time is the time window or track segment length used to statistically calculate the linear smoothness index and local stability index. It depends on the track construction speed, the spacing between monitoring stations, and the rate of change of track geometry. It is usually set between 6 hours and 2 days. In this embodiment, it is set to 1 day, which can reflect the changing trend of track geometry in a timely manner while ensuring the stability of index calculation.

[0082] By statistically analyzing and performing second-order difference processing on the projection deviation of the track coordinate sequence in the normal direction of the reference axis within the linear anomaly section, the smoothness of the overall track curve is quantified. At the same time, by combining the analysis of the coordinated changes in gauge and superelevation in the local deformation section, the coupling relationship between the track's lateral attitude and longitudinal continuity can be accurately reflected. This generates quantifiable linear smoothness index and local stability index, enabling the system to achieve an integrated evaluation of the overall geometric orientation and local structural stability when a single index is insufficient to comprehensively assess the track state, thereby improving the sensitivity and accuracy of anomaly section identification.

[0083] Specifically, the adjustment module is used to calculate the mean and standard deviation of all the linear smoothness indices and all the local stability indices within the preset observation period, and to calculate an adjustment judgment value based on the mean of all the linear smoothness indices and the mean of all the local stability indices, and to adjust the preset allowable deviation threshold based on the mean and standard deviation of all the linear smoothness indices and all the local stability indices when the adjustment judgment value is less than the preset adjustment judgment threshold.

[0084] Where T'=T×[1+k1×(μS-μS0) / μS0+k2×(σL-σL0) / σL0], T' is the adjusted preset allowable deviation threshold, T is the original preset allowable deviation threshold, k1 is the preset local adjustment coefficient, μS is the mean of all local stability indices, μS0 is the preset local stability benchmark value, k2 is the preset linearity adjustment coefficient, σL is the standard deviation of all linearity smoothness indices, and σL0 is the preset linearity benchmark value.

[0085] The preset local adjustment coefficient is a proportional coefficient used to control the influence of the local stability index on the allowable deviation threshold adjustment. It depends on the local deformation sensitivity of the track section and the maintenance strategy requirements, and is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.3, which can maintain threshold stability while responding quickly to local anomalies. The preset local stability benchmark value is a reference value used to measure the local structural stability of the track. It depends on the design track grade, construction accuracy, and train operation safety requirements, and is usually set between 0.7 and 0.95. In this embodiment, it is set to 0.85, which can provide a reasonable reference for local stability judgment and avoid misjudgment or omission. The alignment adjustment coefficient is a proportional coefficient used to control the influence of the alignment smoothness index on the adjustment of the allowable deviation threshold. It depends on the longitudinal continuity requirements of the track and the measurement noise level, and is usually set between 0.1 and 0.5. In this embodiment, it is set to 0.25, which can balance the sensitivity and stability of alignment fluctuations to threshold adjustment. The preset alignment reference value is a reference value used to evaluate the overall alignment continuity of the track. It depends on the track design curve radius, construction allowable deviation, and ride comfort requirements, and is usually set between 0.6 and 0.9. In this embodiment, it is set to 0.75, which can provide a reliable reference for the determination of alignment smoothness and make the identification of abnormal sections more accurate.

[0086] By dynamically adjusting the preset allowable deviation threshold by combining the mean and standard deviation of the linear smoothness index and the local stability index, an adaptive response to fluctuations in track geometry is achieved. Specifically, when the local stability index deviates from the benchmark value or the standard deviation of the linear smoothness index increases abnormally, the threshold is automatically adjusted. This ensures that the system is neither overly sensitive to abnormal sections to avoid noise-induced misjudgments, nor overly sensitive to small deformations of the track. Consequently, the judgment results for track gauge, superelevation, and coordinate deviations under the adjusted thresholds are reasonable and reliable, effectively balancing monitoring sensitivity and data robustness, and improving the accuracy and practicality of measurement and control decisions.

[0087] Specifically, the execution module is used to calculate the average coordinate matching difference of the measurement and control section after adjusting the allowable deviation threshold, and to output the measurement report when the average coordinate matching difference is less than or equal to the preset matching difference threshold.

[0088] In this embodiment, the average coordinate matching difference is calculated as follows:

[0089]

[0090] M δ δ represents the average coordinate matching difference, N' is the total number of newly determined control and measurement sections, and δ j Let be the coordinate matching difference of the j-th measurement and control section.

[0091] By calculating the average coordinate conformity difference of the newly subdivided control sections under the adjusted allowable deviation threshold, the overall degree of fit between the actual track geometry and the reference axis of each section can be quantified. When the average coordinate conformity difference does not exceed the preset conformity difference threshold, the system automatically generates a measurement report, summarizing the geometric deviation, smoothness index, and local stability index of each section, thereby achieving a comprehensive evaluation of the track construction or maintenance effect. This method fully utilizes the mutual constraints between parameters such as track gauge, superelevation, and coordinate deviation to ensure that the division of control sections and threshold adjustment are verified in terms of spatial consistency, structural integrity, and directional continuity, improving the reliability of measurement conclusions and their engineering guidance value.

[0092] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A surveying system for track construction based on a total station, characterized in that, include: The acquisition module is used to acquire in real time the coordinate sequence of each track segment to be measured in the coordinate system of each station within the total station network, the coordinate matching difference between adjacent stations, the relative azimuth of the track centerline, the track gauge, the horizontal superelevation, and the longitudinal smoothness of the track surface. The over-limit determination module is used to determine several preliminary over-limit sections based on the coordinate deviation between the coordinate sequence and the preset reference axis and the preset allowable deviation threshold. The analysis module is used to analyze several measurement and control sections based on a preset analysis model, according to the spatial correlation of the track gauge, the horizontal superelevation, and the coordinate deviation of the preliminary over-limit section. The identification module is used to identify the measurement and control section as a linearly abnormal section or a locally deformed section based on the abrupt changes in the longitudinal smoothness of the track surface and the continuity of the relative azimuth angle of each measurement and control section. The calculation module is used to calculate the linear smoothness index based on the coordinate sequence in each of the linear anomaly sections, and to calculate the local stability index based on the track gauge and the horizontal superelevation in each of the local deformation sections. The adjustment module is used to adjust the preset allowable deviation threshold according to the distribution and evolution trend of the linear smoothness index and the local stability index within a preset observation period. An execution module is used to output a measurement report based on the coordinate matching difference of the measurement and control section after adjusting the allowable deviation threshold; The analysis module is used to calculate the comprehensive change rate of the section based on the change gradient of the track gauge, the horizontal superelevation, and the coordinate deviation along the direction of the track centerline, and to perform curve fitting and smoothing on the comprehensive change rate based on the preset analysis model to obtain the section correlation parameters. The calculation module is used to calculate the linear smoothness index based on the projection deviation of the coordinate sequence in each linear anomaly segment within a preset calculation time along the normal direction of the preset reference axis, and to calculate the local stability index based on the coordinated change rate of the gauge and the horizontal superelevation in each local deformation segment within a preset calculation time.

2. The track construction surveying system based on a total station according to claim 1, characterized in that, The over-limit determination module is used to construct a multi-dimensional feature tensor from the coordinate sequence within a preset over-limit determination period in history and the coordinate deviation of the preset reference axis, and to standardize the feature tensor to obtain a standard feature tensor. It also performs independent component analysis on the standard feature tensor to extract independent feature components, maps the coordinate deviation at the current moment to the independent feature components to calculate the reconstruction error and the contribution of independent features, and determines several preliminary over-limit sections based on the reconstruction error, the contribution of independent features, and the preset allowable deviation threshold.

3. The track construction surveying system based on a total station according to claim 2, characterized in that, The over-limit determination module is used to determine that the track segment under test has a systematic over-limit when the reconstruction error is greater than the preset allowable deviation threshold and the independent feature contribution is less than or equal to the preset contribution threshold, and to mark the track segment under test as the preliminary over-limit section.

4. The track construction surveying system based on a total station according to claim 3, characterized in that, The parsing module is used to determine the preliminary over-limit section as the measurement and control section when the correlation parameter is greater than the preset correlation threshold, so as to parse out several measurement and control sections.

5. The track construction surveying system based on a total station according to claim 4, characterized in that, The identification module is used to perform wavelet packet transform on all the longitudinal smoothness of the track surface to extract specific frequency band energy as the feature index value of the abrupt change feature, and to calculate the standard deviation of the first difference value of all the relative azimuth angles to obtain the continuous index value of continuity, and to construct a two-dimensional feature vector based on the feature index value and the continuous index value, and to identify the linear abnormal section or local deformation section based on the two-dimensional feature vector.

6. The track construction surveying system based on a total station according to claim 5, characterized in that, The identification module is used to determine that the measurement and control section is the linear anomaly section when the Euclidean distance between the two-dimensional feature vector and the preset linear standard center point is less than or equal to the Euclidean distance between the two-dimensional feature vector and the preset local standard center point; and to determine that the measurement and control section is the local deformation section when the Euclidean distance between the two-dimensional feature vector and the preset linear standard center point is greater than the Euclidean distance between the two-dimensional feature vector and the preset local standard center point.

7. The track construction surveying system based on a total station according to claim 6, characterized in that, The adjustment module is used to calculate the mean and standard deviation of all linear smoothness indices and all local stability indices within the preset observation period, and to calculate an adjustment judgment value based on the mean of all linear smoothness indices and the mean of all local stability indices, and to adjust the preset allowable deviation threshold based on the mean and standard deviation of all linear smoothness indices and all local stability indices when the adjustment judgment value is less than the preset adjustment judgment threshold.

8. The track construction surveying system based on a total station according to claim 7, characterized in that, The execution module is used to calculate the average coordinate matching difference of the measurement and control section after adjusting the allowable deviation threshold, and to output the measurement report when the average coordinate matching difference is less than or equal to the preset matching difference threshold.

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