An apparatus for automatically detecting a device foundation

Abstract

The application relates to the technical field of automation control, and discloses a device foundation automatic detection system which comprises a multidimensional sensor distribution module, a benchmark calibration trigger setting module, a device running environment sensing module, a machine tool column angle eccentricity monitoring module and an abnormality early warning automatic response module. A multilevel distributed sensor array is constructed on a machine tool column angle, and a distributed reflective optical fiber is implanted. A laser tracking target is installed on a non-stress area of a machine tool base, a dynamic calibration system is formed together with a top reflective prism of the column angle, calibration is automatically triggered according to a preset time rule, the strain distribution and eccentric displacement of the machine tool column body are sensed in real time, monitoring data are output, and a stepwise power cut-off logic is adopted to gradually brake the machine tool when an abnormality occurs, to start a fault isolation mechanism to lock the shaft system movement authority, so that omnibearing and automatic detection and abnormal response of the device foundation are realized.

Description

Technical Field

[0001] This invention relates to the field of automation control technology, and more specifically to an automatic detection system for equipment foundations. Background Technology

[0002] In modern high-end manufacturing, the operational precision of core processing equipment directly determines product quality. The stability of the basic structure of processing equipment has become a key factor affecting processing quality. However, some processing equipment, such as machine tools, are prone to degradation of the geometric precision of their basic structure due to multiple factors during long-term operation. High-speed rotation of the spindle, changes in cutting force, and friction of the guide rails can cause continuous vibration, resulting in slight displacements in key parts such as column corners. Environmental factors such as temperature fluctuations and slight settlement of the foundation further aggravate the deformation of the basic structure. If these dynamic changes are not monitored in time, they will gradually accumulate into significant eccentric displacements or strains, eventually causing processing errors to exceed the allowable range.

[0003] With the advancement of intelligent manufacturing, flexible production lines require equipment to have continuous operation capabilities. The traditional "stop-and-test - manual calibration" model has become a bottleneck for production capacity. Against this backdrop, there is an urgent need to build a detection system that can sense the basic structural status of processing equipment in real time, automatically analyze the trend of accuracy degradation, and dynamically link with the processing process. This system can solve the shortcomings of traditional methods in terms of timeliness, accuracy, and integration, and provide full-cycle accuracy assurance for high-end manufacturing.

[0004] Although some machine tools are equipped with simple condition monitoring functions, these are mostly limited to the independent monitoring of a single parameter and lack correlation analysis of the overall condition of the basic structure. For example, while traditional closed-loop control systems can correct shaft system errors through position feedback, they cannot identify structural deformation caused by column corner eccentricity; some early warning systems rely solely on static threshold judgments, ignoring the dynamic coupling relationship between "eccentric displacement-strain distribution-environmental parameters," making it difficult to achieve accurate early warning. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides an automatic equipment foundation detection system to solve the problems existing in the background art.

[0006] This invention provides the following technical solution: an automatic equipment detection system, comprising: a multi-dimensional sensor deployment module, a benchmark verification trigger setting module, an equipment operating environment perception module, a machine tool column angle eccentricity monitoring module, and an abnormality early warning automatic response module;

[0007] The multi-dimensional sensor deployment module constructs a multi-level distributed sensor array at the corner of the machine tool column, and embeds distributed reflective optical fibers along the axis inside the corner of the column.

[0008] The reference verification trigger setting module installs a laser tracking target in the non-stressed area of ​​the machine tool base, which, together with the reflecting prism at the top of the column corner, forms a dynamic calibration system and automatically triggers reference verification based on a preset time rule.

[0009] The equipment operating environment sensing module senses the strain distribution of the machine tool column in real time based on distributed reflective optical fiber during machine tool operation, obtains the operating environment sensing results, and outputs them to the abnormal early warning automatic response module.

[0010] The machine tool column angle eccentricity monitoring module monitors the machine tool column angle parameters in real time based on a multi-level distributed sensor array during machine tool operation, analyzes the machine tool column angle eccentricity displacement, and outputs it to the abnormal early warning automatic response module.

[0011] The abnormal warning automatic response module, based on the stepped power cut-off logic, performs progressive braking control on the machine tool when an abnormal warning is issued, and activates the fault isolation mechanism to lock the axis movement authority.

[0012] Preferably, the multi-dimensional sensor deployment module includes a sensor deployment layer and a reflective fiber optic implantation layer, as detailed below:

[0013] The sensor deployment layer constructs a multi-level distributed sensor array at the corner of the machine tool column to obtain key sections of the column corner. The key sections represent three key sections: the bottom, middle, and top of the column corner. The sensor array is uniformly arranged along the circumferential direction at different height levels of the machine tool column corner. Each level contains multiple high-precision displacement sensors and tilt sensors for real-time monitoring of the machine tool column corner parameters.

[0014] The reflected fiber implantation layer has distributed reflected fibers implanted along the axis inside the column corner, and monitoring points are set at fixed intervals to sense the strain distribution of the column in real time.

[0015] Preferably, the specific contents of the benchmark verification trigger setting module are as follows:

[0016] A laser tracking target is installed in the non-stressed area of ​​the machine tool base, forming a dynamic calibration system with a reflecting prism at the top of the column corner. The laser tracking target continuously emits a laser beam to the reflecting prism, receives the reflected light, and captures the real-time position of the prism. The real-time position is compared with the initial reference position parameters of the machine tool. If the comparison result shows that the real-time position is inconsistent with the initial reference position of the machine tool, it indicates that the machine tool position has deviated.

[0017] The system automatically triggers benchmark verification based on preset time rules. When the benchmark verification result shows that the machine tool position has deviated, the system automatically adjusts the emission angle of the laser tracking target and the receiving angle of the reflecting prism to dynamically calibrate the machine tool position.

[0018] Preferably, the specific contents of the device operating environment sensing module are as follows:

[0019] The distributed reflective optical fiber has a built-in optical transmitter and receiver. During the operation of the machine tool, the optical transmitter continuously emits laser signals of a specific wavelength into the optical fiber, and the receiver collects the reflected light signals in real time and converts the reflected light signals into electrical signals.

[0020] The electrical signal represents the strain value of each optical fiber monitoring point, and the strain value represents the axial strain and shear strain of each optical fiber monitoring point.

[0021] Based on the strain values ​​at each fiber optic monitoring point, the strain distribution gradient and strain change rate are analyzed, and the strain values, strain distribution gradient and strain change rate at each fiber optic monitoring point are integrated to generate a strain distribution heat map and change curve of the machine tool column.

[0022] Analyze machine tool stress risk: Based on the strain value distribution in the thermogram, if the strain value at the fiber optic monitoring point exceeds the preset stress threshold, it indicates that the area where the monitoring point is located is under excessive stress. If the difference between the maximum and minimum strain distribution gradients exceeds the preset distribution threshold, it indicates that the stress is uneven in different parts of the column. In this case, it indicates that the machine tool is under stress risk. Analyze machine tool deformation risk: If the strain change rate exceeds the preset rate threshold, it indicates that the machine tool column is at risk of deformation. The analysis results are then output to the abnormal warning automatic response module.

[0023] Preferably, the specific contents of the machine tool column angle eccentricity monitoring module are as follows:

[0024] Each level of displacement sensor is used to capture the linear displacement of the machine tool column corner in the horizontal direction along the X and Y axes, while each level of tilt sensor is used to monitor the tilt angle of the machine tool column corner around the vertical axis, namely the tilt angle around the X axis and the tilt angle around the Y axis. The vertical distance between each monitoring level is preset, namely the distance from the bottom to the middle and the distance from the middle to the top.

[0025] Using the center position of the column corner at the initial installation of the machine tool as a reference, the sensors at each level collect the real-time displacement data of the machine tool column corner in the X-axis and Y-axis directions, which are recorded as the displacement deviations of the bottom, middle and top in the X-axis and Y-axis directions;

[0026] The displacement data is corrected based on the tilt angle. Taking the bottom level as the reference, the theoretical displacements of the middle and top caused by the tilt are calculated, including: the theoretical displacement in the Y direction caused by the tilt of the middle around the X-axis, the theoretical displacement in the X direction caused by the tilt of the middle around the Y-axis, the theoretical displacement in the Y direction caused by the tilt of the top around the X-axis, and the theoretical displacement in the X direction caused by the tilt of the top around the Y-axis.

[0027] The corrected actual displacement deviations of the middle and top are obtained by subtracting the theoretical displacements of the middle and top due to tilt from the displacement deviations of the middle and top on the X and Y axes.

[0028] The analysis calculates the difference between the actual displacement deviation in the middle and the bottom, as well as the difference between the actual displacement deviation at the top and the bottom. If the difference is less than or equal to the preset judgment threshold, the machine tool column angle is judged to be in a normal state. Otherwise, the machine tool column angle is judged to be eccentric, and the analysis results are output to the abnormal warning automatic response module.

[0029] Preferably, the specific contents of the abnormality early warning automatic response module are as follows:

[0030] The system receives the machine tool column corner eccentricity judgment results and the equipment operating environment perception results. When it is determined that the machine tool column corner is eccentric, it issues an early warning message based on the heat map and change curve in the equipment operating environment perception results, combined with the machine tool stress risk and deformation risk: if the equipment operating environment perception module shows that the machine tool has stress risk or the machine tool column has deformation risk, a first-level early warning message is issued; if the equipment operating environment perception module shows that the machine tool has stress risk and the machine tool column has deformation risk, a second-level early warning message is issued.

[0031] The abnormal warning automatic response module uses a stepped power cut-off logic to perform progressive braking control on the machine tool when an abnormal warning occurs. In the first-level warning, a speed adjustment command is issued through the PLC interface of the machine tool spindle drive system to gradually reduce the spindle speed. At the same time, the feed system is linked to reduce the feed speed to reduce the additional stress under eccentric conditions. If the warning is upgraded to the second-level warning, a cut-off command is immediately sent to the axis power control unit to forcibly disconnect the servo motor power through the relay group. At the same time, the axis locking device is triggered to lock the axis movement authority instantly. After the power is cut off, the column corner position and strain status are continuously monitored. The axis lock can only be released and the power supply restored after the operator inputs an authorization command and confirms that the risk has been eliminated.

[0032] The technical effects and advantages of this invention are as follows:

[0033] This invention, by incorporating a multi-dimensional sensor deployment module, a benchmark verification trigger setting module, an equipment operating environment perception module, a machine tool column corner eccentricity monitoring module, and an abnormal early warning automatic response module, captures in real time the minute displacements, eccentricities, and strain changes of the machine tool foundation structure caused by dynamic interference factors. It performs dynamic coupling analysis of "eccentric displacement-strain distribution-environmental parameters" to achieve an assessment of the overall state of the foundation structure, thereby more accurately identifying structural deformation and other problems and improving the effectiveness of early warning.

[0034] The dynamic calibration system, composed of a laser tracking target and a reflecting prism, ensures the accuracy of the machine tool position and avoids monitoring errors caused by machine tool position deviation, further improving the accuracy and reliability of the system. In addition, the preset time rules automatically trigger the benchmark verification function, realizing continuous monitoring and dynamic adjustment of the machine tool position, ensuring the stability of the machine tool during operation.

[0035] Breaking through the time and space limitations of traditional detection methods, it can perform dynamic and uninterrupted monitoring, covering key parts such as column corners and bases, comprehensively grasping the status changes of machine tools during operation, capturing instantaneous precision fluctuations, completing data processing and early warning judgment in a short time, timely identifying potential risks, and buying time for subsequent adjustments and maintenance. Through automated detection and precise early warning, it reduces unnecessary manual inspections and blind maintenance, thereby lowering labor and maintenance costs. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the structure of an automatic detection system for equipment foundations. Detailed Implementation

[0037] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The automatic detection system for equipment foundations involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] like Figure 1 As shown, the present invention provides an automatic equipment detection system, including: a multi-dimensional sensor deployment module, a benchmark verification trigger setting module, an equipment operating environment perception module, a machine tool column angle eccentricity monitoring module, and an abnormality early warning automatic response module;

[0039] The multi-dimensional sensor deployment module constructs a multi-level distributed sensor array at the corner of the machine tool column, and embeds distributed reflective optical fibers along the axis inside the corner of the column.

[0040] The reference verification trigger setting module installs a laser tracking target in the non-stressed area of ​​the machine tool base, which, together with the reflecting prism at the top of the column corner, forms a dynamic calibration system and automatically triggers reference verification based on a preset time rule.

[0041] The equipment operating environment sensing module senses the strain distribution of the machine tool column in real time based on distributed reflective optical fiber during machine tool operation, obtains the operating environment sensing results, and outputs them to the abnormal early warning automatic response module.

[0042] The machine tool column angle eccentricity monitoring module monitors the machine tool column angle parameters in real time based on a multi-level distributed sensor array during machine tool operation, analyzes the machine tool column angle eccentricity displacement, and outputs it to the abnormal early warning automatic response module.

[0043] The abnormal warning automatic response module, based on the stepped power cut-off logic, performs progressive braking control on the machine tool when an abnormal warning is issued, and activates the fault isolation mechanism to lock the axis movement authority.

[0044] In this embodiment, it should be specifically noted that the multi-dimensional sensor deployment module includes a sensor deployment layer and a reflective fiber optic implantation layer, as detailed below:

[0045] The sensor deployment layer constructs a multi-level distributed sensor array at the corner of the machine tool column to obtain key sections of the column corner. The key sections represent three key sections: the bottom, middle, and top of the column corner. The sensor array is uniformly arranged along the circumferential direction at different height levels of the machine tool column corner. Each level contains multiple high-precision displacement sensors and tilt sensors for real-time monitoring of the machine tool column corner parameters.

[0046] The reflected fiber implantation layer has distributed reflected fibers implanted along the axis inside the column corner. Monitoring points are set at fixed intervals to sense the strain distribution of the column in real time. The fixed interval means that a monitoring point is generated every 0.5 meters.

[0047] In this embodiment, it should be specifically explained that the specific content of the benchmark verification trigger setting module is as follows:

[0048] A laser tracking target is installed in the non-stressed area of ​​the machine tool base, forming a dynamic calibration system with a reflecting prism at the top of the column corner. The laser tracking target continuously emits a laser beam to the reflecting prism, receives the reflected light, and captures the real-time position of the prism. The real-time position is compared with the initial reference position parameters of the machine tool. If the comparison result shows that the real-time position is inconsistent with the initial reference position of the machine tool, it indicates that the machine tool position has deviated.

[0049] The system automatically triggers benchmark verification based on preset time rules. When the benchmark verification result shows that the machine tool position has deviated, the system automatically adjusts the emission angle of the laser tracking target and the receiving angle of the reflecting prism to dynamically calibrate the machine tool position.

[0050] Regarding the composition and installation of the dynamic calibration system, the installation position of the laser tracking target is carefully selected. The non-stressed area of ​​the machine tool base can minimize the positional interference of the target caused by the deformation of the machine tool during operation, ensuring that the target is always in a relatively stable state and providing a reliable reference point for calibration. The reflecting prism at the top of the column corner serves as a dynamic monitoring point, providing real-time feedback of position information as the machine tool operates.

[0051] The specific operating mechanism of automatically triggering benchmark verification based on preset time rules requires operators to set reasonable time parameters in the module according to the machine tool's usage frequency, machining accuracy requirements, and past operating data.

[0052] In this embodiment, it should be specifically explained that the specific content of the device operating environment perception module is as follows:

[0053] The distributed reflective optical fiber has a built-in optical transmitter and receiver. During the operation of the machine tool, the optical transmitter continuously emits laser signals of a specific wavelength into the optical fiber, and the receiver collects the reflected light signals in real time and converts the reflected light signals into electrical signals.

[0054] The electrical signal represents the strain value of each fiber optic monitoring point. The strain value represents the axial strain and shear strain of each fiber optic monitoring point. The axial strain reflects the degree of deformation of the column in the tensile or compressive direction, while the shear strain reflects the relative displacement deformation of the column in the direction parallel to the cross section.

[0055] Based on the strain values ​​at each fiber optic monitoring point, the strain distribution gradient and strain change rate are analyzed. The strain distribution gradient represents the ratio of the difference between the strain values ​​of two adjacent points to the straight-line distance between the two adjacent points, and the strain change rate represents the ratio of the difference between the strain values ​​at the current moment and the previous moment to the time interval. The strain values, strain distribution gradient, and strain change rate of each fiber optic monitoring point are integrated to generate a strain distribution heat map and change curve of the machine tool column.

[0056] Analyze machine tool stress risk: Based on the strain value distribution in the thermogram, if the strain value at the fiber optic monitoring point exceeds the preset stress threshold, it indicates that the area where the monitoring point is located is under excessive stress. If the difference between the maximum and minimum strain distribution gradients exceeds the preset distribution threshold, it indicates that the stress is uneven in different parts of the column. In this case, it indicates that the machine tool is under stress risk. Analyze machine tool deformation risk: If the strain change rate exceeds the preset rate threshold, it indicates that the machine tool column is at risk of deformation. The analysis results are then output to the abnormal warning automatic response module.

[0057] In this embodiment, it should be specifically explained that the specific contents of the machine tool column angle eccentricity monitoring module are as follows:

[0058] Displacement sensors at each level are used to capture the linear displacement of the machine tool column angle in the horizontal direction along the X and Y axes, while tilt sensors at each level are used to monitor the tilt angle of the machine tool column angle about the vertical axis, namely the tilt angle about the X-axis and the tilt angle about the Y-axis, denoted as bottom. Central ,top Preset the vertical distance between each monitoring level, i.e., the distance from the bottom to the middle. and the distance from the middle to the top ;

[0059] Using the initial column corner center position of the machine tool as a reference, sensors at each level collect real-time displacement data of the machine tool column corner in the X and Y axes. These data represent the displacement deviations of the bottom, middle, and top sections in the X and Y axes, denoted as the bottom section. Central ,top ;

[0060] Since the tilt of the column corners causes a correlation in the horizontal displacement of different levels, the displacement data is corrected according to the tilt angle. Taking the bottom level as the benchmark, the theoretical displacements of the middle and top caused by the tilt are calculated, including: the theoretical displacement of the middle level around the X-axis, the theoretical displacement of the middle level around the Y-axis, the theoretical displacement of the top level around the X-axis, and the theoretical displacement of the top level around the Y-axis.

[0061] The theoretical displacement in the Y direction caused by the tilt of the middle section around the X-axis is the distance from the bottom to the middle section. Inclination angle of the middle part around the X-axis The product of the tangents, the theoretical X-direction displacement caused by the tilt of the middle part around the Y-axis is the distance from the bottom to the middle. Inclination angle of the middle part around the Y-axis The product of the tangents, the theoretical Y-direction displacement caused by the tilt of the top around the X-axis is the distance from the bottom to the top. Inclination angle of the top around the X-axis The product of the tangents, the theoretical X-direction displacement caused by the top tilting around the Y-axis is the distance from the bottom to the top. Inclination angle of the top around the Y-axis The product of the tangent values;

[0062] The corrected actual displacement deviations of the middle and top are obtained by subtracting the theoretical displacements of the middle and top due to tilt from the displacement deviations of the middle and top on the X and Y axes.

[0063] The analysis calculates the difference between the actual displacement deviation in the middle and the bottom, as well as the difference between the actual displacement deviation at the top and the bottom. If the difference is less than or equal to the preset judgment threshold, the machine tool column angle is judged to be in a normal state. Otherwise, the machine tool column angle is judged to be eccentric, and the analysis results are output to the abnormal warning automatic response module.

[0064] In this embodiment, it should be specifically explained that the specific content of the abnormal warning automatic response module is as follows:

[0065] The system receives the machine tool column corner eccentricity judgment results and the equipment operating environment perception results. When it is determined that the machine tool column corner is eccentric, it issues an early warning message based on the heat map and change curve in the equipment operating environment perception results, combined with the machine tool stress risk and deformation risk: if the equipment operating environment perception module shows that the machine tool has stress risk or the machine tool column has deformation risk, a first-level early warning message is issued; if the equipment operating environment perception module shows that the machine tool has stress risk and the machine tool column has deformation risk, a second-level early warning message is issued.

[0066] The abnormal warning automatic response module uses a stepped power cut-off logic to perform progressive braking control on the machine tool when an abnormal warning occurs. In the first-level warning, a speed adjustment command is issued through the PLC interface of the machine tool spindle drive system to gradually reduce the spindle speed. At the same time, the feed system is linked to reduce the feed speed to reduce the additional stress under eccentric conditions. If the warning is upgraded to the second-level warning, a cut-off command is immediately sent to the axis power control unit to forcibly disconnect the servo motor power through the relay group. At the same time, the axis locking device is triggered to lock the axis movement authority instantly. After the power is cut off, the column corner position and strain status are continuously monitored. The axis lock can only be released and the power supply restored after the operator inputs an authorization command and confirms that the risk has been eliminated.

[0067] In this embodiment, it should be specifically noted that the main difference between this embodiment and the prior art is that this embodiment uses a multi-dimensional sensor deployment module, a benchmark verification trigger setting module, an equipment operating environment perception module, a machine tool column corner eccentricity monitoring module, and an abnormal early warning automatic response module to capture in real time the minute displacement, eccentricity, and strain changes of the machine tool foundation structure caused by dynamic interference factors. It performs dynamic coupling analysis of "eccentric displacement-strain distribution-environmental parameters" to achieve an assessment of the overall state of the foundation structure, thereby more accurately identifying structural deformation and other problems and improving the effectiveness of early warning.

[0068] The dynamic calibration system, composed of a laser tracking target and a reflecting prism, ensures the accuracy of the machine tool position and avoids monitoring errors caused by machine tool position deviation, further improving the accuracy and reliability of the system. In addition, the preset time rules automatically trigger the benchmark verification function, realizing continuous monitoring and dynamic adjustment of the machine tool position, ensuring the stability of the machine tool during operation.

[0069] Breaking through the time and space limitations of traditional detection methods, it can perform dynamic and uninterrupted monitoring, covering key parts such as column corners and bases, comprehensively grasping the status changes of machine tools during operation, capturing instantaneous precision fluctuations, completing data processing and early warning judgment in a short time, timely identifying potential risks, and buying time for subsequent adjustments and maintenance. Through automated detection and precise early warning, it reduces unnecessary manual inspections and blind maintenance, thereby lowering labor and maintenance costs.

[0070] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0071] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An automatic equipment foundation detection system, characterized in that: include: Multi-dimensional sensor deployment module, benchmark verification trigger setting module, equipment operating environment perception module, machine tool column corner eccentricity monitoring module, and abnormal early warning automatic response module; The multi-dimensional sensor deployment module constructs a multi-level distributed sensor array at the corner of the machine tool column, and embeds distributed reflective optical fibers along the axis inside the corner of the column. The sensor deployment layer constructs a multi-level distributed sensor array at the corner of the machine tool column to obtain key sections of the column corner. The key sections represent three key sections: the bottom, middle, and top of the column corner. The sensor array is uniformly arranged along the circumferential direction at different height levels of the machine tool column corner. Each level contains multiple high-precision displacement sensors and tilt sensors for real-time monitoring of the machine tool column corner parameters. The reflected fiber implantation layer has distributed reflected fibers implanted along the axis inside the column corner, and monitoring points are set at fixed intervals to sense the strain distribution of the column in real time. The reference verification trigger setting module installs a laser tracking target in the non-stressed area of ​​the machine tool base, which, together with the reflecting prism at the top of the column corner, forms a dynamic calibration system and automatically triggers reference verification based on a preset time rule. A laser tracking target is installed in the non-stressed area of ​​the machine tool base, forming a dynamic calibration system with a reflecting prism at the top of the column corner. The laser tracking target continuously emits a laser beam to the reflecting prism, receives the reflected light, and captures the real-time position of the prism. The real-time position is compared with the initial reference position parameters of the machine tool. If the comparison result shows that the real-time position is inconsistent with the initial reference position of the machine tool, it indicates that the machine tool position has deviated. The system automatically triggers benchmark verification based on preset time rules. When the benchmark verification result shows that the machine tool position has deviated, the system automatically adjusts the emission angle of the laser tracking target and the receiving angle of the reflecting prism to dynamically calibrate the machine tool position. The equipment operating environment sensing module senses the strain distribution of the machine tool column in real time based on distributed reflective optical fiber during machine tool operation, obtains the operating environment sensing results, and outputs them to the abnormal early warning automatic response module. The machine tool column angle eccentricity monitoring module monitors the machine tool column angle parameters in real time based on a multi-level distributed sensor array during machine tool operation, analyzes the machine tool column angle eccentricity displacement, and outputs it to the abnormal early warning automatic response module. The abnormal warning automatic response module, based on the stepped power cut-off logic, performs progressive braking control on the machine tool when an abnormal warning is issued, and activates the fault isolation mechanism to lock the axis movement authority.

2. The automatic equipment foundation detection system according to claim 1, characterized in that: The specific contents of the device operating environment perception module are as follows: The distributed reflective optical fiber has a built-in optical transmitter and receiver. During the operation of the machine tool, the optical transmitter continuously emits laser signals of a specific wavelength into the optical fiber, and the receiver collects the reflected light signals in real time and converts the reflected light signals into electrical signals. The electrical signal represents the strain value of each optical fiber monitoring point, and the strain value represents the axial strain and shear strain of each optical fiber monitoring point. Based on the strain values ​​at each fiber optic monitoring point, the strain distribution gradient and strain change rate are analyzed, and the strain values, strain distribution gradient and strain change rate at each fiber optic monitoring point are integrated to generate a strain distribution heat map and change curve of the machine tool column. Analyze machine tool stress risk: Based on the strain value distribution in the thermogram, if the strain value at the fiber optic monitoring point exceeds the preset stress threshold, it indicates that the area where the monitoring point is located is under excessive stress. If the difference between the maximum and minimum strain distribution gradients exceeds the preset distribution threshold, it indicates that the stress is uneven in different parts of the column. In this case, it indicates that the machine tool is under stress risk. Analyze machine tool deformation risk: If the strain change rate exceeds the preset rate threshold, it indicates that the machine tool column is at risk of deformation. The analysis results are then output to the abnormal warning automatic response module.

3. The automatic equipment foundation detection system according to claim 1, characterized in that: The specific contents of the machine tool column angle eccentricity monitoring module are as follows: Each level of displacement sensor is used to capture the linear displacement of the machine tool column corner in the horizontal direction along the X and Y axes, while each level of tilt sensor is used to monitor the tilt angle of the machine tool column corner around the vertical axis, namely the tilt angle around the X axis and the tilt angle around the Y axis. The vertical distance between each monitoring level is preset, namely the distance from the bottom to the middle and the distance from the middle to the top. Using the center position of the column corner at the initial installation of the machine tool as a reference, the sensors at each level collect the real-time displacement data of the machine tool column corner in the X-axis and Y-axis directions, which are recorded as the displacement deviations of the bottom, middle and top in the X-axis and Y-axis directions; The displacement data is corrected based on the tilt angle. Taking the bottom level as the reference, the theoretical displacements of the middle and top caused by the tilt are calculated, including: the theoretical displacement in the Y direction caused by the tilt of the middle around the X-axis, the theoretical displacement in the X direction caused by the tilt of the middle around the Y-axis, the theoretical displacement in the Y direction caused by the tilt of the top around the X-axis, and the theoretical displacement in the X direction caused by the tilt of the top around the Y-axis. The corrected actual displacement deviations of the middle and top are obtained by subtracting the theoretical displacements of the middle and top due to tilt from the displacement deviations of the middle and top on the X and Y axes. The analysis calculates the difference between the actual displacement deviation in the middle and the bottom, as well as the difference between the actual displacement deviation at the top and the bottom. If the difference is less than or equal to the preset judgment threshold, the machine tool column angle is judged to be in a normal state. Otherwise, the machine tool column angle is judged to be eccentric, and the analysis results are output to the abnormal warning automatic response module.

4. The automatic equipment foundation detection system according to claim 1, characterized in that: The specific contents of the abnormal early warning automatic response module are as follows: The system receives the machine tool column corner eccentricity judgment results and the equipment operating environment perception results. When it is determined that the machine tool column corner is eccentric, it issues an early warning message based on the heat map and change curve in the equipment operating environment perception results, combined with the machine tool stress risk and deformation risk: if the equipment operating environment perception module shows that the machine tool has stress risk or the machine tool column has deformation risk, a first-level early warning message is issued; if the equipment operating environment perception module shows that the machine tool has stress risk and the machine tool column has deformation risk, a second-level early warning message is issued. The abnormal warning automatic response module uses a stepped power cut-off logic to perform progressive braking control on the machine tool when an abnormal warning occurs. In the first-level warning, a speed adjustment command is issued through the PLC interface of the machine tool spindle drive system to gradually reduce the spindle speed. At the same time, the feed system is linked to reduce the feed speed to reduce the additional stress under eccentric conditions. If the warning is upgraded to the second-level warning, a cut-off command is immediately sent to the axis power control unit to forcibly disconnect the servo motor power through the relay group. At the same time, the axis locking device is triggered to lock the axis movement authority instantly. After the power is cut off, the column corner position and strain status are continuously monitored. The axis lock can only be released and the power supply restored after the operator inputs an authorization command and confirms that the risk has been eliminated.

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