Multi-sensor fusion positioning method

Abstract

The invention discloses a multi-sensor fusion positioning method, particularly relates to the field of data analysis, and comprises a grinding machine monitoring time division module, a grinding machine data acquisition module, a grinding machine data analysis module, a grinding machine calibration index calculation module, a grinding machine calibration index evaluation module and a grinding machine calibration module. The actual use data of the grinding wheel and the machined workpiece are collected through the industrial camera and the laser scanner, the position and posture of the grinding wheel and the machined workpiece can be more accurately determined, calibration errors are reduced, the data collection precision is improved, the abnormal condition of the running state of the grinding machine can be found in time through analysis of the running data of the grinding machine, and the working efficiency is improved. According to the grinding machine calibration device, equipment damage and production accidents are avoided, when the grinding machine needs to be calibrated, the closest calibration personnel can be timely contacted to calibrate the grinding machine, the downtime and the maintenance cost of the grinding machine can be reduced, the operation efficiency and the production benefit of the grinding machine are improved, and the safety of the grinding machine in the operation process is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and more specifically, to a multi-sensor fusion positioning method. Background Art

[0002] In modern manufacturing, data analysis technology plays an increasingly important role in improving production efficiency and ensuring equipment safety. Especially in the field of grinding machine processing, accurate and real-time equipment status monitoring is essential to ensure processing accuracy, extend equipment life, and prevent production accidents. In order to achieve this goal, multi-sensor fusion positioning methods have emerged, which combine the advantages of multiple sensors to provide more comprehensive and accurate equipment status information.

[0003] The application process of the existing multi-sensor fusion positioning method in grinding machine processing is roughly as follows: First, with the help of multiple sensors such as vibration sensors, laser rangefinders, encoders, hardness testers, etc., the key parameters of the grinding machine operation process are collected in real time, including but not limited to grinding wheel amplitude, grinding wheel vibration frequency, processing distance, grinding wheel hardness, etc. Subsequently, these data are transmitted to the data analysis system, processed and analyzed to reveal the various factors that affect the grinding machine processing accuracy. Based on these analysis results, the operator can perform necessary calibration and maintenance operations on the grinder to ensure its stable operation.

[0004] However, the existing technology still has some obvious shortcomings. First, the complexity and diversity of the grinding machine processing environment cause the sensor data to often contain noise and errors, which to a certain extent reduces the accuracy of data analysis. Secondly, the existing technology is often limited to the analysis of a single sensor or data dimension, and fails to fully utilize the correlation and complementarity between multi-sensor data, thereby limiting the potential and depth of data analysis. In addition, the response speed and efficiency of grinder calibration and maintenance need to be improved to better meet the needs of modern manufacturing for efficient and precise production. These shortcomings indicate that the application of existing multi-sensor fusion positioning methods in the field of grinding machine processing still needs to be improved and optimized. Summary of the invention

[0005] In order to overcome the above defects of the prior art, an embodiment of the present invention provides a multi-sensor fusion positioning method, which solves the problems raised in the above background technology through the following scheme.

[0006] To achieve the above object, the present invention provides the following technical solution: a multi-sensor fusion positioning method, comprising: Grinding machine monitoring time division module: used to obtain the operating data of the target five-axis notch CNC grinder within a preset time period, and divide it into various monitoring sub-areas according to the time division method, and number the grinders in each monitoring sub-area, and number them 1, 2, 3...n.

[0007] The grinding machine data acquisition module is used to collect the grinding wheel amplitude, grinding wheel vibration frequency, grinding wheel grain number, processing distance, grinding wheel hardness, grinding fluid flow, and grinding wheel radius of each monitoring sub-area grinder, and the density and hardness of the workpiece, which are marked as , , , , , , , ,as well as , where i=1, 2,...n, and i represents the i-th monitoring sub-area.

[0008] Grinding machine data analysis module: including vibration variation coefficient calculation unit, feed speed variation coefficient calculation unit, grinding depth variation coefficient calculation unit, and temperature variation coefficient calculation unit, used to analyze the data transmitted by the grinding machine data acquisition module, and transmit the analyzed data to the grinding machine calibration index calculation module.

[0009] Grinder calibration index calculation module: used to receive various characteristic data affecting the calibration of the five-axis notch CNC grinder transmitted by the grinder data analysis module, and calculate the various data transmitted by the grinder data analysis module using a mathematical model through the grinder calibration index calculation unit to obtain the grinder calibration index, and transmit the grinder calibration index to the grinder calibration index evaluation module.

[0010] The grinder calibration index evaluation module is used to receive the grinder calibration index transmitted by the grinder calibration index calculation module, evaluate the grinder calibration index through the grinder calibration index evaluation unit, and transmit the evaluation result to the grinder calibration module.

[0011] The grinder calibration module is used to receive the monitoring sub-area number and grinder operation data of the grinder calibration index exceeding the standard transmitted by the grinder calibration index evaluation module, and calibrate the grinder with the grinder calibration index exceeding the standard by analyzing and recording the grinder operation data of the grinder calibration index exceeding the standard.

[0012] Preferably, the grinding wheel amplitude is collected by a vibration sensor installed on the grinding machine, the grinding wheel vibration frequency is collected by a vibration sensor, and the collected vibration signal is subjected to frequency analysis to obtain the vibration frequency of the grinding wheel, the grinding wheel grain count is acquired by a high-resolution industrial camera for image acquisition, and then the grains on the grinding wheel surface are counted by an image processing algorithm, the processing distance is measured in real time by a laser rangefinder or an encoder for the moving distance of the grinder spindle, the grinding wheel hardness is measured regularly by a dedicated hardness tester, or indirectly evaluated by feedback data during the grinding process, the grinding fluid flow is monitored by a flow sensor for the grinding fluid delivery pipeline, and the grinding fluid flow data is acquired in real time, the grinding wheel radius is scanned in three dimensions by a laser scanner or an industrial camera, and then the radius of the grinding wheel is calculated by an algorithm, the density of the workpiece is measured regularly by a density tester, or estimated according to the material and specifications of the workpiece, the hardness of the workpiece is measured by a hardness tester, and the hardness of the workpiece is evaluated by an indentation method or a rebound method.

[0013] Preferably, the grinder data analysis module performs calculation and analysis on the data transmitted by the grinder data acquisition module through the mathematical model corresponding to the calculation unit, integrates the data transmitted by the grinder data acquisition module with the existing data of the grinder, extracts and classifies various features that affect the calibration of the five-axis notch CNC grinder.

[0014] The mathematical model used by the vibration variation coefficient calculation unit is: , represents the vibration variation coefficient of the ith monitoring sub-area, represents the grinding wheel amplitude of the i-th monitoring sub-area, represents the grinding wheel vibration frequency of the i-th monitoring sub-area, represents the number of grinding wheel grains in the i-th monitoring sub-area, represents the monitoring time of the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Other factors affecting the coefficient of vibration variation; The mathematical model used by the feed speed variation coefficient calculation unit is: , represents the feed speed variation coefficient of the i-th monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the density of processed workpieces in the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Other factors affecting the feed rate variation coefficient; The mathematical model used by the grinding depth variation coefficient calculation unit is: , represents the grinding depth variation coefficient of the i-th monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the grinding wheel hardness of the i-th monitoring sub-area, represents the hardness of the workpiece in the i-th monitoring sub-area, Other influencing factors that represent the grinding depth variation coefficient; The mathematical model used by the temperature variation coefficient calculation unit is: , represents the temperature variation coefficient of the i-th monitoring sub-area, Indicates the preset maximum temperature of the grinding wheel of the grinding machine. represents the grinding wheel radius of the ith monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the grinding fluid flow rate of the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Indicates other factors affecting the temperature variation coefficient.

[0015] Preferably, the mathematical model used by the grinder calibration index calculation unit is: , represents the grinder calibration index of the ith monitoring sub-area, represents the vibration variation coefficient of the ith monitoring sub-area, represents the feed speed variation coefficient of the i-th monitoring sub-area, represents the grinding depth variation coefficient of the i-th monitoring sub-area, represents the temperature variation coefficient of the i-th monitoring sub-area, Indicates other influencing factors of the grinder calibration index.

[0016] Preferably, the grinder calibration index evaluation unit calibrates or continues to monitor the grinder by analyzing the grinder calibration index. When , it means that the grinder calibration index of the i-th monitoring sub-area exceeds the standard, and the monitoring sub-area number of the grinder calibration index exceeding the standard and the grinder operation data are transmitted to the grinder calibration module. When , it indicates that the calibration index of the grinder in the ith monitoring sub-area is normal, and the monitoring of the grinder operation data in the ith monitoring sub-area is maintained.

[0017] Preferably, the grinder calibration module generates a corresponding calibration plan by analyzing the grinder operation data of the grinder whose calibration index exceeds the standard, and sends the calibration plan and the monitoring sub-area number to the calibration personnel closest to the target monitoring sub-area via the Internet to calibrate the five-axis notch CNC grinder.

[0018] Technical effects and advantages of the present invention: The present invention collects actual usage data of grinding wheels and processed workpieces through industrial cameras and laser scanners, and can determine their positions and postures more accurately, thereby reducing calibration errors and improving data collection accuracy. By analyzing the operating data of the grinder, abnormal operating conditions of the grinder can be discovered in time to avoid equipment damage and production accidents. When the grinder needs to be calibrated, the nearest calibration personnel can be contacted in time to calibrate the grinder, which can reduce the grinder downtime and maintenance costs, improve the operating efficiency and production benefits of the grinder, extend its service life, and ensure the safety of the grinder during operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] refer to Figure 1 A multi-sensor fusion positioning method is shown, including a grinder monitoring time division module, a grinder data acquisition module, a grinder data analysis module, a grinder calibration index calculation module, a grinder calibration index evaluation module, and a grinder calibration module.

[0022] The grinder monitoring time division module is used to obtain the operating data of the target five-axis notch CNC grinder within a preset time period, and divide it into monitoring sub-areas according to the time division method, and number the grinders in each monitoring sub-area, and number them 1, 2, 3...n.

[0023] The grinding machine data acquisition module is used to collect the grinding wheel amplitude, grinding wheel vibration frequency, grinding wheel grain number, processing distance, grinding wheel hardness, grinding fluid flow rate, and grinding wheel radius of the grinding machine in each monitoring sub-area, and the density and hardness of the processed workpiece, which are marked as , , , , , , , ,as well as , where i=1, 2,...n, and i represents the i-th monitoring sub-area.

[0024] The grinding wheel amplitude is collected by a vibration sensor installed on the grinding machine, the grinding wheel vibration frequency is collected by a vibration sensor, and the collected vibration signal is subjected to frequency analysis to obtain the vibration frequency of the grinding wheel. The grinding wheel grain count is collected by a high-resolution industrial camera, and then the grains on the grinding wheel surface are counted by an image processing algorithm. The processing distance is measured in real time by a laser rangefinder or an encoder to measure the moving distance of the grinder spindle. The grinding wheel hardness is measured regularly by a dedicated hardness tester, or indirectly evaluated by feedback data during the grinding process. The grinding fluid flow is monitored by a flow sensor on the grinding fluid delivery pipeline, and the grinding fluid flow data is obtained in real time. The grinding wheel radius is scanned in three dimensions by a laser scanner or an industrial camera, and then the radius of the grinding wheel is calculated by an algorithm. The density of the workpiece is measured regularly by a density tester, or estimated according to the material and specifications of the workpiece. The hardness of the workpiece is measured by a hardness tester, and the hardness of the workpiece is evaluated by an indentation method or a rebound method.

[0025] The grinder data analysis module includes a vibration variation coefficient calculation unit, a feed speed variation coefficient calculation unit, a grinding depth variation coefficient calculation unit, and a temperature variation coefficient calculation unit, which are used to analyze the various data transmitted by the grinder data acquisition module and transmit the analyzed data to the grinder calibration index calculation module.

[0026] The grinder data analysis module calculates and analyzes the data transmitted by the grinder data acquisition module through the mathematical model corresponding to the calculation unit, integrates the data transmitted by the grinder data acquisition module and the existing data of the grinder, extracts and classifies various features that affect the calibration of the five-axis notch CNC grinder.

[0027] The mathematical model used by the vibration variation coefficient calculation unit is: , represents the vibration variation coefficient of the ith monitoring sub-area, represents the grinding wheel amplitude of the i-th monitoring sub-area, represents the grinding wheel vibration frequency of the i-th monitoring sub-area, represents the number of grinding wheel grains in the i-th monitoring sub-area, represents the monitoring time of the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Indicates other influencing factors of the vibration variation coefficient.

[0028] The mathematical model used by the feed speed variation coefficient calculation unit is: , represents the feed speed variation coefficient of the i-th monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the density of processed workpieces in the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Indicates other influencing factors of the feed rate variation coefficient.

[0029] The mathematical model used by the grinding depth variation coefficient calculation unit is: , represents the grinding depth variation coefficient of the i-th monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the grinding wheel hardness of the i-th monitoring sub-area, represents the hardness of the workpiece in the i-th monitoring sub-area, Other factors affecting the grinding depth variation coefficient.

[0030] The mathematical model used by the temperature variation coefficient calculation unit is: , represents the temperature variation coefficient of the i-th monitoring sub-area, Indicates the preset maximum temperature of the grinding wheel of the grinding machine. represents the grinding wheel radius of the ith monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the grinding fluid flow rate of the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Indicates other factors affecting the temperature variation coefficient.

[0031] The grinder calibration index calculation module is used to receive various characteristic data affecting the calibration of the five-axis notch CNC grinder transmitted by the grinder data analysis module, and calculate the various data transmitted by the grinder data analysis module using a mathematical model through the grinder calibration index calculation unit to obtain the grinder calibration index, and transmit the grinder calibration index to the grinder calibration index evaluation module.

[0032] The mathematical model used by the grinding machine calibration index calculation unit is: , represents the grinder calibration index of the ith monitoring sub-area, represents the vibration variation coefficient of the ith monitoring sub-area, represents the feed speed variation coefficient of the i-th monitoring sub-area, represents the grinding depth variation coefficient of the i-th monitoring sub-area, represents the temperature variation coefficient of the i-th monitoring sub-area, Indicates other influencing factors of the grinder calibration index.

[0033] The grinder calibration index evaluation module is used to receive the grinder calibration index transmitted by the grinder calibration index calculation module, evaluate the grinder calibration index through the grinder calibration index evaluation unit, and transmit the evaluation result to the grinder calibration module.

[0034] The grinder calibration index evaluation unit calibrates or continues to monitor the grinder by analyzing the grinder calibration index. When , it means that the grinder calibration index of the i-th monitoring sub-area exceeds the standard, and the monitoring sub-area number of the grinder calibration index exceeding the standard and the grinder operation data are transmitted to the grinder calibration module. When , it indicates that the calibration index of the grinder in the ith monitoring sub-area is normal, and the monitoring of the grinder operation data in the ith monitoring sub-area is maintained.

[0035] The grinder calibration module is used to receive the monitoring sub-area number and grinder operation data of the grinder calibration index exceeding the standard transmitted by the grinder calibration index evaluation module, and calibrate the grinder with the grinder calibration index exceeding the standard by analyzing and recording the grinder operation data of the grinder calibration index exceeding the standard.

[0036] The grinder calibration module generates a corresponding calibration plan by analyzing the grinder operation data of the grinder calibration index that exceeds the standard, and sends the calibration plan and the monitoring sub-area number to the calibration personnel closest to the target monitoring sub-area through the Internet to calibrate the five-axis notch CNC grinder.

[0037] The present invention divides the monitoring of the grinder into monitoring sub-areas according to time and numbers them through a grinder monitoring time division module, uses an industrial camera and a laser scanner through a grinder data acquisition module to collect pictures of the target grinder and convert them into digital information, and classifies the collected data and transmits them to a grinder data analysis module, calculates and analyzes the data transmitted by the grinder data acquisition module through a mathematical model corresponding to a calculation unit in the grinder data analysis module, and transmits the analyzed data to a grinder calibration index calculation module, calculates the various data transmitted by the grinder data analysis module through a grinder calibration index calculation unit in the grinder calibration index calculation module to obtain a grinder calibration index, and transmits the grinder calibration index to a grinder calibration index evaluation module, evaluates the grinder calibration index through a grinder calibration index evaluation unit in the grinder calibration index evaluation module, and transmits the evaluation result to a grinder calibration module, analyzes and records the operation data of the grinder whose grinder calibration index exceeds the standard through the grinder calibration module, and calibrates the grinder whose grinder calibration index exceeds the standard.

[0038] The present invention collects actual usage data of grinding wheels and processed workpieces through industrial cameras and laser scanners, and can determine their positions and postures more accurately, thereby reducing calibration errors and improving data collection accuracy. By analyzing the operating data of the grinder, abnormal operating conditions of the grinder can be discovered in time to avoid equipment damage and production accidents. When the grinder needs to be calibrated, the nearest calibration personnel can be contacted in time to calibrate the grinder, which can reduce the grinder downtime and maintenance costs, improve the operating efficiency and production benefits of the grinder, extend its service life, and ensure the safety of the grinder during operation.

[0039] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other; Finally: 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 in the protection scope of the present invention.

Claims

1. A multi-sensor fusion positioning method, comprising: Grinding machine monitoring time division module: used to obtain the operation data of the target five-axis notch CNC grinding machine within a preset time period, and divide it into various monitoring sub-areas according to the time division method, and number the grinders in each monitoring sub-area, and number them 1, 2, 3...n; The grinding machine data acquisition module is used to collect the grinding wheel amplitude, grinding wheel vibration frequency, grinding wheel grain number, processing distance, grinding wheel hardness, grinding fluid flow, and grinding wheel radius of each monitoring sub-area grinder, and the density and hardness of the workpiece, which are marked as , , , , , , , ,as well as , where i=1, 2, ..., n, i represents the i-th monitoring sub-area; Grinding machine data analysis module: including a vibration variation coefficient calculation unit, a feed speed variation coefficient calculation unit, a grinding depth variation coefficient calculation unit, and a temperature variation coefficient calculation unit, used to analyze various data transmitted by the grinding machine data acquisition module, and transmit the analyzed data to the grinding machine calibration index calculation module; The grinder calibration index calculation module is used to receive various characteristic data that affect the calibration of the five-axis notch CNC grinder transmitted by the grinder data analysis module, and calculate the various data transmitted by the grinder data analysis module using a mathematical model through the grinder calibration index calculation unit to obtain the grinder calibration index, and transmit the grinder calibration index to the grinder calibration index evaluation module; The grinder calibration index evaluation module is used to receive the grinder calibration index transmitted by the grinder calibration index calculation module, evaluate the grinder calibration index through the grinder calibration index evaluation unit, and transmit the evaluation result to the grinder calibration module; The grinder calibration module is used to receive the monitoring sub-area number and grinder operation data of the grinder calibration index exceeding the standard transmitted by the grinder calibration index evaluation module, and calibrate the grinder with the grinder calibration index exceeding the standard by analyzing and recording the grinder operation data of the grinder calibration index exceeding the standard.

2. A multi-sensor fusion positioning method according to claim 1, characterized in that: The grinding wheel amplitude is collected by a vibration sensor installed on the grinding machine, the grinding wheel vibration frequency is collected by a vibration sensor, and the collected vibration signal is subjected to frequency analysis to obtain the vibration frequency of the grinding wheel. The grinding wheel grain count is collected by a high-resolution industrial camera, and then the grains on the grinding wheel surface are counted by an image processing algorithm. The processing distance is measured in real time by a laser rangefinder or an encoder to measure the moving distance of the grinder spindle. The grinding wheel hardness is measured regularly by a dedicated hardness tester, or indirectly evaluated by feedback data during the grinding process. The grinding fluid flow is monitored by a flow sensor on the grinding fluid delivery pipeline, and the grinding fluid flow data is obtained in real time. The grinding wheel radius is scanned in three dimensions by a laser scanner or an industrial camera, and then the radius of the grinding wheel is calculated by an algorithm. The density of the workpiece is measured regularly by a density tester, or estimated according to the material and specifications of the workpiece. The hardness of the workpiece is measured by a hardness tester, and the hardness of the workpiece is evaluated by an indentation method or a rebound method.

3. A multi-sensor fusion positioning method according to claim 1, characterized in that: The grinding machine data analysis module calculates and analyzes the data transmitted by the grinding machine data acquisition module through the mathematical model corresponding to the calculation unit, integrates the data transmitted by the grinding machine data acquisition module and the existing data of the grinding machine, extracts and classifies various features that affect the calibration of the five-axis notch CNC grinding machine; The mathematical model used by the vibration variation coefficient calculation unit is: , represents the vibration variation coefficient of the ith monitoring sub-area, represents the grinding wheel amplitude of the i-th monitoring sub-area, represents the grinding wheel vibration frequency of the i-th monitoring sub-area, represents the number of grinding wheel grains in the i-th monitoring sub-area, represents the monitoring time of the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Other factors affecting the coefficient of vibration variation; The mathematical model used by the feed speed variation coefficient calculation unit is: , represents the feed speed variation coefficient of the i-th monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the density of processed workpieces in the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Other factors affecting the feed rate variation coefficient; The mathematical model used by the grinding depth variation coefficient calculation unit is: , represents the grinding depth variation coefficient of the i-th monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the grinding wheel hardness of the i-th monitoring sub-area, represents the hardness of the workpiece in the i-th monitoring sub-area, Other influencing factors that represent the grinding depth variation coefficient; The mathematical model used by the temperature variation coefficient calculation unit is: , represents the temperature variation coefficient of the i-th monitoring sub-area, Indicates the preset maximum temperature of the grinding wheel. represents the grinding wheel radius of the ith monitoring sub-area, represents the processing distance of the ith monitoring sub-area, represents the grinding fluid flow rate of the ith monitoring sub-area, represents the time difference between the monitoring time of the ith monitoring sub-area and the monitoring time of the i-1th monitoring sub-area, Indicates other factors affecting the temperature variation coefficient.

4. The multi-sensor fusion positioning method according to claim 1, characterized in that: The mathematical model used by the grinding machine calibration index calculation unit is: , represents the grinder calibration index of the ith monitoring sub-area, represents the vibration variation coefficient of the ith monitoring sub-area, represents the feed speed variation coefficient of the i-th monitoring sub-area, represents the grinding depth variation coefficient of the i-th monitoring sub-area, represents the temperature variation coefficient of the i-th monitoring sub-area, Indicates other influencing factors of the grinder calibration index.

5. The multi-sensor fusion positioning method according to claim 1, characterized in that: The grinder calibration index evaluation unit calibrates or continues to monitor the grinder by analyzing the grinder calibration index. When , it means that the grinder calibration index of the i-th monitoring sub-area exceeds the standard, and the monitoring sub-area number of the grinder calibration index exceeding the standard and the grinder operation data are transmitted to the grinder calibration module. When , it indicates that the calibration index of the grinder in the ith monitoring sub-area is normal, and the monitoring of the grinder operation data in the ith monitoring sub-area is maintained.

6. The multi-sensor fusion positioning method according to claim 1, characterized in that: The grinder calibration module generates a corresponding calibration plan by analyzing the grinder operation data of the grinder calibration index that exceeds the standard, and sends the calibration plan and the monitoring sub-area number to the calibration personnel closest to the target monitoring sub-area through the Internet to calibrate the five-axis notch CNC grinder.

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