System for monitoring safety production of automobile parts

Abstract

A system for monitoring safety production of automobile parts relates to the technical field of data monitoring and comprises a monitoring center which is in communication connection with a data acquisition module, a data storage module, a flow visualization module, a process parameter monitoring module, an automobile part monitoring module and a safety monitoring module. The data acquisition module acquires process parameter information and automobile part information; the process visualization module is used for constructing an automobile part production whole-process model; the process parameter monitoring module monitors the whole process model of the automobile part production in real time according to the process parameter monitoring result; the automobile part monitoring module is used for judging whether automobile parts are qualified or not; and the safety monitoring module visually displays the safety early warning information of the safety production process of the automobile parts based on an automobile part production whole-process model, so that the product quality and the efficiency and accuracy of safety control of the production process are greatly improved, and meanwhile, the cost of manual monitoring and the risk of human errors are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of data monitoring, and specifically to a safety production system for monitoring automotive parts and components. Background Art

[0002] Today, the competition of automotive products in the market is based on high quality. High-quality automotive products are first ensured by high-quality parts and a safe and reliable production system for automotive parts and components.

[0003] In recent years, in the automotive industry, manufacturers at home and abroad have been pursuing advanced processing technologies and perfect detection methods to ensure the qualification of all parts. Among them, how to conduct a strict and comprehensive inspection and screening of processed automotive parts in each process sub-sequence, and ensure that problems such as aging, damage, and faults of automotive production equipment in each process can be detected in a timely manner during the production process of automotive parts and components is a technical problem that we urgently need to solve. Now, a safety production system for monitoring automotive parts and components is provided. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a safety production system for monitoring automotive parts and components, including a monitoring center, which is communicatively connected to a data acquisition module, a data storage module, a process visualization module, a process parameter monitoring module, an automotive parts and components monitoring module, and a safety monitoring module; The data acquisition module is used to collect process parameter information and automotive parts and components information in the process sub-sequences of automotive parts and components and set a monitoring period; The data storage module is used to store historical data information during the production process of automotive parts and components; The process visualization module is used to construct a full-process model for the production of automotive parts and components based on the process parameter information and automotive parts and components information of each process sub-sequence; The process parameter monitoring module is used to perform real-time monitoring and control on the full-process model for the production of automotive parts and components based on the monitoring results of the process parameters of each process sub-sequence; The automotive parts and components monitoring module is used to determine whether the automotive parts and components are qualified based on the image data information and weight data information of the automotive parts and components in each process sub-sequence; The safety monitoring module is used to visually display the safety warning information during the safety production process of automotive parts and components based on the full-process model for the production of automotive parts and components.

[0005] Furthermore, the process of the data acquisition module collecting process parameter information and automotive parts and components information in the process sub-sequences of automotive parts and components includes: The data acquisition module includes a process flow information acquisition module and an automotive parts data acquisition module; The process flow information acquisition module is used to obtain the process flow information of automotive parts production in the current monitoring period, extract process flow characteristics according to the process flow information, split the automotive parts production process according to the process flow characteristics, and divide it into several process flow subsequences; determine the process parameter monitoring indicators of each process flow subsequence according to the process flow characteristics of each process flow subsequence and deploy sensors, and collect process parameter data corresponding to the process parameter monitoring indicators through the sensors; the process parameter data includes: temperature, pressure, humidity, and vibration spectrum; The automotive parts data acquisition module is used to set up automotive parts image sensors and weight sensors in each process flow subsequence, and collect image data information and weight data information of the automotive parts to be monitored that have completed the process flow processing in each process flow subsequence through the automotive parts image sensors and weight sensors.

[0006] Further, the process of the data acquisition module deploying sensors in each process flow subsequence includes: Obtain the location information and process parameter monitoring indicators of the automotive parts production equipment in each process flow subsequence, obtain the risk failure sources according to the location information and process parameter monitoring indicators of the automotive parts production equipment in each process flow subsequence, and extract the failure source characteristics of the risk failure sources according to the process parameter monitoring indicators involved when the risk failure sources suddenly fail; Use the big data method to obtain the historical occurrence data of sudden failures of the automotive parts production equipment in each process flow subsequence, and perform statistical analysis on the historical occurrence data when the risk failure sources suddenly fail through the failure source characteristics to obtain the historical occurrence times corresponding to each failure source characteristic; Obtain the process parameter monitoring indicators of each process flow subsequence and select the sensor types corresponding to the process parameter monitoring indicators; and obtain the number of sensors deployed corresponding to each process parameter monitoring indicator in each process flow subsequence according to the historical occurrence times corresponding to the failure source characteristics when the risk failure sources in each process flow subsequence suddenly fail.

[0007] Further, the process of the process visualization module constructing a full-process model of automotive parts production according to the process parameter information and automotive part information of each process flow subsequence includes: Obtain the physical entities of the automotive parts production equipment in the physical space in the automotive parts production process in the current monitoring period, obtain the multi-source heterogeneous data sets of each physical entity in the automotive parts production process in the current monitoring period regarding process parameter information and automotive part information, and perform data format preprocessing; Perform three-dimensional modeling on the physical entities of automotive parts production equipment and map them to the digital space. Generate twin data from multi-source heterogeneous data after preprocessing the data format, and match the twin data with the three-dimensional model in the digital space according to the process flow assembly connection relationship of the physical entities in the physical space to obtain a digital twin model; Obtain the spatial position information of each automotive parts production equipment in the automotive parts production process, store the spatial position information in the digital space, and combine the spatial position information of each automotive parts production equipment in the automotive parts production process in the current monitoring period with the digital twin model to generate a full-process model of automotive parts production.

[0008] Further, the process of the process parameter monitoring module performing real-time monitoring and control on the full-process model of automotive parts production according to the process parameter monitoring results of each process flow subsequence includes: Obtain the process parameter data of each process flow subsequence, set the standard index values of the process parameters and the warning threshold of the process parameter index deviation for each process flow subsequence, compare the process parameter data with the standard index values of the process parameters of each process flow subsequence to obtain the deviation values of each process parameter index, and compare the deviation values of each process parameter index with the warning threshold of the process parameter index deviation; When the deviation value of each process parameter index is greater than the warning threshold of the process parameter index deviation; set a preset time threshold and accumulate the time when the deviation value of each process parameter index is greater than the warning threshold of the process parameter index deviation; When the accumulated time is greater than or equal to the preset time threshold, stop the operation of the automotive parts production equipment corresponding to the process parameter index deviation value of this process flow subsequence and generate a fault warning information at the location where the automotive parts production equipment is located.

[0009] Further, the process of the automotive parts monitoring module judging whether the automotive parts are qualified according to the image data information and weight data information of the automotive parts in each process flow subsequence includes: Obtain the three-dimensional model of the automotive parts after processing in different process flow subsequences through the data storage module, and obtain the template image of the automotive parts after processing in different process flow subsequences according to the three-dimensional model. Extract the image features of the image data information of the automotive parts collected in the process flow subsequence of the current monitoring period, and obtain the grayscale histogram of the grayscale features of the image data information and the histogram of oriented gradients of the texture features of the image data information; Set a preset similarity threshold, and compare the similarity of the grayscale histogram and the histogram of oriented gradients of the image data information of the automotive parts collected in the process flow subsequence of the current monitoring period with the grayscale histogram and the histogram of oriented gradients of the template image of the automotive parts corresponding to this process flow subsequence; Measure the dimensions of the automotive parts with a similarity greater than or equal to the preset similarity threshold; Mark the automotive parts with a similarity less than the preset similarity threshold as unqualified parts, stop the operation of the production equipment for unqualified parts, and generate a fault warning message for the location where the production equipment for unqualified parts is located.

[0010] Further, the process of the automotive parts monitoring module measuring the dimensions of automotive parts includes: Obtain the standard dimension data of the automotive parts after processing in different process sub-sequences according to the three-dimensional model, extract the image edge features of the image data information of the automotive parts collected in the process sub-sequence of the current monitoring cycle through the Canny algorithm; obtain the actual dimensions of the automotive parts through the image edge features, set the dimension error threshold, and compare the actual dimensions of the automotive parts with the standard dimension data; Measure the weight of the automotive parts with a deviation value between the actual dimension and the standard dimension data less than or equal to the dimension error threshold; Mark the automotive parts with a deviation value between the actual dimension and the standard dimension data less than or equal to the dimension error threshold as unqualified parts, stop the operation of the production equipment for unqualified parts, and generate a fault warning message for the location where the production equipment for unqualified parts is located.

[0011] Further, the process of the automotive parts monitoring module measuring the weight of automotive parts includes: Obtain the standard weight information of the automotive parts after processing in different process sub-sequences through the data storage module, set the weight error threshold, and compare the weight data information of the automotive parts with the standard weight information; Mark the automotive parts with a deviation value between the weight data information and the standard weight information less than or equal to the weight error threshold as qualified parts; Mark the automotive parts with a deviation value between the weight data information and the standard weight information greater than the weight error threshold as unqualified parts, stop the operation of the production equipment for unqualified parts, and generate a fault warning message for the location where the production equipment for unqualified parts is located.

[0012] Further, the process of the safety monitoring module visually displaying the safety warning information during the safe production process of automotive parts based on the full-process model of automotive parts production includes: Obtain the fault warning information of each process sub - sequence in the current monitoring period, perform zoning processing on each process sub - sequence according to the fault warning information, and obtain the compliance rate of process parameter data and the qualified rate of auto parts in each process sub - sequence area according to the fault warning information. Match the corresponding warning levels with each process sub - sequence area according to the compliance rate of process parameter data and the qualified rate of auto parts; Provide an execution basis for the safety emergency measures of auto parts production in the next monitoring period according to the warning levels of each process sub - sequence area during the production process of auto parts in the current monitoring period.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: By monitoring the process parameters of auto parts production equipment during the production process and setting warning thresholds, once an abnormal situation occurs, the system will promptly stop the production of the auto parts production equipment and generate equipment fault warning information at the location of the auto parts production equipment; And visual display of the safety warning information during the production process of auto parts based on the full - process model of auto parts production can greatly improve the efficiency and accuracy of product quality and production process safety control, while reducing the cost of manual monitoring and the risk of human errors.

[0014] On the other hand, by monitoring the surface damage degree, size and weight of auto parts during the production process, it is determined whether the auto parts are qualified to ensure the accuracy and qualification of the final quality of auto parts. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of a system for monitoring the safe production of auto parts according to an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The following clearly and completely describes the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those skilled in the art based on the embodiments in the present application without creative efforts fall within the scope of protection of the present application.

[0017] As Figure 1 shown, a system for monitoring the safe production of auto parts includes a monitoring center, characterized in that the monitoring center is communicatively connected to a data acquisition module, a data storage module, a process visualization module, a process parameter monitoring module, an auto parts monitoring module, and a safety monitoring module; The data acquisition module is used to collect process parameter information and auto part information in the process sub - sequences of auto parts and set the monitoring period; The data storage module is used to store the historical data information in the production process of auto parts; The process visualization module is used to construct a full-process model of auto parts production according to the process parameter information and auto part information of each process sub-sequence; The process parameter monitoring module is used to monitor and control the full-process model of auto parts production in real time according to the process parameter monitoring results of each process sub-sequence; The auto parts monitoring module is used to judge whether the auto parts are qualified according to the image data information and weight data information of the auto parts in each process sub-sequence; The safety monitoring module is used to visually display the safety warning information in the safe production process of auto parts based on the full-process model of auto parts production.

[0018] It should be further noted that in the specific implementation process, the process of the data acquisition module collecting the process parameter information and auto part information in each process sub-sequence of auto parts includes: The data acquisition module includes a process information acquisition module and an auto parts data acquisition module; The process information acquisition module is used to obtain the process information of auto parts production in the current monitoring period, extract the process characteristics according to the process information, split the auto parts production process according to the process characteristics, and divide it into several process sub-sequences; determine the process parameter monitoring indexes of each process sub-sequence according to the process characteristics of each process sub-sequence and deploy sensors, and collect the process parameter data corresponding to the process parameter monitoring indexes through the sensors; the process parameter data includes: temperature, pressure, humidity and vibration spectrum; The auto parts data acquisition module is used to set up auto parts image sensors and weight sensors in each process sub-sequence, and collect the image data information and weight data information of the auto parts to be monitored that have completed the process treatment in each process sub-sequence through the auto parts image sensors and weight sensors.

[0019] It should be further noted that in the specific implementation process, the process of the data acquisition module deploying sensors in each process sub-sequence includes: Obtain the position information of the auto parts production equipment and the process parameter monitoring indexes in each process sub-sequence, obtain the risk failure sources according to the position information of the auto parts production equipment and the process parameter monitoring indexes in each process sub-sequence, and extract the failure source characteristics of the risk failure sources according to the process parameter monitoring indexes involved when the risk failure sources suddenly fail; Using big data methods to obtain historical occurrence data of sudden failures of automotive parts production equipment for each process flow subsequence, and performing statistical analysis on the historical occurrence data when the risk failure source suddenly fails through the characteristics of the failure source to obtain the corresponding historical occurrence times of each failure source characteristic; Obtain the process parameter monitoring indicators for each process flow subsequence and select the corresponding sensor types for the process parameter monitoring indicators; and obtain the number of sensors arranged corresponding to each process parameter monitoring indicator for each process flow subsequence according to the historical occurrence times corresponding to the characteristics of the failure source when the risk failure source of each process flow subsequence suddenly fails.

[0020] It should be further noted that in the specific implementation process, the process of the process visualization module constructing a full-process model of automotive parts production based on the process parameter information and automotive parts information of each process flow subsequence includes: Obtain the physical entities of the automotive parts production equipment in the physical space in the automotive parts production process of the current monitoring period, obtain the multi-source heterogeneous data sets of each physical entity in the automotive parts production process of the current monitoring period regarding process parameter information and automotive parts information, and perform preprocessing of the data format; Perform three-dimensional modeling processing on the physical entities of the automotive parts production equipment and map them to the digital space, generate twin data from the preprocessed multi-source heterogeneous data, and match the twin data with the three-dimensional model in the digital space according to the process flow assembly connection relationship of the physical entities in the physical space to obtain a digital twin model; Obtain the spatial position information of each automotive parts production equipment in the automotive parts production process, store the spatial position information in the digital space, and generate a full-process model of automotive parts production by combining the spatial position information of each automotive parts production equipment in the automotive parts production process of the current monitoring period with the digital twin model.

[0021] It should be further noted that in the specific implementation process, the process of the process parameter monitoring module performing real-time monitoring and control on the full-process model of automotive parts production according to the process parameter monitoring results of each process flow subsequence includes: Obtain the process parameter data of each process flow subsequence, set the standard index values of the process parameters and the warning threshold of the process parameter index deviation for each process flow subsequence, compare the process parameter data with the standard index values of the process parameters of each process flow subsequence to obtain the deviation values of each process parameter index, and compare the deviation values of each process parameter index with the warning threshold of the process parameter index deviation; When the deviation value of each process parameter index is greater than the warning threshold of the process parameter index deviation; set a preset time threshold and accumulate the time when the deviation value of each process parameter index is greater than the warning threshold of the process parameter index deviation; When the cumulative time is greater than or equal to the preset time threshold, stop the operation of the automotive parts production equipment for the process flow subsequence corresponding to the deviation value of the process parameter index and generate a fault warning message for the location where the automotive parts production equipment is located.

[0022] It should be further noted that in the specific implementation process, the process by which the automotive parts monitoring module determines whether the automotive parts are qualified based on the image data information and weight data information of the automotive parts in each process flow subsequence includes: Obtain the three-dimensional model of the automotive parts after processing in different process flow subsequences through the data storage module, and obtain the template image of the automotive parts after processing in different process flow subsequences based on the three-dimensional model. Extract the image features of the image data information of the automotive parts collected in the process flow subsequence of the current monitoring period, and obtain the grayscale histogram of the grayscale features of the image data information and the histogram of oriented gradients of the texture features of the image data information; Set a preset similarity threshold, and compare the similarity of the grayscale histogram and the histogram of oriented gradients of the image data information of the automotive parts collected in the process flow subsequence of the current monitoring period with the grayscale histogram and the histogram of oriented gradients of the template image of the automotive parts corresponding to this process flow subsequence; Measure the size of the automotive parts with a similarity greater than or equal to the preset similarity threshold; Mark the automotive parts with a similarity less than the preset similarity threshold as unqualified parts, stop the operation of the unqualified parts production equipment and generate a fault warning message for the location where the unqualified parts production equipment is located.

[0023] It should be further noted that in the specific implementation process, the process by which the automotive parts monitoring module measures the size of the automotive parts includes: Obtain the standard size data of the automotive parts after processing in different process flow subsequences based on the three-dimensional model. Extract the image edge features of the image data information of the automotive parts collected in the process flow subsequence of the current monitoring period through the Canny algorithm; obtain the actual size of the automotive parts through the image edge features, set a size error threshold, and compare the actual size of the automotive parts with the standard size data; Measure the weight of the automotive parts with a deviation value between the actual size and the standard size data less than or equal to the size error threshold; Mark the automotive parts with a deviation value between the actual size and the standard size data less than or equal to the size error threshold as unqualified parts, stop the operation of the unqualified parts production equipment and generate a fault warning message for the location where the unqualified parts production equipment is located.

[0024] It should be further noted that in the specific implementation process, the process of extracting the image edge features from the image data information of automotive parts and components collected in the process flow subsequence of the current monitoring period through the Canny algorithm includes: According to each pixel point in the image data information of automotive parts and components collected in the process flow subsequence of the current monitoring period Calculate the obvious gray-scale change points, and use the gradient G to represent the obvious gray-scale change points in the image. Retain the pixel points with the largest gray-scale change in the gradient direction in the image, and do not retain the others, to obtain the image edge;

[0025]

[0026] Among them, represents the obvious gray-scale change points in the image; represents each pixel point in the image in the x-axis direction; represents each pixel point in the image in the y-axis direction; represents the gradient direction; arctan is the arctangent function; It should be further noted that in the specific implementation process, the process of the automotive parts and components monitoring module measuring the weight of automotive parts and components includes: Obtain the standard weight information of the automotive parts and components after processing in different process flow subsequences through the data storage module, set the weight error threshold, and compare the weight data information of the automotive parts and components with the standard weight information; Mark the automotive parts and components with the deviation value between the weight data information and the standard weight information less than or equal to the weight error threshold as qualified parts and components; Mark the automotive parts and components with the deviation value between the weight data information and the standard weight information greater than the weight error threshold as unqualified parts and components, stop the operation of the production equipment for unqualified parts and components, and generate a fault warning information at the location of the production equipment for unqualified parts and components.

[0027] It should be further noted that in the specific implementation process, the process of the safety monitoring module visually displaying the safety warning information in the safe production process of automotive parts and components based on the full-process model of automotive parts and components production includes: Obtain the fault warning information of each process subsequence in the current monitoring period, perform zoning processing on each process subsequence according to the fault warning information, and obtain the compliance rate of process parameter data and the qualified rate of auto parts in each process subsequence area according to the fault warning information, and obtain the corresponding warning level according to the compliance rate of process parameter data and the qualified rate of auto parts and match it with each process subsequence area; Provide an implementation basis for the safety production emergency measures of auto parts in the next monitoring period according to the warning level of each process subsequence area in the safety production process of auto parts in the current monitoring period.

[0028] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An automobile spare part production safety monitoring system, comprising a monitoring center, characterized in that, The monitoring center is communicatively connected with a data acquisition module, a data storage module, a process visualization module, a process parameter monitoring module, an auto parts monitoring module, and a safety monitoring module; The data acquisition module is used to collect process parameter information and auto parts information in the sub-sequences of the auto parts production process and set the monitoring period; The data storage module is used to store historical data information during the production process of auto parts; The process visualization module is used to construct a full-process model of auto parts production based on the process parameter information and auto parts information of each sub-sequence of the production process; The process parameter monitoring module is used to perform real-time monitoring and control on the full-process model of auto parts production according to the monitoring results of the process parameters of each sub-sequence of the production process; The auto parts monitoring module is used to determine whether the auto parts are qualified according to the image data information and weight data information of the auto parts in each sub-sequence of the production process; The safety monitoring module is used to visually display the safety warning information during the safe production process of auto parts based on the full-process model of auto parts production; 2. The safety production system for monitoring automobile spare parts according to claim 1, characterized in that, The process of the data acquisition module collecting process parameter information and auto parts information in the sub-sequences of the auto parts production process includes: The data acquisition module includes a process information acquisition module and an auto parts data acquisition module; The process information acquisition module is used to obtain the process information of auto parts production in the current monitoring period, extract process features according to the process information, split the auto parts production process according to the process features, and divide it into several sub-sequences of the production process; determine the process parameter monitoring indicators of each sub-sequence of the production process according to the process features of each sub-sequence of the production process and deploy sensors, and collect process parameter data corresponding to the process parameter monitoring indicators through the sensors; The auto parts data acquisition module is used to set up auto parts image sensors and weight sensors in each sub-sequence of the production process, and collect image data information and weight data information of the auto parts to be monitored that have completed the process treatment in each sub-sequence of the production process through the auto parts image sensors and weight sensors; 3. The safety production system for monitoring automobile spare parts according to claim 2, characterized in that, The process of the process visualization module constructing a full-process model of auto parts production based on the process parameter information and auto parts information of each sub-sequence of the production process includes: Obtain the physical entities of the auto parts production equipment in the physical space in the auto parts production process of the current monitoring period, obtain the multi-source heterogeneous data set of each physical entity in the auto parts production process of the current monitoring period regarding process parameter information and auto parts information, and perform data format preprocessing; Perform three-dimensional modeling processing on the physical entities of the auto parts production equipment and map them to the digital space, generate twin data from the multi-source heterogeneous data after data format preprocessing, and match the twin data with the three-dimensional model in the digital space according to the process flow assembly connection relationship of the physical entities in the physical space to obtain the digital twin model; Obtain the spatial location information of each automotive parts production equipment in the automotive parts production process, store the spatial location information in the digital space, and generate a full-process model of automotive parts production by combining the spatial location information of each automotive parts production equipment in the automotive parts production process of the current monitoring period with the digital twin model.

4. The safety production system for monitoring automobile spare parts according to claim 3, characterized in that, The process of the process parameter monitoring module performing real-time monitoring and control on the full-process model of automotive parts production according to the process parameter monitoring results of each process subsequence includes: Obtain the process parameter data of each process subsequence, set the standard index values of the process parameters and the warning threshold of the process parameter index deviation for each process subsequence, compare the process parameter data with the standard index values of the process parameters of each process subsequence to obtain the deviation values of each process parameter index, and compare the deviation values of each process parameter index with the warning threshold of the process parameter index deviation; When the deviation value of each process parameter index is greater than the warning threshold of the process parameter index deviation; set a preset time threshold, and accumulate the time when the deviation value of each process parameter index is greater than the warning threshold of the process parameter index deviation; When the accumulated time is greater than or equal to the preset time threshold, stop the operation of the automotive parts production equipment corresponding to the process parameter index deviation value and generate a fault warning information at the location of the automotive parts production equipment.

5. The safety production system for monitoring automobile spare parts according to claim 4, characterized in that, The process of the automotive parts monitoring module judging whether the automotive parts are qualified according to the image data information and weight data information of the automotive parts in each process subsequence includes: Obtain the three-dimensional model of the automotive parts after processing in different process subsequences through the data storage module, and obtain the template image of the automotive parts after processing in different process subsequences according to the three-dimensional model. Extract the image features of the image data information of the automotive parts collected in the process subsequence of the current monitoring period, and obtain the gray histogram of the gray level features of the image data information and the histogram of oriented gradients of the texture features of the image data information; Set a preset similarity threshold, and compare the similarity of the gray histogram and the histogram of oriented gradients of the image data information of the automotive parts collected in the process subsequence of the current monitoring period with the gray histogram and the histogram of oriented gradients of the template image of the automotive parts corresponding to this process subsequence; Measure the size of the automotive parts with the similarity greater than or equal to the preset similarity threshold; Mark the automotive parts with the similarity less than the preset similarity threshold as unqualified parts, stop the operation of the unqualified parts production equipment and generate a fault warning information at the location of the unqualified parts production equipment.

6. The safety production system for monitoring automotive parts according to claim 5, characterized in that, The process of the automotive parts monitoring module measuring the size of the automotive parts includes: Obtain the standard dimension data of the auto parts after processing in different process subsequences according to the three-dimensional model, and extract the image edge features of the image data information of the auto parts collected in the process subsequence of the current monitoring period through the Canny algorithm; obtain the actual dimensions of the auto parts through the image edge features, set the dimension error threshold, and compare the actual dimensions of the auto parts with the standard dimension data; Measure the weight of the auto parts whose deviation value between the actual dimension and the standard dimension data is less than or equal to the dimension error threshold; Mark the auto parts whose deviation value between the actual dimension and the standard dimension data is less than or equal to the dimension error threshold as unqualified parts, stop the operation of the production equipment for unqualified parts, and generate a fault warning information at the location of the production equipment for unqualified parts.

7. The safety production system for monitoring automobile parts according to claim 6, characterized in that, The process of the auto parts monitoring module measuring the weight of the auto parts includes: Obtain the standard weight information of the auto parts after processing in different process subsequences through the data storage module, set the weight error threshold, and compare the weight data information of the auto parts with the standard weight information; Mark the auto parts whose deviation value between the weight data information and the standard weight information is less than or equal to the weight error threshold as qualified parts; Mark the auto parts whose deviation value between the weight data information and the standard weight information is greater than the weight error threshold as unqualified parts, stop the operation of the production equipment for unqualified parts, and generate a fault warning information at the location of the production equipment for unqualified parts.

8. A safety production monitoring system for automotive spare parts according to claim 7, characterized in that, The process of the safety monitoring module visually displaying the safety warning information of the safe production process of the auto parts based on the full-process model of auto parts production includes: Obtain the fault warning information of each process subsequence in the current monitoring period, perform zoning processing on each process subsequence according to the fault warning information, and obtain the compliance rate of process parameter data and the qualified rate of auto parts in the area of each process subsequence according to the fault warning information, and match the corresponding warning level with each process subsequence area according to the compliance rate of process parameter data and the qualified rate of auto parts; provide the execution basis for the safety production emergency measures of auto parts in the next monitoring period according to the warning level of each process subsequence area in the safe production process of auto parts in the current monitoring period.

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