A mechanical fitting machining safety data analysis system

Abstract

This invention discloses a safety data analysis system for mechanical parts processing, specifically relating to the fields of agricultural engineering and information technology. It includes a sub-region division module, a sub-region processing information collection module, a sub-region data standardization processing module, a sub-region parts processing comprehensive analysis module, a target area parts processing comprehensive analysis module, a parts processing safety comprehensive judgment module, and an interactive feedback module. This invention achieves precise region division, comprehensively monitors the target area, and collects multi-dimensional information covering machine status, production environment, product quality, energy consumption management, and safety management. Through in-depth analysis of this information, a comprehensive mathematical model is constructed to comprehensively evaluate the safety data of agricultural machinery parts processing and its impact on various aspects. This model not only improves the system's monitoring accuracy of the processing process but also enhances its ability to evaluate the system's effectiveness from multiple dimensions, thereby promoting a dual improvement in the efficiency and quality of the mechanical parts processing safety data analysis system.

Description

Technical Field

[0001] This invention relates to the fields of agricultural engineering and information technology, and more specifically, to a safety data analysis system for the processing of mechanical parts. Background Technology

[0002] Numerous safety hazards exist in the processing of agricultural machinery parts, such as improper operation, equipment malfunction, and material problems, all of which can threaten production safety. Therefore, the agricultural machinery industry has placed higher demands on safety management during the processing, requiring a system capable of real-time monitoring, early warning, and handling of safety issues.

[0003] A data analysis system for the safety of mechanical parts processing is mainly based on modern information technology, big data analysis and the actual needs of the agricultural machinery industry. It aims to improve the safety, efficiency and intelligence of the processing of agricultural machinery parts.

[0004] With the rapid development of information technology, especially the widespread application of technologies such as the Internet of Things, cloud computing, and big data, strong technical support has been provided for the research and development of safety data analysis systems for mechanical parts processing. These technologies have made data collection, transmission, storage, processing, and analysis more efficient, accurate, and intelligent.

[0005] However, in practical use, it still has some shortcomings. For example, the data collected by existing technologies is too singular, making it difficult to accurately judge the overall situation of agricultural machinery parts processing. In addition, current monitoring of the safety of agricultural machinery parts processing mainly relies on a single dimension, such as the status parameters of the processing equipment, lacking comprehensive indicators. If monitoring is based solely on a single dimension, the impact on product quality, energy consumption, safety management, and the production environment is ignored, which in turn affects the ultimate practicality, work quality, and efficiency of the machinery parts processing safety data analysis system. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, embodiments of the present invention provide a mechanical parts processing safety data analysis system, which solves the problems mentioned in the background art through the following solutions.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a mechanical parts processing safety data analysis system, comprising a sub-region division module, a sub-region processing information collection module, a sub-region data standardization processing module, a sub-region parts processing comprehensive analysis module, a target area parts processing comprehensive analysis module, a parts processing safety comprehensive judgment module, and an interactive feedback module.

[0008] Preferably, the sub-region division module is used to designate the parts processing plant to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to the production line, and label them sequentially as 1, 2, 3...i; The sub-region processing information acquisition module includes a machine operation status information acquisition unit, a production environment information acquisition unit, a product quality information acquisition unit, an energy consumption management information acquisition unit, and a safety management information acquisition unit. It is used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region data standardization processing module. The sub-region parts processing comprehensive analysis module is used to import the data collected in the sub-region processing information collection module into the mathematical models of the sub-region machine operation status coefficient, the sub-region processing environment coefficient, the sub-region safety management coefficient, the sub-region product quality coefficient, and the sub-region parts processing safety comprehensive index, and calculate them to obtain the sub-region machine operation status coefficient, sub-region processing environment coefficient, sub-region safety management coefficient, sub-region product quality coefficient, and sub-region parts processing safety comprehensive index. The target area parts processing comprehensive analysis module is used to import the data obtained from the sub-area parts processing comprehensive analysis module into the mathematical model of the target area parts processing safety comprehensive index and perform calculations to obtain the target area parts processing safety comprehensive index. The comprehensive safety judgment module for parts processing is used to compare the comprehensive safety index of parts processing in the target area with the preset value, and input the comparison result into the interactive feedback module. The interactive feedback module is used to import the comparison results into the administrator terminal. When the comparison result of the comprehensive safety index of the target area parts processing is lower than the preset value, an alarm will be issued to the administrator's equipment.

[0009] Preferably, the specific method for obtaining the comprehensive parameters of each sub-region in the sub-region processing information acquisition module is as follows: The comprehensive parameters refer to the sub-region machine speed parameters, sub-region machine component temperature suitability parameters, sub-region machine internal pressure parameters, sub-region machine vibration frequency parameters, sub-region ambient temperature parameters, sub-region ambient humidity parameters, sub-region ambient harmful gas concentration parameters, sub-region production environment noise level parameters, sub-region unit product energy consumption parameters, sub-region peak energy consumption parameters, sub-region energy saving rate parameters, sub-region product qualification rate parameters, sub-region defective product rate parameters, sub-region safety inspection frequency parameters, sub-region safety hazard rectification rate parameters, and sub-region safety training participation rate parameters. The sub-region machine speed parameter refers to the sub-region machine speed. ; The sub-region machine component temperature suitability parameter refers to the sub-region machine component temperature suitability. ; The sub-region machine internal pressure parameter refers to the sub-region machine internal pressure. ; The sub-region machine vibration frequency parameter refers to the sub-region machine vibration frequency. ; The sub-region ambient temperature parameter refers to the sub-region ambient temperature. ; The sub-region environmental humidity parameter refers to the sub-region environmental humidity. ; The sub-region environmental hazardous gas concentration parameter refers to the sub-region environmental hazardous gas concentration. ; The sub-region production environment noise level parameter refers to the sub-region production environment noise level. ; The sub-region unit product energy consumption parameter refers to the sub-region unit product energy consumption. ; The sub-region peak energy consumption parameter refers to the sub-region peak energy consumption. ; The sub-region energy saving rate parameter refers to the sub-region energy saving rate. ; The sub-region product qualification rate parameter refers to the sub-region product qualification rate. ; The sub-region defect rate parameter refers to the sub-region defect rate. ; The sub-area security check frequency parameter refers to the sub-area security check frequency. ; The sub-region safety hazard rectification rate parameter refers to the sub-region safety hazard rectification rate. ; The sub-regional security training participation rate parameter refers to the sub-regional security training participation rate. .

[0010] Preferably, the specific method for collecting the temperature suitability parameters of the machine components in the sub-region is as follows: The sub-regions are divided into sections based on each component and labeled as 1, 2, 3...n. The temperature of each component in each sub-region is then collected. The temperature suitability of each component in the sub-region is obtained. = ,in The temperature suitability of the nth component in sub-region i. The temperature of the nth component in sub-region i. The average production temperature of the nth component in sub-region i is ultimately obtained. = .

[0011] Preferably, the sub-region energy saving rate parameter specifically refers to: The degree to which energy consumption per unit of product output is reduced relative to the baseline period after energy-saving measures are implemented.

[0012] Preferably, the sub-regional safety training participation rate parameter specifically refers to: The percentage of employees in a sub-region who participated in safety training out of the total number of employees in that sub-region.

[0013] Preferably, the mathematical model for the machine operating state coefficients of the sub-region is as follows: = ,in The machine operating status coefficient of the sub-region. The machine speed in the finger area. Temperature suitability of machine components in the referential area. The internal pressure of the machine in the finger area. The vibration frequency of the machine in the sub-region. , , These refer to the average internal pressure, rotational speed, and vibration frequency under normal machine operating conditions.

[0014] Preferably, the mathematical model for the processing environment coefficient of the sub-region is as follows: = ,in The processing environment coefficient of the sub-region. The ambient temperature of the sub-region The humidity of the sub-area. The humidity of the sub-area. The concentration of harmful gases in the sub-regional environment. The noise level in the production environment of the finger area. , These refer to the average ambient temperature and humidity of the processed parts obtained from daily production practices.

[0015] Preferably, the mathematical model for the sub-region security management coefficient is as follows: = ,in The sub-area safety management coefficient The frequency of security checks in the sub-area. This refers to the participation rate in safety training in the designated area.

[0016] Preferably, the mathematical model for the product quality coefficient of the sub-region is as follows: = ,in The product quality coefficient of the sub-region. Peak energy consumption in the sub-region Energy consumption per unit of product in a sub-region Energy efficiency of the sub-region The product qualification rate of the sub-region The defect rate of a sub-region.

[0017] Preferably, the mathematical model for the comprehensive safety index of the sub-region parts processing is as follows: = ,in The comprehensive safety index of component processing in the sub-area. The machine operating status coefficient of the sub-region. The processing environment coefficient of the sub-region. The sub-area safety management coefficient The product quality coefficient of the sub-region. , , , This refers to the weighting coefficient.

[0018] Preferably, in this embodiment, it should be specifically noted that the weighting coefficient , , , It is obtained through the entropy method, and the specific calculation steps of the entropy method are as follows: Data standardization: Since the units of measurement for various indicators may differ, it is necessary to standardize the collected data to eliminate the influence of dimensions. Commonly used standardization methods include Z-score standardization and range standardization. Calculate the weight of the indicator: Calculate the weight Pij of the i-th sample value under the j-th indicator relative to the sum of all sample values ​​for that indicator. This step is the basis for subsequent calculation of information entropy; Calculate information entropy: Based on the definition and calculation formula of information entropy, calculate the information entropy ej of the j-th indicator. The smaller the information entropy, the greater the degree of variation of the indicator, and the greater the amount of information it provides. Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, i.e., dj = 1 - ej. The larger the information entropy redundancy, the more information the indicator contains, and the greater its impact on the overall evaluation. Calculate the weights: Based on the information entropy redundancy of each indicator, calculate its weight in the comprehensive evaluation. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0019] Preferably, the mathematical model for the comprehensive safety index of the target area parts processing is as follows: = ,in The comprehensive safety index for parts processing in the target area. The comprehensive safety index for the processing of parts in the finger area.

[0020] Preferably, the preset value is a warning value obtained based on industry practical experience to assess the machine operating status, processing environment, safety management, and product quality of agricultural machinery parts processing safety. When the comprehensive safety index of parts processing in the target area is lower than the preset value, it indicates that the machine operating status, processing environment, safety management, and product quality in the area are poor, and corresponding measures need to be taken to reduce the risk.

[0021] The technical effects and advantages of this invention are as follows: 1. This invention achieves real-time and comprehensive monitoring of the target area through precise regional division. The target area is divided into several sub-regions using a sub-region division module, and basic information is collected in each sub-region. This basic information includes sub-region machine speed, sub-region machine component temperature suitability, sub-region machine internal pressure, sub-region machine vibration frequency, sub-region ambient temperature, sub-region ambient humidity, sub-region ambient harmful gas concentration, sub-region production environment noise level, sub-region unit product energy consumption, sub-region peak energy consumption, sub-region energy saving rate, sub-region product qualification rate, sub-region defect rate, sub-region safety inspection frequency, sub-region safety hazard rectification rate, and sub-region safety training participation rate. This covers five major aspects of agricultural machinery parts processing: machine operating status, production environment, product quality, energy consumption management, and safety management information. Therefore, it provides a more comprehensive and detailed monitoring method for the overall performance of the machinery parts processing safety data analysis system. 2. Through in-depth analysis of the collected data, this invention establishes a mathematical model that comprehensively measures the overall situation of agricultural machinery parts processing. By establishing such a comprehensive model, this invention can better measure the overall effectiveness of the machinery parts processing safety data analysis system from different dimensions. This comprehensive evaluation method can provide a more complete understanding of the overall effectiveness of the machinery parts processing safety data analysis system in actual operation, as well as its impact on various aspects of parts processing, thereby improving the overall efficiency and quality of the machinery parts processing safety data analysis system. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the overall structure of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] As attached Figure 1 The mechanical parts processing safety data analysis system shown includes a sub-region division module, a sub-region processing information collection module, a sub-region data standardization processing module, a sub-region parts processing comprehensive analysis module, a target area parts processing comprehensive analysis module, a parts processing safety comprehensive judgment module, and an interactive feedback module.

[0025] The output of the sub-region division module is telecommunicationly connected to the input of the sub-region processing information acquisition module. The output of the sub-region processing information acquisition module is also telecommunicationly connected to the input of the sub-region data standardization processing module. The output of the sub-region data standardization processing module is telecommunicationly connected to the input of the sub-region parts processing comprehensive analysis module. The output of the sub-region parts processing comprehensive analysis module is telecommunicationly connected to the input of the target region parts processing comprehensive analysis module. The output of the target region parts processing comprehensive analysis module is telecommunicationly connected to the input of the parts processing comprehensive judgment module. The output of the parts processing comprehensive judgment module is also telecommunicationly connected to the input of the interactive feedback module.

[0026] The sub-region division module is used to designate the parts processing plant to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to the production line, and label them as 1, 2, 3...i in sequence; The sub-region processing information acquisition module includes a machine operation status information acquisition unit, a production environment information acquisition unit, a product quality information acquisition unit, an energy consumption management information acquisition unit, and a safety management information acquisition unit. It is used to collect data from the sub-region to obtain comprehensive parameters and output the comprehensive parameters to the sub-region data standardization processing module. In the preferred embodiment of this application, the specific method for obtaining the comprehensive parameters of each sub-region in the sub-region processing information acquisition module is as follows: In this embodiment, it should be specifically explained that the comprehensive parameters refer to the sub-region machine speed parameters, sub-region machine component temperature suitability parameters, sub-region machine internal pressure parameters, sub-region machine vibration frequency parameters, sub-region ambient temperature parameters, sub-region ambient humidity parameters, sub-region ambient harmful gas concentration parameters, sub-region production environment noise level parameters, sub-region unit product energy consumption parameters, sub-region peak energy consumption parameters, sub-region energy saving rate parameters, sub-region product qualification rate parameters, sub-region defective product rate parameters, sub-region safety inspection frequency parameters, sub-region safety hazard rectification rate parameters, and sub-region safety training participation rate parameters. The sub-region machine speed parameter refers to the sub-region machine speed. ; The sub-region machine component temperature suitability parameter refers to the sub-region machine component temperature suitability. ; The sub-region machine internal pressure parameter refers to the sub-region machine internal pressure. ; The sub-region machine vibration frequency parameter refers to the sub-region machine vibration frequency. ; The sub-region ambient temperature parameter refers to the sub-region ambient temperature. ; The sub-region environmental humidity parameter refers to the sub-region environmental humidity. ; The sub-region environmental hazardous gas concentration parameter refers to the sub-region environmental hazardous gas concentration. ; The sub-region production environment noise level parameter refers to the sub-region production environment noise level. ; The sub-region unit product energy consumption parameter refers to the sub-region unit product energy consumption. ; The sub-region peak energy consumption parameter refers to the sub-region peak energy consumption. ; The sub-region energy saving rate parameter refers to the sub-region energy saving rate. ; The sub-region product qualification rate parameter refers to the sub-region product qualification rate. ; The sub-region defect rate parameter refers to the sub-region defect rate. ; The sub-area security check frequency parameter refers to the sub-area security check frequency. ; The sub-region safety hazard rectification rate parameter refers to the sub-region safety hazard rectification rate. ; The sub-regional security training participation rate parameter refers to the sub-regional security training participation rate. ; In this embodiment, it should be specifically noted that the parameters of sub-region machine speed, sub-region machine component temperature suitability, sub-region machine internal pressure, sub-region machine vibration frequency, sub-region ambient temperature, sub-region ambient humidity, sub-region ambient harmful gas concentration, sub-region production environment noise level, sub-region material consumption rate, sub-region product qualification rate, sub-region defect rate, sub-region safety inspection frequency, sub-region safety hazard rectification rate, and sub-region safety training participation rate are all obtained using conventional methods or conventional equipment. For example, the sub-region machine speed parameters are collected by a tachometer, the sub-region machine vibration frequency parameters are collected by a vibration frequency sensor, and the sub-region product qualification rate and defect rate parameters are obtained from production logs. Therefore, this embodiment does not impose specific limitations. In this embodiment, it should be specifically explained that the specific method for collecting the temperature suitability parameters of the machine components in the sub-region is as follows: Divide the sub-region into sections based on each component and label them as 1, 2, 3...n. Collect the temperature of each component in each sub-region. The temperature suitability of each component in the sub-region is obtained. = ,in The temperature suitability of the nth component in sub-region i. The temperature of the nth component in sub-region i. The average production temperature of the nth component in sub-region i is ultimately obtained. = ; In this embodiment, it should be specifically noted that the sub-region energy saving rate parameter specifically refers to: The degree to which energy consumption per unit of product output is reduced relative to the baseline period after energy-saving measures are implemented; In this embodiment, it should be specifically noted that the sub-regional security training participation rate parameter refers to: The percentage of employees in a sub-region who participated in safety training out of the total number of employees in that sub-region. The sub-region data standardization processing module is used to standardize the collected data. Since the units of measurement for various indicators may be different, the Z-score standardization of the collected data is used to eliminate the influence of dimensions and output the processed comprehensive parameters to the sub-region parts processing comprehensive analysis module.

[0027] In this embodiment, it is important to note that Z-score standardization is a commonly used data preprocessing method. It converts the original data into standardized Z-scores by calculating the mean and standard deviation. This method can eliminate differences in magnitude between data points, enabling comparison and comprehensive analysis of data from different magnitudes.

[0028] The sub-region parts processing comprehensive analysis module is used to import the data collected in the sub-region processing information collection module into the mathematical models of the sub-region machine operation status coefficient, the sub-region processing environment coefficient, the sub-region safety management coefficient, the sub-region product quality coefficient, and the sub-region parts processing safety comprehensive index, and calculate them to obtain the sub-region machine operation status coefficient, sub-region processing environment coefficient, sub-region safety management coefficient, sub-region product quality coefficient, and sub-region parts processing safety comprehensive index. In this embodiment, it should be specifically explained that the mathematical model for the machine operating state coefficients of the sub-region is as follows: = ,in The machine operating status coefficient of the sub-region. The machine speed in the finger area. Temperature suitability of machine components in the referential area. The internal pressure of the machine in the finger area. The vibration frequency of the machine in the sub-region. , , These refer to the average internal pressure, rotational speed, and vibration frequency under normal machine operating conditions, respectively. In this embodiment, it should be specifically explained that the mathematical model for the sub-region processing environment coefficient is as follows: = ,in The processing environment coefficient of the sub-region. The ambient temperature of the sub-region Refers to the humidity of the sub-area. Refers to the humidity of the sub-area. The concentration of harmful gases in the sub-regional environment. The noise level in the production environment of the finger area. , These refer to the average ambient temperature and humidity of the processed parts, obtained from daily production practices. In this embodiment, it should be specifically explained that the mathematical model for the sub-region security management coefficient is as follows: = ,in The sub-area safety management coefficient The frequency of security checks in the sub-area. The participation rate in safety training in the designated area; In this embodiment, it should be specifically explained that the mathematical model for the product quality coefficient of the sub-region is as follows: = ,in The product quality coefficient of the sub-region. Peak energy consumption in the sub-region Energy consumption per unit of product in a sub-region Energy efficiency of the sub-region The product qualification rate of the sub-region The defect rate of a specific sub-region; In this embodiment, it should be specifically explained that the mathematical model for the comprehensive safety index of the sub-regional parts processing is as follows: = ,in The comprehensive safety index of component processing in the sub-area. The machine operating status coefficient of the sub-region. The processing environment coefficient of the sub-region. The sub-area safety management coefficient The product quality coefficient of the sub-region. , , , Weighting coefficient; In this embodiment, it should be specifically noted that the weighting coefficient , , , It is obtained through the entropy method, and the specific calculation steps of the entropy method are as follows: Data standardization: Since the units of measurement for various indicators may differ, it is necessary to standardize the collected data to eliminate the influence of dimensions. Commonly used standardization methods include Z-score standardization and range standardization. Calculate the weight of the indicator: Calculate the weight Pij of the i-th sample value under the j-th indicator relative to the sum of all sample values ​​for that indicator. This step is the basis for subsequent calculation of information entropy; Calculate information entropy: Based on the definition and calculation formula of information entropy, calculate the information entropy ej of the j-th indicator. The smaller the information entropy, the greater the degree of variation of the indicator, and the greater the amount of information it provides. Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, i.e., dj = 1 - ej. The larger the information entropy redundancy, the more information the indicator contains, and the greater its impact on the overall evaluation. Calculate the weights: Based on the information entropy redundancy of each indicator, calculate its weight in the comprehensive evaluation. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0029] The target area parts processing comprehensive analysis module is used to import the data obtained from the sub-area parts processing comprehensive analysis module into the mathematical model of the target area parts processing safety comprehensive index and perform calculations to obtain the target area parts processing safety comprehensive index. In this embodiment, it should be specifically explained that the mathematical model for the comprehensive safety index of the target area parts processing is as follows: = ,in The comprehensive safety index for parts processing in the target area. The comprehensive safety index for the processing of parts in the finger area.

[0030] The comprehensive safety judgment module for parts processing is used to compare the comprehensive safety index of parts processing in the target area with the preset value, and input the comparison result into the interactive feedback module. In this embodiment, it should be specifically noted that the preset value is a warning value obtained based on industry practical experience to assess the machine operating status, processing environment, safety management, and product quality of agricultural machinery parts processing safety. When the comprehensive safety index of parts processing in the target area is lower than the preset value, it indicates that the machine operating status, processing environment, safety management, and product quality in the area are poor, and corresponding measures need to be taken to reduce the risk.

[0031] The interactive feedback module is used to import the comparison results into the administrator terminal. When the comparison result of the comprehensive safety index of the target area parts processing is lower than the preset value, an alarm will be issued to the administrator's equipment. In this embodiment, it should be specifically noted that when the comparison result is lower than the preset value, the interactive feedback module will trigger an alarm function on the terminal, and issue a warning signal to the manager through sound, vibration and pop-up window and provide relevant parameters. Artificial intelligence helps the manager analyze the reasons affecting the comprehensive safety index of the target area parts processing, and further track down the specific aspects affecting the comprehensive performance, such as poor machine operation status, poor processing environment, unqualified safety management and poor product quality.

[0032] Secondly: The accompanying drawings of the embodiments disclosed in this invention only involve the structures involved in the embodiments disclosed in this invention. Other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of this invention can be combined with each other. 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.

Claims

1. A safety data analysis system for machining mechanical parts, characterized in that, include: The system includes a sub-region division module, a sub-region processing information collection module, a sub-region data standardization processing module, a sub-region parts processing comprehensive analysis module, a target area parts processing comprehensive analysis module, a parts processing safety comprehensive judgment module, and an interactive feedback module. Sub-region division module: used to mark the parts processing factory to be monitored as the target monitoring area, divide the target monitoring area into sub-monitoring areas according to the production line, and mark them as 1, 2, 3...i in sequence; Sub-region processing information acquisition module: includes machine operation status information acquisition unit, production environment information acquisition unit, product quality information acquisition unit, energy consumption management information acquisition unit and safety management information acquisition unit, used to collect data from sub-regions to obtain comprehensive parameters and output the comprehensive parameters to sub-region data standardization processing module; The sub-region parts processing comprehensive analysis module is used to import and calculate the data collected in the sub-region processing information collection module into the mathematical models of the sub-region machine operation status coefficient, sub-region processing environment coefficient, sub-region safety management coefficient, sub-region product quality coefficient, and sub-region parts processing safety comprehensive index, and obtain the sub-region machine operation status coefficient, sub-region processing environment coefficient, sub-region safety management coefficient, sub-region product quality coefficient, and sub-region parts processing safety comprehensive index. Target Area Parts Processing Comprehensive Analysis Module: This module imports the data obtained from the sub-area parts processing comprehensive analysis module into the mathematical model of the target area parts processing safety comprehensive index and performs calculations to obtain the target area parts processing safety comprehensive index. Parts processing safety comprehensive judgment module: It is used to compare the comprehensive safety index of parts processing in the target area with the preset value and input the comparison result into the interactive feedback module; Interactive feedback module: Used to import comparison results into the administrator terminal. When the comparison result of the comprehensive safety index of the target area parts processing is lower than the preset value, an alarm will be issued to the administrator's equipment.

2. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The specific method for obtaining the comprehensive parameters of each sub-region in the sub-region processing information acquisition module is as follows: The comprehensive parameters refer to the sub-region machine speed parameters, sub-region machine component temperature suitability parameters, sub-region machine internal pressure parameters, sub-region machine vibration frequency parameters, sub-region ambient temperature parameters, sub-region ambient humidity parameters, sub-region ambient harmful gas concentration parameters, sub-region production environment noise level parameters, sub-region unit product energy consumption parameters, sub-region peak energy consumption parameters, sub-region energy saving rate parameters, sub-region product qualification rate parameters, sub-region defective product rate parameters, sub-region safety inspection frequency parameters, sub-region safety hazard rectification rate parameters, and sub-region safety training participation rate parameters. The sub-region machine speed parameter refers to the sub-region machine speed. ; The sub-region machine component temperature suitability parameter refers to the sub-region machine component temperature suitability. ; The sub-region machine internal pressure parameter refers to the sub-region machine internal pressure. ; The sub-region machine vibration frequency parameter refers to the sub-region machine vibration frequency. ; The sub-region ambient temperature parameter refers to the sub-region ambient temperature. ; The sub-region environmental humidity parameter refers to the sub-region environmental humidity. ; The sub-region environmental hazardous gas concentration parameter refers to the sub-region environmental hazardous gas concentration. ; The sub-region production environment noise level parameter refers to the sub-region production environment noise level. ; The sub-region unit product energy consumption parameter refers to the sub-region unit product energy consumption. ; The sub-region peak energy consumption parameter refers to the sub-region peak energy consumption. ; The sub-region energy saving rate parameter refers to the sub-region energy saving rate. ; The sub-region product qualification rate parameter refers to the sub-region product qualification rate. ; The sub-region defect rate parameter refers to the sub-region defect rate. ; The sub-area security check frequency parameter refers to the sub-area security check frequency. ; The sub-region safety hazard rectification rate parameter refers to the sub-region safety hazard rectification rate. ; The sub-regional security training participation rate parameter refers to the sub-regional security training participation rate. .

3. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The mathematical model for the machine operating state coefficients in the sub-region is as follows: = ,in The machine operating status coefficient of the sub-region. The machine speed in the finger area. Temperature suitability of machine components in the referential area. The internal pressure of the machine in the finger area. The vibration frequency of the machine in the sub-region. , , These refer to the average internal pressure, rotational speed, and vibration frequency under normal machine operating conditions.

4. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The mathematical model for the processing environment coefficient of the sub-region is as follows: = ,in The processing environment coefficient of the sub-region. The ambient temperature of the sub-region Refers to the humidity of the sub-area. Refers to the humidity of the sub-area. The concentration of harmful gases in the sub-regional environment. The noise level in the production environment of the finger area. , These refer to the average ambient temperature and humidity of the processed parts obtained from daily production practices.

5. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The mathematical model for the sub-region security management coefficient is as follows: = ,in The sub-area safety management coefficient The frequency of security checks in the sub-area. This refers to the participation rate in safety training in the designated area.

6. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The mathematical model for the product quality coefficient of the sub-region is as follows: = ,in The product quality coefficient of the sub-region. Peak energy consumption in the sub-region Energy consumption per unit of product in a sub-region Energy efficiency of the sub-region The product qualification rate of the sub-region The defect rate of a sub-region.

7. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The mathematical model for the comprehensive safety index of the sub-regional parts processing is as follows: = ,in The comprehensive safety index of component processing in the sub-area. The machine operating status coefficient of the sub-region. The processing environment coefficient of the sub-region. The sub-area safety management coefficient The product quality coefficient of the sub-region. , , , This refers to the weighting coefficient.

8. The mechanical parts processing safety data analysis system according to claim 1, characterized in that: The mathematical model for the comprehensive safety index of parts processing in the target area is as follows: = ,in The comprehensive safety index for parts processing in the target area. The comprehensive safety index for the processing of parts in the finger area.

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