Production line general control management system, storage medium and computer equipment

Abstract

The invention discloses a production line general control management system, a storage medium and computer equipment. The system comprises a real-time monitoring module which receives and processes data from various sensors and equipment on a production line in real time; the data preprocessing module is used for carrying out abnormal value detection, missing data processing and data standardization processing on the data acquired by the real-time monitoring module; the data storage module is used for storing the preprocessed data; the fault prediction module is used for performing fault prediction through the collected data; the system can provide comprehensive monitoring and management for the production process of a company, and can perform real-time monitoring and comprehensive display on data of various sensors and equipment on a production line, thereby ensuring that a user can quickly obtain required information and perform effective operation, and improving the production efficiency. And effective early warning can be carried out on equipment faults.

Description

Technical Field

[0001] The present invention relates to the field of control systems, and in particular to a production line master control management system, a storage medium and a computer device. Background Art

[0002] In the production field, when manufacturing a product, multiple steps need to be implemented. Therefore, in the entire production process of the product, multiple devices are needed for continuous coordination. Therefore, if a single device fails, it will affect other devices on the entire production line. Therefore, in order to ensure the elongation stability of the entire assembly line, the entire assembly line needs to be fully monitored and managed. Summary of the invention

[0003] The technical problem solved by the present invention is to provide a production line master control management system, which can realize comprehensive monitoring and management of the entire assembly line.

[0004] The technical solution adopted by the present invention to solve the technical problem is: a production line master control management system, including:

[0005] Real-time monitoring module: receives and processes data from various sensors and equipment on the production line in real time;

[0006] Data preprocessing module: performs outlier detection, missing data processing and data standardization on the data obtained by the real-time monitoring module;

[0007] Data storage module: stores the preprocessed data;

[0008] Fault prediction module: Fault prediction based on collected data;

[0009] Display module: displays the working status of each device in real time.

[0010] Furthermore, in the real-time monitoring module, data from sensors in various devices are collected, and in the process of collecting data, the data from various sensors are communicated and transmitted through a communication protocol;

[0011] The communication protocol rule is: the format of the data packet to be transmitted is: header identifier + data length + message type + data content + check code;

[0012] At the receiving end, a queue is used to cache received data packets, and then the data packets are extracted from the queue through the data processing thread and unpacked according to the protocol rules to obtain the data content.

[0013] Furthermore, the abnormal value detection module is to obtain multiple detection values ​​detected by the sensor and calculate the average value Mean and the standard deviation SD, and calculate the Z value of the value currently required for abnormal value detection, wherein Z=(X-Mean) / SD, wherein X is the value to be detected, and when |Z|>threshold, the value is determined to be an abnormal value;

[0014] The missing data processing method is to perform linear interpolation based on the trend of the data to fill in the missing values ​​for prediction and filling.

[0015] Furthermore, the data storage module adopts a distributed database to store large-scale data, and uses an AES symmetric encryption method to encrypt the stored data;

[0016] It also includes database backup and recovery strategies, and the database backup types include full backup, incremental backup, and differential backup.

[0017] Furthermore, it also includes a data monitoring module, which is used to monitor the accuracy of the collected data. When the data is accurate, the data is preprocessed in the data preprocessing module. If the data is inaccurate, erroneous data information is fed back.

[0018] Furthermore, it also includes a rights management module, which specifically includes the following modules:

[0019] User account management module: performs user registration, user verification and uses a strong password policy when registering users. It can also retrieve and reset passwords when they are lost.

[0020] Role and permission configuration module: define roles and assign different permissions according to different roles, including data access rights and function operation permissions;

[0021] Permission audit module: records the operation logs of all users, including operation time, operation content and operation and author information, and can quickly track the operation logs;

[0022] Multi-factor authentication module: At least two types of multi-factor authentication are performed when users log in. The authentication methods are SMS verification code, email verification code or biometric recognition;

[0023] Session management module: Set a session timeout mechanism so that users will automatically log out of the system after a period of inactivity. At the same time, users can lock the session when leaving to prevent others from accessing the system.

[0024] Furthermore, the display module includes a main interface display window, and the main interface display window includes a device display window, a log display window, a navigation bar and a status bar;

[0025] The device display window is used to display the real-time parameters of the device operation status in the form of dynamic charts and flow charts;

[0026] The log display window is used to record operation logs and system events, providing a complete view of the software running status

[0027] The navigation bar is used to quickly access various functional modules of the system;

[0028] The status bar is used to display the current operating status of the system.

[0029] The present invention also discloses a production line master control management method, including the production line master control management system described above, comprising the following steps:

[0030] Use real-time monitoring modules to receive and process data from various sensors and equipment on the production line in real time;

[0031] The data preprocessing module is used to perform outlier detection, missing data processing and data standardization on the data obtained by the real-time monitoring module;

[0032] A data storage module is used to store the preprocessed data;

[0033] A fault prediction module is used to predict faults on the collected data;

[0034] The display module is used to display the working status of each device in real time.

[0035] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned production line master control management method are implemented.

[0036] The present invention also discloses a computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; wherein:

[0037] The memory is used to store computer programs;

[0038] The processor is used to execute the steps in the above-mentioned production line master control management method by running the program stored in the memory.

[0039] The beneficial effects of the present invention are as follows: the system can provide comprehensive monitoring and management for the company's production process, and at the same time can monitor the data of various sensors and equipment on the production line in real time and display them comprehensively, thereby ensuring that users can quickly obtain the required information, perform effective operations, and effectively warn of equipment failures. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a module diagram of the production line master control management system according to an embodiment of the present application. DETAILED DESCRIPTION

[0041] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0042] The embodiment of the present application discloses a production line master control management system, including:

[0043] Real-time monitoring module: receives and processes data from various sensors and equipment on the production line in real time;

[0044] Data preprocessing module: performs outlier detection, missing data processing and data standardization on the data obtained by the real-time monitoring module;

[0045] Data storage module: stores the preprocessed data;

[0046] Fault prediction module: Fault prediction based on collected data;

[0047] Display module: displays the working status of each device in real time.

[0048] This system can provide comprehensive monitoring and management for the company's production process. At the same time, it can monitor the data of various sensors and equipment on the production line in real time and display them comprehensively, thus ensuring that users can quickly obtain the required information, perform effective operations, and effectively warn of equipment failures.

[0049] In this embodiment, the real-time monitoring module collects data from sensors in various devices. During the data collection process, the data from various sensors are communicated and transmitted through a communication protocol.

[0050] The communication protocol rule is: the format of the data packet to be transmitted is: header identifier + data length + message type + data content + check code;

[0051] At the receiving end, a queue is used to cache received data packets, and then the data packets are extracted from the queue through the data processing thread and unpacked according to the protocol rules to obtain the data content.

[0052] Specifically, the system can collect data from various industrial equipment and sensors, including but not limited to robotic arms, conveyor belts, temperature sensors, pressure sensors, etc. At the same time, since data sticking and unpacking are common phenomena in frequent data communications, in order to deal with this problem, the above-mentioned communication protocol is adopted to ensure that the receiving end can accurately parse and verify the integrity of the data packet.

[0053] In this embodiment, the abnormal value detection module is as follows: obtaining multiple detection values ​​detected by the sensor and calculating the mean value Mean and the standard deviation SD, calculating the Z value of the value currently required for abnormal value detection, where Z = (X-Mean) / SD, where X is the value to be detected, and when |Z|>threshold, the value is determined to be an abnormal value;

[0054] For example: suppose we obtain 100 temperature readings from a temperature sensor. These readings may vary due to sensor errors, environmental changes, or other factors. First, we need to calculate the basic statistics of these temperature readings. The mean value is the sum of all temperature values ​​divided by 100. The standard deviation SD can represent the degree of variation of the temperature readings. For each temperature reading, we calculate its Z value to determine its relative distance from the mean. In the temperature collection environment, we usually use the absolute value of the Z value greater than 3 as the threshold for identifying outliers. This threshold is based on the characteristics of the normal distribution, which means that the data point is outside three standard deviations of the mean. If |Z|>3, the temperature reading is considered to be an outlier and the value will be eliminated.

[0055] The method for processing missing data is to perform linear interpolation based on the trend of the data to fill in the missing values ​​for prediction and filling. Specifically, the formula: slope = (latter data - previous data) / time interval is used to obtain the trend of the data. Based on the slope trend, we can estimate the missing data.

[0056] Then the collected data is standardized to eliminate the impact of different dimensions and magnitudes, laying the foundation for subsequent data analysis.

[0057] The above operation steps can process the detected abnormal values ​​to prevent the production process from being affected by detection problems.

[0058] In this embodiment, the data storage module adopts a distributed database to store large-scale data and ensures that all collected and processed data can be persistently stored to prevent data loss.

[0059] The stored data is encrypted using the AES symmetric encryption method, and the system implements a strict access control mechanism to ensure that only authorized users can access sensitive data.

[0060] It also includes database backup and recovery strategies, and the database backup types include full backup, incremental backup, and differential backup.

[0061] Full backup refers to regular backup of the entire database, usually during business off-peak hours. Incremental backup refers to backing up only the data that has changed since the last backup, reducing the amount of backup data and time. Differential backup refers to backing up all changed data since the last full backup, which is suitable for quick recovery. The backup frequency can be determined based on the speed of data change and business needs, which can be daily, weekly or monthly. Backups should be stored in a secure location, which can be local encrypted storage or remote cloud storage service.

[0062] The setting of the above method can ensure the security of data and prevent data leakage and tampering.

[0063] In this embodiment, a data monitoring module is also included, and the data monitoring module is used to monitor the accuracy of the collected data. When the data is accurate, the data is preprocessed in the data preprocessing module. If the data is inaccurate, error data information is fed back.

[0064] The specific method of the above data monitoring is to set a mark bit in the program, assign a value to the flag bit whenever new data is received, and parse the received data at the same time. When the format of the parsed data is incorrect, or the parsed data exceeds the upper and lower limits, it is judged as erroneous data. When erroneous data is encountered, an error message is printed, and the data processing is completed. The end signal is fed back and the flag bit is cleared.

[0065] The design of the above method can realize intelligent monitoring of data, avoid interruption of data processing logic caused by erroneous data, and timely discover and deal with potential problems.

[0066] In this embodiment, a rights management module is also included, which specifically includes the following modules:

[0067] User account management module: performs user registration, user verification and uses a strong password policy when registering users. It can also retrieve and reset passwords when they are lost.

[0068] Specifically, user registration means that new users can create an account through the system registration process, including setting a username and password. User verification means that the system supports multiple account verification methods, including email verification, mobile phone verification, etc., to ensure the authenticity and security of the account.

[0069] Role and permission configuration module: define roles and assign different permissions according to different roles, including data access rights and function operation permissions;

[0070] Permission audit module: records the operation logs of all users, including operation time, operation content and operation and author information, and can quickly track the operation logs;

[0071] The above-mentioned fast tracking of operation logs refers to quickly locating the operation logs by filtering by operator, operation type and keyword;

[0072] Multi-factor authentication module: At least two types of multi-factor authentication are performed when users log in. The authentication methods are SMS verification code, email verification code or biometric recognition;

[0073] Session management module: Set a session timeout mechanism so that users will automatically log out of the system after a period of inactivity. At the same time, users can lock the session when leaving to prevent others from accessing the system.

[0074] In this method, permission management can be used to easily confirm user responsibilities, thereby ensuring the security of the system and the integrity of data.

[0075] In this embodiment, the display module includes a main interface display window, and the main interface display window includes a device display window, a log display window, a navigation bar and a status bar;

[0076] The device display window is used to display the real-time parameters of the device operating status in the form of dynamic charts and flow charts, including speed,

[0077] Real-time data of key parameters such as temperature and pressure;

[0078] The log display window is used to record operation logs and system events, provide a complete software operation status view, and help users track operation history and system status changes;

[0079] The navigation bar is used to quickly access the various functional modules of the system, including data processing, database operation, authority management, communication settings, etc.;

[0080] The status bar is used to display the current operating status of the system, including data synchronization status, system health, and any warning or error information.

[0081] This interface ensures that users can quickly obtain the required information and perform effective operations through reasonable layout and clear information hierarchy.

[0082] The present invention also discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned production line master control management system are implemented.

[0083] In addition, the computer-readable storage medium of this embodiment may adopt any combination of one or more computer-readable storage media, wherein the computer-readable storage medium includes electrical, optical, electromagnetic, infrared or semiconductor systems, devices or components, or any combination thereof.

[0084] The present invention also discloses a computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; wherein:

[0085] The memory is used to store computer programs;

[0086] The processor is used to execute the steps in the above-mentioned production line master control management system by running the program stored in the memory.

[0087] As an embodiment of the present invention, the communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0088] As an implementation mode of the present invention, the communication interface is used for communication between the above-mentioned terminal and other devices.

[0089] As an embodiment of the present invention, the memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0090] As an embodiment of the present invention, the above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0091] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific 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. The production line master control management system is characterized by: include: Real-time monitoring module: receives and processes data from various sensors and equipment on the production line in real time; Data preprocessing module: performs outlier detection, missing data processing and data standardization on the data obtained by the real-time monitoring module; Data storage module: stores the preprocessed data; Fault prediction module: Fault prediction based on collected data; Display module: displays the working status of each device in real time.

2. The production line master control management system according to claim 1, characterized in that: In the real-time monitoring module, data from sensors in various devices are collected. During the data collection process, the data from various sensors are communicated and transmitted through a communication protocol; The communication protocol rule is: the format of the data packet to be transmitted is: header identifier + data length + message type + data content + check code; At the receiving end, a queue is used to cache received data packets, and then the data packets are extracted from the queue through the data processing thread and unpacked according to the protocol rules to obtain the data content.

3. The production line master control management system according to claim 1, characterized in that: The abnormal value detection module is as follows: obtaining multiple detection values ​​detected by the sensor and calculating the mean value Mean and the standard deviation SD, calculating the Z value of the value currently required for abnormal value detection, wherein Z=(X-Mean) / SD, wherein X is the value to be detected, and when |Z|>threshold, the value is determined to be an abnormal value; The missing data processing method is to perform linear interpolation based on the trend of the data to fill in the missing values ​​for prediction and filling.

4. The production line master control management system according to claim 1, characterized in that: The data storage module adopts a distributed database to store large-scale data, and uses the AES symmetric encryption method to encrypt the stored data; It also includes database backup and recovery strategies, and the database backup types include full backup, incremental backup, and differential backup.

5. The production line master control management system according to claim 1, characterized in that: It also includes a data monitoring module, which is used to monitor the accuracy of the collected data. When the data is accurate, the data is preprocessed in the data preprocessing module. If the data is inaccurate, error data information is fed back.

6. The production line master control management system according to claim 1, characterized in that: It also includes a rights management module, which specifically includes the following modules: User account management module: performs user registration, user verification and uses a strong password policy when registering users. It can also retrieve and reset passwords when they are lost. Role and permission configuration module: define roles and assign different permissions according to different roles, including data access rights and function operation permissions; Permission audit module: records the operation logs of all users, including operation time, operation content and operation and author information, and can quickly track the operation logs; Multi-factor authentication module: At least two types of multi-factor authentication are performed when users log in. The authentication methods are SMS verification code, email verification code or biometric recognition; Session management module: Set a session timeout mechanism so that users will automatically log out of the system after a period of inactivity. At the same time, users can lock the session when leaving to prevent others from accessing the system.

7. The production line master control management system according to claim 1, characterized in that: The display module includes a main interface display window, and the main interface display window includes a device display window, a log display window, a navigation bar and a status bar; The device display window is used to display the real-time parameters of the device operation status in the form of dynamic charts and flow charts; The log display window is used to record operation logs and system events, and provide a complete software running status view; The navigation bar is used to quickly access various functional modules of the system; The status bar is used to display the current operating status of the system.

8. A production line master control management method, comprising the production line master control management system according to any one of claims 1 to 7, characterized in that: The steps include: Use real-time monitoring modules to receive and process data from various sensors and equipment on the production line in real time; The data preprocessing module is used to perform outlier detection, missing data processing and data standardization on the data obtained by the real-time monitoring module; A data storage module is used to store the preprocessed data; A fault prediction module is used to predict faults on the collected data; The display module is used to display the working status of each device in real time.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps in the production line master control management method described in claim 8 are implemented.

10. A computer device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; wherein: The memory is used to store computer programs; The processor is used to execute the steps of the production line master control management method described in claim 8 by running the program stored in the memory.

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