Intelligent factory monitoring system

Abstract

The invention provides an intelligent factory monitoring system which comprises a sensor network, a PLC control system, a monitoring center and a man-machine interaction end, the PLC control system and the man-machine interaction end communicate with the monitoring center through the Internet of Things, and the sensor network is connected with the PLC control system. According to the intelligent factory monitoring system disclosed by the invention, real-time monitoring, data analysis and intelligent control of the factory production process can be realized, and efficient, reliable and intelligent real-time monitoring, fault detection and fault processing of production equipment are realized.

Description

Technical Field

[0001] The present disclosure relates to the field of industrial automation, and in particular to an intelligent factory monitoring system. Background Art

[0002] The smart factory system is a factory operation model that realizes the automation, intelligence and informationization of the production process through technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence. Its core lies in optimizing the production process, improving production efficiency, reducing production costs and improving product quality through equipment interconnection, data collection and analysis, and intelligent decision-making.

[0003] With the continuous development of industrial automation, the monitoring requirements for factory production processes are getting higher and higher. Traditional monitoring solutions have problems such as untimely information, inaccurate data, and unintelligent management, which cannot meet the monitoring needs of industrial automation. In order to improve the production efficiency of the factory, reduce costs, ensure production safety, and meet the monitoring requirements of the industrial production process, a more intelligent, efficient, and reliable monitoring system is needed. Summary of the invention

[0004] In view of this, the present disclosure provides a smart factory monitoring system.

[0005] According to a first aspect of the present disclosure, there is provided a smart factory monitoring system, comprising: a sensor network, a PLC control system, a monitoring center and a human-computer interaction terminal, wherein the PLC control system and the human-computer interaction terminal communicate with the monitoring center via the Internet of Things respectively, and the sensor network is connected to the PLC control system;

[0006] The sensor network is used to collect the operating parameters of the production equipment in real time and send them to the PLC control system;

[0007] A PLC control system, used to obtain status signals of production equipment in real time, execute the PLC program configured by the monitoring center to control the operation of the production equipment based on the operating parameters and status signals of the production equipment, and feed back the status signals and operating parameters of the production equipment to the monitoring center; and, used to receive and execute control instructions from the monitoring center to control the operation of the production equipment;

[0008] A monitoring center is used to perform abnormality detection and fault location using the operating parameters and status signals of the production equipment, send the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the human-machine interaction terminal, generate a fault handling strategy when a fault is detected, and send the fault handling strategy to the PLC control system through the control instruction;

[0009] The human-computer interaction terminal is used to receive and display alarm information and fault sources from the monitoring center.

[0010] In some embodiments of the present disclosure, the monitoring center includes a central control machine and a server; the central control machine is used to configure the PLC program for the PLC control system, use the status signal and operating parameters of the production equipment to perform abnormality detection and fault location, send the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the server, and generate a fault handling strategy when a fault is detected and send the fault handling strategy to the PLC control system through control instructions; the server is used to send the alarm information and the fault source to the human-computer interaction end.

[0011] In some embodiments of the present disclosure, the monitoring center also includes: a database, which is connected to the central control machine, and the central control machine is also used to store the operating parameters and status signals of the production equipment, the alarm information, the fault source and the control instructions in the database.

[0012] In some embodiments of the present disclosure, the PLC control system is also used to feed back the execution results to the central control machine after receiving and executing control instructions from the monitoring center to implement fault handling for production equipment so that the central control machine can obtain the execution results of the PLC control system to form a closed-loop control.

[0013] In some embodiments of the present disclosure, the PLC control system includes: an AI module, a processor module, a DIO module and an actuator, wherein the AI ​​module is respectively connected to each sensor in the sensor network, the processor module is connected to the AI ​​module and the DIO module, and the DIO module is connected to the actuator; the AI ​​module is used to read the operating parameters collected in real time from each sensor in the sensor network and convert the operating parameters into a data format recognizable by the processor module; the processor module is used to obtain the status signal of the production equipment in real time, execute the PLC program based on the status signal of the production equipment and the operating parameters of the production equipment converted by the AI ​​module to generate control instructions for the execution structure; and receive control instructions from the monitoring center; the DIO module is used to convert the control instructions generated and received by the processor module into a format recognizable by the actuator and send them to the actuator; the actuator is used to receive the control instructions sent by the DIO module to perform corresponding physical operations to control the operation of the production equipment.

[0014] In some embodiments of the present disclosure, the DIO module is also used to obtain the execution result of the actuator and convert the execution result into a format recognizable by the processor module and then send it to the processor module; the processor module is also used to receive the execution result sent by the DIO module and send it to the central control computer of the monitoring center.

[0015] In some embodiments of the present disclosure, the PLC program includes a locally deployed lightweight fault diagnosis algorithm and a lightweight fault handling algorithm; the processor module is also used to execute the PLC program based on the operating parameters and status signals of the production equipment to achieve fault detection and fault handling of the production equipment.

[0016] In some embodiments of the present disclosure, the human-computer interaction terminal is specifically used to provide a factory monitoring interface, through which the operator's identity is authenticated, and after the identity authentication is passed, the alarm information and fault source are displayed on the factory monitoring interface.

[0017] In some embodiments of the present disclosure, the human-computer interaction terminal is further used to receive the control instructions input by the operator in the factory monitoring interface after the identity authentication is passed and send them to the monitoring center; the monitoring center is further used to forward the control instructions from the human-computer interaction terminal to the PLC control system; the PLC control system is further used to receive and execute the control instructions to realize the control of the production equipment.

[0018] In some implementations of the present disclosure, the human-computer interaction terminal includes a mobile terminal.

[0019] It can be seen from the above technical solutions that the intelligent factory monitoring system of the disclosed embodiment can realize real-time monitoring, data analysis and intelligent control of the factory production process, and realize efficient, reliable and intelligent real-time monitoring, fault detection and fault handling for production equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0021] Figure 1 A schematic diagram of the structure of a smart factory monitoring system provided by an embodiment of the present disclosure;

[0022] Figure 2 A schematic diagram of the structure of a sensor network in a smart factory monitoring system provided by an embodiment of the present disclosure;

[0023] Figure 3 A schematic diagram of the structure of a PLC control system in a smart factory monitoring system provided in an embodiment of the present disclosure;

[0024] Figure 4A schematic diagram of the structure of a monitoring center in a smart factory monitoring system provided in an embodiment of the present disclosure;

[0025] Figure 5 A schematic diagram of a human-computer interaction terminal in a smart factory monitoring system provided by an embodiment of the present disclosure;

[0026] Figure 6 A schematic diagram of the specific structure of the smart factory monitoring system provided in the embodiment of the present disclosure. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0028] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure. The singular forms "a", "said" and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0029] As used herein, the words "if," "if," and the like may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0030] There are many types of equipment involved in the factory production process, and these equipment work together to complete tasks such as manufacturing and processing. In the embodiments of the present disclosure, the various equipment involved in the factory production process is related to specific application scenarios. Herein, the various equipment involved in the factory production process is collectively referred to as production equipment, and the production equipment may include but is not limited to one or more of the following types: processing equipment, molding equipment, assembly equipment, testing equipment, conveying equipment, storage equipment, packaging equipment, energy equipment (for example, generators, transformers, etc.), environmental protection equipment, heating and cooling equipment, tools, fixtures, measuring equipment, testing equipment, etc. The specific types of production equipment are not limited in the embodiments of the present disclosure.

[0031] Figure 1 FIG. 1 shows a schematic diagram of the structure of the intelligent factory monitoring system provided by the embodiment of the present disclosure. Figure 1As shown, the smart factory system provided by the embodiment of the present disclosure includes: a sensor network 110, a programmable logic controller (PLC) control system 120, a monitoring center 130 and a human-computer interaction terminal 140.

[0032] Among them, the sensor network 110 can be used to collect the operating parameters of the production equipment in real time and send them to the PLC control system 120; the PLC control system can be used to obtain the status signal of the production equipment in real time, execute the PLC program pre-configured by the monitoring center 130 based on the operating parameters and status signals of the production equipment to control the operation of the production equipment, and feed back the status signal and operating parameters of the production equipment to the monitoring center 130, and receive and execute control instructions from the monitoring center 130 to control the operation of the production equipment; the monitoring center 130 is used to use the operating parameters and status signals of the production equipment to perform abnormality detection and fault location, and send the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the human-computer interaction terminal 140, generate a fault handling strategy when a fault is detected, and send the fault handling strategy to the PLC control system through control instructions; the human-computer interaction terminal 140 is used to receive and display the alarm information and fault source from the monitoring center 130, so as to facilitate the operator to monitor and manage the factory production process anytime and anywhere.

[0033] The smart factory monitoring system provided by the embodiments of the present invention can realize real-time monitoring, data analysis and intelligent control of the factory production process, realize efficient, intelligent and reliable monitoring, fault detection and fault handling of the industrial automation system, and effectively improve the factory's production efficiency and automation management level.

[0034] In some implementations, the PLC control system 120 and the human-machine interaction terminal 140 can communicate with the monitoring center 130 through the Internet of Things, and the sensor network 110 is connected to the PLC control system 120. By using the Internet of Things technology to achieve interconnection between various parts of the smart factory monitoring system, the scalability and flexibility of the smart factory monitoring system can be improved.

[0035] The sensor network 110 may include various types of sensors, and the operating parameters collected by the sensors may include but are not limited to temperature, pressure, flow, liquid level, voltage, current, etc.

[0036] Figure 2 FIG. 1 shows an example of the structure of the sensor network 110. Figure 2 The sensor network 110 may include, but is not limited to: a voltage transmitter, a current transformer, a temperature sensor, a pressure sensor, and a liquid level sensor, which are electrically connected to the production equipment to measure the operating parameters of the production equipment in real time.

[0037] Specifically, voltage transmitters can be used to detect the voltage of production equipment in real time to ensure that the voltage is maintained within the range required for the normal operation of the equipment. Current transformers can be used to detect the current of production equipment in real time to prevent overload and short circuit. Temperature sensors can be used to monitor the temperature of production equipment or its environment to achieve process control, product quality control, and prevent equipment from overheating. Pressure sensors can be used to detect the pressure of production equipment or its environment (for example, air pressure or hydraulic pressure) to ensure system safety and efficiency. Liquid level sensors can be used to monitor the liquid level of production equipment to determine the liquid height in containers, tanks or pipelines to manage liquid storage and prevent overflow or drying up.

[0038] In specific applications, the types of sensors in the sensor network 110 are not limited to the above five types, and may also include photoelectric sensors, flow sensors, visual sensors, etc. Through these sensors, the smart factory monitoring system can monitor and control various parameters of various devices involved in the factory production process in real time, improve production efficiency, quality and safety. The embodiments of the present disclosure do not limit the types of sensors in the sensor network 110 and their connection methods.

[0039] Figure 3 An exemplary block diagram of the PLC control system 120 is shown. Figure 3 The PLC control system 120 may include: an analog input module 122 (AI module), a processor module 121, a digital input / output module 123 (DIO module) and an actuator 124, the AI ​​module 122 is respectively connected to each sensor in the sensor network 110, the processor module 121 is connected to the AI ​​module 122 and the DIO module 123, the DIO module 123 is connected to the actuator 124, and the actuator 124 is connected to each production equipment (that is, production equipment 1, production equipment 2, production equipment 3, ..., production equipment n, where n is an integer greater than 3).

[0040] The AI ​​module 122 is used to read the operating parameters collected in real time from each sensor in the sensor network 110 and convert the operating parameters into a data format recognizable by the processor module 121. The processor module 121 can be used to obtain the status signal of the production equipment in real time, execute the PLC program based on the status signal and operating parameters of the production equipment to generate control instructions for the execution structure; and receive control instructions from the monitoring center 130. The DIO module 123 is used to convert the control instructions generated and received by the processor module 121 into a format recognizable by the actuator 124 and send it to the actuator 124. The actuator 124 can be used to receive the control instructions sent by the DIO module 123 and perform corresponding physical operations to control the production equipment (i.e., Figure 3Operation of one or more of production equipment 1, production equipment 2, production equipment 3, ..., production equipment n, where n is an integer greater than 3).

[0041] Specifically, the AI ​​module 122 can be used to read the original signal collected in real time by each sensor in the sensor network 110, which carries the operating parameters of the production equipment and is an analog signal, and convert the original signal into a digital signal recognizable by the processor module 121, such as a digital quantity (such as a switch state) and a standardized value, and then send it to the processor module 121. In other examples, the AI ​​module 122 can also perform pre-processing such as filtering and de-jittering after signal conversion to improve data reliability.

[0042] The processor module 121 in the PLC control system 120 may include one or more processor modules 121, which may be deployed in a centralized or distributed manner as required. The centralized deployment method is suitable for scenarios with simple control logic and centralized equipment, with low cost and easy debugging. The distributed deployment method is more suitable for large-scale, high real-time, and complex industrial environments that require redundancy and fault tolerance (such as intelligent manufacturing, energy pipelines, etc.).

[0043] Exemplarily, the status signal of the production equipment may include, but is not limited to, the input signal, output status, internal variables, fault codes, switching quantities, etc. of the production equipment.

[0044] The PLC program can be configured to the processor module 121 through the industrial computer of the monitoring center 130. The PLC program is stored in the memory of the processor module 121 so that the processor module 121 can realize its functions by reading the instructions in the PLC program. The PLC program runs in the processor module 121 and is periodically scanned and executed to realize real-time control of each production equipment. By configuring and optimizing the PLC program, the flexibility, reliability and efficiency of the industrial automation system can be improved to meet the ever-changing production needs.

[0045] In specific applications, PLC programs can be written using specific programming languages, such as ladder diagram, function block diagram, structured text, etc.

[0046] In some implementations, the PLC program may include a locally deployed lightweight fault diagnosis algorithm and a lightweight fault processing algorithm; the processor module 121 may also be used to execute the PLC program based on the operating parameters and status signals of the production equipment to implement fault detection and fault processing of the production equipment. Thus, some lightweight fault diagnosis algorithms may be deployed locally in the processor module 121, for example, to quickly respond to emergency shutdown signals through logical judgment, thereby reducing processing delays in the central control machine 131.

[0047] Specifically, the PLC program executed by the processor module 121 may include but is not limited to one or more of the following logics: 1) logical judgment; 2) lightweight fault diagnosis algorithm; 3) redundancy check, i.e., comparing the consistency of the operating parameters of multiple sensors to identify sensor faults; 4) lightweight fault handling algorithm; 5) production equipment status signal detection; 6) recording errors or abnormal conditions during the execution of the PLC program to provide fault diagnosis information.

[0048] Among them, the fault detection involved in the lightweight fault diagnosis algorithm may include but is not limited to one or more of the following processes: 1) threshold monitoring of the operating parameters of each production equipment (such as whether the temperature exceeds the limit, etc.); 2) detecting whether the action of the production equipment complies with the preset process, for example, whether pump B starts after valve A is opened; 3) recording the number of consecutive abnormalities through a counter and triggering a fault when the number of consecutive abnormalities reaches a predetermined threshold.

[0049] Among them, the fault handling involved in the lightweight fault handling algorithm may include but is not limited to one or more of the following processes: 1) triggering an alarm; 2) recording a fault code; 3) switching to a safe mode (such as shutdown, reduced frequency operation); 4) starting a backup device.

[0050] The logic judgment may include but is not limited to: performing Boolean operations (such as AND / OR), comparison, delayed start and / or action count based on the input state.

[0051] The DIO module 123 can realize the interaction between the processor module 121 and the actuator 124. Specifically, the DIO module 123 can be used to convert the control instructions of the processor module 121 into a digital control signal in a format suitable for driving the actuator 124 and send it to the corresponding actuator 124 (for example, activating a relay, an indicator light, a solenoid valve, etc.), receive the digital signal of the actuator 124 (for example, a binary signal of a button, a switch, etc.) and convert the digital signal into a format that can be recognized and processed by the processor module 121 and then send it to the processor module 121. The DIO module 123 can not only realize the interaction between the processor module 121 and the actuator 124, but also provide electrical isolation of input and output signals to protect the smart factory monitoring system from external electrical interference and equipment failure.

[0052] The actuator 124 may include but is not limited to a motor, a pump, a valve, a relay, a switch, a button, etc. The actuator 124 receives a control instruction and performs a corresponding physical operation (such as valve opening and closing, motor start and stop, pump flow adjustment, etc.) to achieve precise control of the production equipment. That is, the actuator is responsible for converting the control instruction of the PLC control system 120 into a physical action to directly or indirectly control the operation of the production equipment.

[0053] Furthermore, the PLC control system 120 can also be used to feed back the execution results to the central control machine 131 after receiving and executing control instructions from the monitoring center 130 to implement fault handling for production equipment so that the central control machine 131 of the monitoring center 130 can obtain the execution results of the PLC control system 120 in real time to form a closed-loop control.

[0054] Specifically, the DI / O module can also be used to obtain the execution result of the actuator 124 and convert the execution result into a format recognizable by the processor module 121 and then send it to the processor module 121; the processor module 121 can also be used to receive the execution result sent by the DIO module 123 and send it to the central control machine 131 of the monitoring center 130. In this way, closed control of the PLC control system 120 can be achieved.

[0055] In some examples, the processor module 121 can read the actual feedback signal of the actuator 124 and verify whether the control instruction is effective, and feed back the actual feedback signal of the actuator 124 and the verification result of whether the control instruction is effective as the execution result to the central control machine 131 to achieve closed-loop control.

[0056] Exemplarily, the execution process of the PLC control system 120 may include: the processor module 121 obtains the state signal of the production equipment through the DIO module 123 or other interfaces, reads the operating parameters collected in real time from the sensor through the AI ​​module 122 and converts them into digital quantities (such as switch status) or standardized values ​​(such as 4-20mA current converted to engineering unit values) that can be recognized by the processor module 121, and temporarily stores the processed operating parameters and state signals in the input image register of the PLC control system 120 for unified call by subsequent programs to ensure that the input state is consistent during program execution. The processor module 121 executes the PLC program line by line according to a preset scanning cycle (usually milliseconds) to generate control instructions (for example, control instructions such as "start the motor" and "close the valve"), writes the control instructions into the output image register, and sends the control instructions to the actuator 124 through the DIO module 123 to control the operation of the production equipment.

[0057] Figure 4 FIG. 1 shows an example of the structure of the monitoring center 130. Figure 4The monitoring center 130 may include: a central control machine 131 and a server 132; wherein the central control machine 131 is used to configure a PLC program for the PLC control system 120, use the status signal and operating parameters of the production equipment to perform abnormality detection and fault location, send the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the server 132, and generate a fault handling strategy when a fault is detected and send the fault handling strategy to the PLC control system 120 through a control instruction. The server 132 can be used to send the alarm information and the fault source to the human-computer interaction terminal 140.

[0058] An industrial computer is a rugged computer designed specifically for use in industrial environments. It has high durability and adaptability and can withstand harsh industrial environments such as high temperature, vibration, dust, and electromagnetic interference. In addition, an industrial computer may also have specific features such as expansion slots, multiple communication interfaces, and wide voltage input to meet the specific needs of industrial automation systems.

[0059] The industrial computer can be used to monitor, configure and manage the entire PLC control system 120. Specifically, the industrial computer can configure the PLC program to the processor module 121 by running dedicated software, and the dedicated software can be provided by the PLC manufacturer.

[0060] Exemplarily, the fault handling strategy may include, but is not limited to, switching to a backup device, adjusting production parameters, or other similar strategies.

[0061] Anomaly detection may include identifying abnormal conditions of production equipment through threshold comparison, trend analysis and / or machine learning models, and generating corresponding alarm information when anomalies of production equipment are identified.

[0062] Specifically, the specific implementation methods of anomaly detection may include but are not limited to one or more of the following: 1) making quick judgments based on preset thresholds or pre-configured logical rules (IF-THEN) to identify abnormal conditions of production equipment; 2) using sliding window statistics (such as Z-score anomaly detection) or dynamic time warping algorithms to identify abnormal trends in operating parameters of production equipment.

[0063] Fault location may include locating the source of the fault by combining historical data and the topological relationship of the production equipment stored in the database 133 when an abnormal situation of the production equipment is identified. For example, when the communication of the processor module 121 of a production line PLC is interrupted, the central control machine 131 may determine whether it is a module fault or a network problem by combining the status of adjacent equipment.

[0064] Specifically, the specific implementation methods of fault location may include but are not limited to: 1) Combining multi-dimensional data such as vibration spectrum, temperature curve, control signal, etc., extracting key fault features through machine learning models such as Transformer that use attention mechanism. For example, in the diagnosis of abnormal noise of a CNC machine tool spindle, the central control machine 131 integrates the high-frequency components of vibration (bearing wear characteristics) and the harmonics of the drive current (gear meshing abnormality) to lock the source of the fault. 2) Construct a knowledge graph based on the topological relationship of production equipment and the historical fault library to infer the fault propagation path. For example: when it is identified that the conveyor belt has stopped, the possible causes of the fault can be traced back through fault propagation path reasoning, including motor failure, drive power failure, and false triggering of photoelectric sensors.

[0065] The industrial computer can also be used to read data from the processor module 121 in real time, such as input status, output status, internal variables, etc., and display these data on the user interface. At the same time, the industrial computer can also send instructions to the processor module 121 to change its operation, such as modifying set points, starting or stopping processes, etc.

[0066] The industrial computer can also be used to monitor the operating status of the processor module 121, including the load, memory usage, errors and alarms of the processor module 121, which helps to discover and solve problems in a timely manner and ensure the stable operation of the smart factory monitoring system.

[0067] The industrial computer can also support remote access and control of the PLC control system 120 , so that engineers and operators can connect to the industrial computer through the network at any location to monitor and control the PLC control system 120 .

[0068] The server 132 is a central node for data processing and storage, and is responsible for receiving data from the industrial computer and sending the processed data to the human-computer interaction terminal 140. At the same time, the server 132 can also be used to receive control instructions from the human-computer interaction terminal 140 and send them to the central control computer 131.

[0069] Further, see Figure 4 The monitoring center 130 may also include a database 133, which is connected to the central control computer 131 and is used to store various data related to the factory production process. Specifically, the central control computer 131 may also be used to store the production equipment status signal, the operating parameters, alarm information, fault sources and control instructions collected in real time by the sensor network 110 into the database 133 for subsequent query and analysis.

[0070] As can be seen from the above, in the intelligent factory monitoring system of the embodiment of the present disclosure, the central control machine 131 and the processor module 121 realize fault detection and fault handling in the factory production process through hierarchical collaboration.

[0071] Furthermore, the human-machine interaction terminal 140 can be used to provide a factory monitoring interface, authenticate the operator through the factory monitoring interface, and display the alarm information and fault source on the factory monitoring interface after the identity authentication is passed. The reliability and stability of the smart factory monitoring system can be further improved through identity authentication technology.

[0072] Furthermore, the human-machine interaction terminal 140 can also be used to receive the control instructions input by the operator in the factory monitoring interface after the identity verification is passed and send them to the monitoring center 130. The monitoring center 130 is also used to forward the control instructions from the human-machine interaction terminal 140 to the PLC control system 120. The PLC control system 120 is also used to receive and execute the control instructions to achieve the control of the production equipment. Thus, the operator can use the human-machine interaction terminal 140 to achieve remote fault detection and remote fault handling for the production equipment as needed, and can also remotely control various equipment involved in the factory production process through the human-machine interaction terminal 140.

[0073] Furthermore, the human-machine interaction terminal 140 may include a mobile terminal, which may be, but is not limited to, a mobile phone, a tablet, a wearable device, a portable device, etc. The mobile terminal may provide a human-machine interaction interface, support remote monitoring, alarm reception, equipment control, etc. For example, the mobile terminal may access system data through a mobile application or a Web interface to achieve flexible management. Using a mobile terminal as the human-machine interaction terminal 140 may facilitate factory managers to monitor and manage the factory production process anytime and anywhere.

[0074] For example, Figure 5 An example diagram of the human-computer interaction terminal 140 is shown. Figure 5 The human-machine interaction terminal 140 may include but is not limited to an operator workstation, an administrator terminal and a mobile terminal. The operator workstation provides an interface for the operator to interact with the system for monitoring and controlling the production process. The administrator terminal is used to provide production data and analysis reports to managers. The mobile terminal can be used to remotely access and control production equipment.

[0075] Figure 6 The specific structural diagram of the intelligent factory monitoring system provided by the embodiment of the present disclosure is shown. Figure 6 ,The specific implementation process of the smart factory monitoring system can include:

[0076] The PLC program is configured in advance for the processor module 121 through the central control machine 131 , and the PLC program includes a lightweight fault diagnosis algorithm and a lightweight fault processing algorithm deployed locally in the processor module 121 .

[0077] The voltage transmitter, current transformer, temperature sensor, pressure sensor, and liquid level sensor in the sensor network 110 respectively collect operating parameters of the production equipment such as voltage, current, temperature, pressure, and liquid level in real time and transmit them to the AI ​​module 122. The AI ​​module 122 converts the operating parameters into a data format recognizable by the processor module 121 and sends them to the processor module 121.

[0078] The processor module 121 obtains the status signal of the production equipment in real time, executes the PLC program based on the status signal of the production equipment and the operating parameters of the production equipment converted by the AI ​​module 122 to generate control instructions for the execution structure, and receives control instructions from the monitoring center 130 at the same time, transmits the control instructions to the DIO module 123, and the DIO module 123 transmits the control instructions to the actuator 124 so that the actuator 124 performs specific physical operations (for example, switching valves, starting motors, controlling the operation of pumps, etc.) to control the operation of the production equipment. At the same time, the processor module 121 transmits the data involved in the process (for example, the operating parameters and status signals of the production equipment, etc.) to the industrial computer, and the industrial computer stores these data in the database 133 for subsequent viewing and analysis. Among them, when the processor module 121 executes the PLC program, it generates control instructions for the execution structure, and these control instructions can simultaneously realize the fault detection and fault handling of the production equipment.

[0079] After the execution of the actuator 124 is completed, the DIO module 123 obtains the execution result of the actuator 124 and converts the execution result into a format recognizable by the processor module 121 and sends it to the processor module 121. The processor module 121 receives the execution result sent by the DIO module 123 and sends it to the central control machine 131 of the monitoring center 130, so that the central control machine 131 can perform PLC program configuration or generate a fault handling strategy based on the execution result.

[0080] After the processor module 121 transmits the data involved in the process (for example, the operating parameters and status signals of the production equipment, etc.) to the industrial computer, the central control computer 131 uses the status signals and operating parameters of the production equipment to perform abnormality detection and fault location, and sends the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the server 132. When a fault is detected, it generates a fault handling strategy and sends the fault handling strategy to the PLC control system 120 through control instructions to control the operation of the production equipment to achieve fault handling of the production equipment. The server 132 sends the alarm information and the fault source to the human-computer interaction terminal 140. The human-computer interaction terminal 140 authenticates the operator and then displays the alarm information and fault source from the monitoring center 130.

[0081] In addition, the operator can input control instructions through the human-computer interaction terminal 140, and the control instructions are transmitted to the industrial computer through the server 132. The industrial computer is configured to the processor module 121. The processor module 121 sends the control instructions configured by the industrial computer to the actuator 124 through the DIO module 123 to perform specific physical operations to control the operation of the production equipment, thereby realizing the operator's remote control of the production equipment.

[0082] The technical solution provided by the present disclosure is described in detail above. The principles and implementation methods of the present disclosure are described in detail using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present disclosure. At the same time, for those skilled in the art, according to the idea of ​​the present disclosure, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present disclosure.

[0083] The above description is only a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A smart factory monitoring system, characterized in that: include: A sensor network, a PLC control system, a monitoring center and a human-computer interaction terminal, wherein the PLC control system and the human-computer interaction terminal communicate with the monitoring center via the Internet of Things respectively, and the sensor network is connected to the PLC control system; The sensor network is used to collect the operating parameters of the production equipment in real time and send them to the PLC control system; A PLC control system, used to obtain status signals of production equipment in real time, execute the PLC program configured by the monitoring center to control the operation of the production equipment based on the operating parameters and status signals of the production equipment, and feed back the status signals and operating parameters of the production equipment to the monitoring center; and, used to receive and execute control instructions from the monitoring center to control the operation of the production equipment; A monitoring center is used to perform abnormality detection and fault location using the operating parameters and status signals of the production equipment, send the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the human-machine interaction terminal, generate a fault handling strategy when a fault is detected, and send the fault handling strategy to the PLC control system through the control instruction; The human-computer interaction terminal is used to receive and display alarm information and fault sources from the monitoring center.

2. The system according to claim 1, characterized in that The monitoring center includes a central control machine and a server; The central control machine is used to configure the PLC program for the PLC control system, perform abnormality detection and fault location using the status signal and operating parameters of the production equipment, send the alarm information generated by the abnormality detection and the fault source obtained by the fault location to the server, and generate a fault handling strategy when a fault is detected and send the fault handling strategy to the PLC control system through a control instruction; The server is used to send the alarm information and the fault source to the human-computer interaction terminal.

3. The system according to claim 1 or 2, characterized in that: The monitoring center also includes: a database, which is connected to the central control machine, and the central control machine is also used to store the operating parameters and status signals of the production equipment, the alarm information, the fault source and the control instruction in the database.

4. The system according to claim 2, characterized in that The PLC control system is also used to feed back the execution results to the central control machine after receiving and executing the control instructions from the monitoring center to implement fault handling for the production equipment so that the central control machine can obtain the execution results of the PLC control system to form a closed-loop control.

5. The system according to claim 1, characterized in that The PLC control system comprises: an AI module, a processor module, a DIO module and an actuator, wherein the AI ​​module is respectively connected to each sensor in the sensor network, the processor module is connected to the AI ​​module and the DIO module, and the DIO module is connected to the actuator; The AI ​​module is used to read the operating parameters collected in real time from each sensor in the sensor network and convert the operating parameters into a data format recognizable by the processor module; A processor module, configured to obtain a status signal of a production device in real time, execute the PLC program based on the status signal of the production device and the operating parameters of the production device converted by the AI ​​module to generate a control instruction for an execution structure; and receive a control instruction from a monitoring center; The DIO module is used to convert the control instructions generated and received by the processor module into a format recognizable by the actuator and then send it to the actuator; The execution mechanism is used to receive the control instruction sent by the DIO module and execute the corresponding physical operation to control the operation of the production equipment.

6. The system according to claim 5, characterized in that The DIO module is further used to obtain the execution result of the actuator and convert the execution result into a format recognizable by the processor module and then send it to the processor module; The processor module is also used to receive the execution result sent by the DIO module and send it to the central control computer of the monitoring center.

7. The system according to claim 5, characterized in that The PLC program includes a locally deployed lightweight fault diagnosis algorithm and a lightweight fault processing algorithm; The processor module is also used to execute the PLC program based on the operating parameters and status signals of the production equipment to achieve fault detection and fault processing of the production equipment.

8. The system according to claim 1, characterized in that The human-computer interaction terminal is specifically used to provide a factory monitoring interface, through which the operator's identity is authenticated, and after the identity authentication is passed, the alarm information and fault source are displayed on the factory monitoring interface.

9. The system according to claim 8, characterized in that The human-computer interaction terminal is also used to receive the control command input by the operator on the factory monitoring interface and send it to the monitoring center after the identity verification is passed; The monitoring center is also used to forward the control instructions from the human-computer interaction terminal to the PLC control system; The PLC control system is also used to receive and execute the control instructions to achieve control of the production equipment.

10. The system according to claim 1, 8 or 9, characterized in that The human-computer interaction terminal includes a mobile terminal.

Images