Industrial data processing system, method, device, equipment, medium and product

Abstract

The present disclosure provides an industrial data processing system, method, device, equipment, medium and product, wherein the system includes: an acquisition module, the acquisition module is used to obtain the equipment status image of the factory area; an identification module is used to identify the equipment parameters of the factory equipment from the equipment status image, and the equipment parameters include the equipment type and status parameters; a transmission module is used to transmit the equipment parameters to the control module; the control module is used to adjust the parameters of the factory equipment based on the equipment parameters; a database cluster includes multiple databases, and the transmission module stores the equipment parameters in the database cluster. The system proposed in the present disclosure monitors various equipment in the factory area in real time through the acquisition module, and transmits the video signal to the identification module. The identification module identifies the type and parameters of the equipment by analyzing and processing the acquired image, thereby realizing rapid remote and non-contact acquisition of field data and improving data processing efficiency.

Description

Technical Field

[0001] The present disclosure relates to the field of automatic control, and in particular to an industrial data processing system, method, device, equipment, medium and product. Background Art

[0002] In related technologies, power plants usually use various sensors and on-site measurement equipment (such as displacement sensors, switch state sensors, flame detectors, etc.) to collect and process field data in the most intuitive way. These data are transmitted to the central control room for analysis and processing via wired or wireless means. However, the purchase, installation and maintenance costs of various special on-site measurement equipment are high, and the data standards of on-site measurement equipment from different ages and manufacturers are inconsistent. There may be delays and errors in the process of data transmission and communication, which affects real-time performance and reliability. Summary of the invention

[0003] The present disclosure provides an industrial data processing system, method, device, equipment, medium and product to solve the problems in related technologies and improve data processing efficiency and the reliability and real-time performance of detection data.

[0004] The first aspect of the present disclosure proposes an industrial data processing system, including: an acquisition module, the acquisition module is used to obtain an equipment status image of a factory area; an identification module, used to identify equipment parameters of factory equipment from the equipment status image, the equipment parameters including equipment type and status parameters; a transmission module, used to transmit the equipment parameters to a control module; the control module is used to adjust parameters of factory equipment based on the equipment parameters; a database cluster, including multiple databases, and the transmission module stores the equipment parameters in the database cluster.

[0005] In some embodiments of the present disclosure, the acquisition module includes at least a high-definition camera.

[0006] In some embodiments of the present disclosure, the identification module includes: a device identification submodule and a parameter identification submodule, the device identification submodule is used to identify the device type in the device status image, and the parameter identification submodule is used to identify the status parameters in the device status image.

[0007] The second aspect of the present disclosure proposes an industrial data processing method, which is applied to the system shown in the first aspect above, and the method includes: an acquisition module acquires an equipment status image of a factory area; based on the equipment status image, an identification module identifies equipment parameters of the factory equipment, and the equipment parameters include equipment type and status parameters; a transmission module transmits the equipment parameters to a control module; based on the equipment parameters, the control module adjusts parameters of the factory equipment; and the transmission module stores the equipment parameters in a database cluster.

[0008] In some embodiments of the present disclosure, based on the equipment status image, the identification module identifies the equipment parameters of the factory equipment, including: based on the equipment status image, the equipment sub-identification module determines a first local feature, and the parameter identification sub-module determines a second local feature, the first local feature is used to indicate the contour feature of the factory equipment, and the second local feature is used to indicate the regional feature of the equipment; based on the first local feature, the equipment identification sub-module identifies the equipment type of the factory equipment; based on the second local feature, the parameter identification sub-module identifies the equipment parameters of the factory equipment.

[0009] In some embodiments of the present disclosure, the method further includes: when the device parameter identified by the parameter identification submodule exceeds a preset range, the identification module generates an alarm message and sends the alarm message to the database cluster.

[0010] The third aspect of the present disclosure proposes an industrial data processing device, which includes: an acquisition unit for acquiring a device status image of a plant area; an identification unit for identifying device parameters of plant area devices based on the device status image, wherein the device parameters include device type and status parameters; a first transmission unit for transmitting the device parameters to a control module; and further for storing the device parameters in a database cluster. A control unit for adjusting parameters of plant area devices based on the device parameters; and a second transmission unit for storing the device parameters in a database cluster.

[0011] The fourth aspect embodiment of the present disclosure proposes an electronic device, comprising: a processor and a memory for storing a computer program that can be run on the processor, wherein the processor, when used to run the computer program, executes the method described in the second aspect embodiment of the present disclosure.

[0012] The fifth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the method described in the second aspect embodiment of the present disclosure.

[0013] The sixth aspect embodiment of the present disclosure proposes a computer program product, including a computer program, which implements the method described in the second aspect embodiment of the present disclosure when executed by a processor.

[0014] In summary, an industrial data processing system proposed in the present disclosure includes: an acquisition module, which is used to obtain the equipment status image of the factory area; an identification module, which is used to identify the equipment parameters of the factory equipment from the equipment status image, and the equipment parameters include equipment type and status parameters; a transmission module, which is used to transmit the equipment parameters to the control module; the control module is used to adjust the parameters of the factory equipment based on the equipment parameters; a database cluster, including multiple databases, and the transmission module stores the equipment parameters in the database cluster. The system proposed in the present disclosure monitors various equipment in the factory area in real time through the acquisition module, and transmits the video signal to the identification module. The identification module identifies the type and parameters of the equipment by analyzing and processing the acquired image, thereby realizing rapid remote and non-contact acquisition of field data and improving data processing efficiency.

[0015] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0017] Figure 1 An exemplary diagram of another industrial data processing system provided by an embodiment of the present disclosure;

[0018] Figure 2 A flowchart of an industrial data processing method provided by an embodiment of the present disclosure;

[0019] Figure 3 A flowchart of another industrial data processing method provided by an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram of the structure of an industrial data processing device provided in an embodiment of the present disclosure;

[0021] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] Embodiments of the present disclosure are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0023] In related technologies, power plants usually use various sensors and on-site measurement equipment (such as displacement sensors, switch state sensors, flame detectors, etc.) to collect and process field data in the most intuitive way. These data are transmitted to the central control room for analysis and processing via wired or wireless means. However, the purchase, installation and maintenance costs of various special on-site measurement equipment are high, and the data standards of on-site measurement equipment from different ages and manufacturers are inconsistent. There may be delays and errors in the process of data transmission and communication, which affects real-time performance and reliability.

[0024] The present disclosure is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] Figure 1 1 is an example diagram of an industrial data processing system provided by an embodiment of the present disclosure). Figure 1 As shown, the following modules are included.

[0026] In some embodiments, the industrial data processing system 100 may include: a collection module 110 , an identification module 120 , a transmission module 130 , a control module 140 , and a database cluster 105 .

[0027] Among them, the acquisition module 110 is used to obtain the equipment status image of the factory; the identification module 120 is used to identify the equipment parameters of the factory equipment from the equipment status image, and the equipment parameters include equipment type and status parameters; the transmission module 130 is used to transmit the equipment parameters to the control module, and the control module 140 is used to adjust the parameters of the factory equipment based on the equipment parameters. The database cluster 150 may include multiple databases for storing the equipment parameters transmitted by the transmission module 130.

[0028] In some embodiments, the equipment type is used to indicate the type of plant equipment, and the status parameter is used to indicate the operating status of the plant equipment.

[0029] Among them, the equipment type is, for example, a boiler, a closed water pump, a high-pressure heater, etc.; the state parameters are, for example: displacement parameters, switch parameters, combustion parameters, water level pressure parameters, etc.

[0030] In some embodiments, the acquisition module 110 is communicatively connected to the identification module 120 , the identification module 120 is communicatively connected to the transmission module 130 , and the transmission module 130 is communicatively connected to the control 140 and the database cluster 150 , respectively.

[0031] In some embodiments, the acquisition module 110 includes at least one or more high-definition cameras.

[0032] In some embodiments, the acquisition module 110 may be arranged around the factory equipment, or on the inner wall, outer wall, etc. of the factory equipment. The present disclosure does not limit the arrangement position of the acquisition module.

[0033] Optionally, in some embodiments, the identification module 120 may include a device identification submodule and a parameter identification submodule, wherein the device identification submodule is used to identify the device type in the device status image, and the parameter identification submodule is used to identify the status parameters in the device status image.

[0034] In summary, the industrial data processing system proposed in the present disclosure includes: an acquisition module, which is used to obtain the equipment status image of the factory area; an identification module, which is used to identify the equipment parameters of the factory equipment from the equipment status image, and the equipment parameters include equipment type and status parameters; a transmission module, which is used to transmit the equipment parameters to the control module; the control module is used to adjust the parameters of the factory equipment based on the equipment parameters; a database cluster, including multiple databases, and the transmission module stores the equipment parameters in the database cluster. The system proposed in the present disclosure monitors various equipment in the factory area in real time through the acquisition module, and transmits the video signal to the identification module. The identification module identifies the type and parameters of the equipment by analyzing and processing the acquired image, thereby realizing rapid remote and non-contact acquisition of field data and improving data processing efficiency.

[0035] Figure 2 A flowchart showing an industrial data processing method proposed in the present disclosure is shown, which is applied to Figure 1 The system shown. Figure 2 The following steps are included.

[0036] Step 201: The acquisition module obtains the equipment status image of the factory area.

[0037] In some embodiments, the acquisition module can use the high-definition camera in the module to take real-time photos of factory equipment, thereby acquiring equipment status images.

[0038] In some embodiments, the device status image may be a single frame of image or a video formed by multiple image frames, which is not limited in the present disclosure.

[0039] For example, taking a transformer as an example of a plant equipment, the equipment status image acquired by the acquisition module is, for example, an image of a dial of a transformer instrument panel taken by a high-definition camera.

[0040] Step 202: Based on the equipment status image, the recognition module recognizes equipment parameters of the factory equipment.

[0041] In some embodiments, the recognition module may extract image features of the device status image based on the device status image using a feature extraction algorithm, and then determine the device parameters according to the extracted image features.

[0042] In an optional embodiment, based on the equipment status image, the equipment sub-identification module determines a first local feature, and the parameter identification sub-module determines a second local feature, the first local feature is used to indicate a contour feature of the factory equipment, and the second local feature is used to indicate a regional feature of the equipment; further, based on the first local feature, the equipment identification sub-module identifies the equipment type of the factory equipment; based on the second local feature, the parameter identification sub-module identifies the equipment parameters of the factory equipment.

[0043] Step 203: The transmission module transmits the device parameters to the control module.

[0044] Step 204: Based on the equipment parameters, the control module adjusts the parameters of the factory equipment.

[0045] In some embodiments, the control module determines whether the operating status of the plant equipment meets expectations based on the received equipment parameters. When the allowed status of the plant equipment does not meet expectations, the control module can adjust the parameters of the plant equipment.

[0046] For example, when the control module receives information that the pressure parameter of the transformer is smaller than an expected value, the control module may increase the pressure parameter of the transformer to an expected value by adjusting parameters that can affect the pressure of the transformer.

[0047] Step 205: The transmission module stores the device parameters in the database cluster.

[0048] In some embodiments, the transmission module stores the equipment parameters identified by the identification module in a database cluster, so that subsequent factory staff can perform data analysis and processing on the factory equipment based on the equipment parameters in the database cluster.

[0049] In some embodiments, step 205 may be performed simultaneously with step 203 , or may be performed before or after step 203 , which is not limited in the present disclosure.

[0050] In summary, according to the industrial data processing method proposed in the present disclosure, which is applied to an industrial data processing system, the method includes: a collection module acquires an image of the equipment status of a factory area;

[0051] Based on the equipment status image, the recognition module identifies the equipment parameters of the plant equipment, which include equipment type and status parameters; the transmission module transmits the equipment parameters to the control module; based on the equipment parameters, the control module adjusts the parameters of the plant equipment; the transmission module stores the equipment parameters in the database cluster. The method disclosed in the present invention monitors various equipment in the plant in real time through the acquisition module, and transmits the video signal to the recognition module. The recognition module analyzes and processes the acquired image to identify the type and parameters of the equipment, thereby realizing rapid remote and non-contact acquisition of field data and improving data processing efficiency.

[0052] Figure 3 The flowchart of an industrial data processing method proposed in the present disclosure is further shown, which is applied to an industrial data processing system. Figure 1 The embodiment shown, Figure 3 The following steps are included.

[0053] Step 301: The acquisition module obtains the equipment status image of the factory area.

[0054] In some embodiments, the principle of step 301 is the same as that of the embodiment shown in step 201, and reference may be made to the above related description, which will not be repeated here.

[0055] Step 302: Based on the device state image, the device sub-recognition module determines a first local feature, and the parameter recognition sub-module determines a second local feature.

[0056] In some embodiments, the first local feature is used to indicate a contour feature of the plant equipment, and the second local feature is used to indicate a regional feature of the equipment.

[0057] In some embodiments, the device sub-identification module can use algorithms such as boundary feature method and Fourier shape descriptor method to extract the first local feature in the device status image, but is not limited to this. The present disclosure does not limit the algorithm for extracting the first local feature.

[0058] In some embodiments, the parameter identification submodule may utilize algorithms such as the geometric parameter method and the invariant moment method to extract the second local feature in the device status image, but is not limited thereto. The present disclosure does not limit the algorithm for extracting the second local feature.

[0059] In some embodiments, when the device status image includes features such as a dashboard and a parameter display screen that can directly indicate device parameters, the parameter identification submodule can determine the above features as second local features.

[0060] In some embodiments, when the device state image does not include features that can directly indicate device parameters, the remaining features used to calculate the device parameters can be used as second local features.

[0061] For example, taking the device type of condensing equipment as an example, the parameter identification submodule uses the condensing water level as the second local feature.

[0062] Step 303: Based on the first local feature, the equipment identification submodule identifies the equipment type of the factory equipment.

[0063] In some embodiments, since the shapes of the equipment in different factory areas vary greatly, that is, the contour features of the equipment in different factory areas are also different, the identification submodule determines the matching equipment type based on the determined first local feature, thereby realizing the identification of the equipment type.

[0064] Step 304: Based on the second local feature, the parameter identification submodule identifies equipment parameters of the factory equipment.

[0065] In some embodiments, when the device status image includes features such as a dashboard and a parameter display screen that can directly indicate device parameters, the parameter identification submodule can determine the above features as second local features, and then obtain the device parameters by identifying the parameter values ​​indicated by the features.

[0066] In some embodiments, when the equipment status image does not contain features that can directly indicate equipment parameters, the parameter identification submodule can determine the equipment parameters through calculation according to regional features of the factory equipment.

[0067] For example, taking the device type as condensing equipment, the parameter identification submodule takes the condensing water level as the second local feature as an example for explanation. The identification submodule can use the condensing water level as a parameter for calculation to determine the water level pressure of the condensing equipment, thereby obtaining the water level pressure parameters of the condensing equipment (ie, the equipment parameters).

[0068] Step 305: The transmission module transmits the device parameters to the control module.

[0069] In particular, when the device parameter identified by the parameter identification submodule exceeds a preset range, the identification module generates an alarm message and sends the alarm message to the database cluster.

[0070] Step 306: Based on the equipment parameters, the control module adjusts the parameters of the factory equipment.

[0071] Step 307: The transmission module stores the device parameters in the database cluster.

[0072] In some embodiments, the principles of steps 305 to 307 are the same as those of the embodiments shown in steps 203 to 205, and reference may be made to the above related descriptions, which will not be repeated here.

[0073] In summary, the industrial data processing method proposed in the present disclosure includes: the acquisition module acquires the equipment status image of the factory area; based on the equipment status image, the equipment sub-identification module determines the first local feature, and the parameter identification sub-module determines the second local feature, the first local feature is used to indicate the contour feature of the factory equipment, and the second local feature is used to indicate the regional feature of the equipment; based on the first local feature, the equipment identification sub-module identifies the equipment type of the factory equipment; based on the second local feature, the parameter identification sub-module identifies the equipment parameters of the factory equipment; the transmission module transmits the equipment parameters to the control module; based on the equipment parameters, the control module adjusts the parameters of the factory equipment; the transmission module stores the equipment parameters in the database cluster. The method proposed in the present disclosure monitors various equipment in the factory area in real time through the acquisition module, and transmits the video signal to the identification module. The identification module identifies the type and parameters of the equipment by analyzing and processing the acquired image, thereby realizing rapid remote and non-contact acquisition of field data and improving data processing efficiency.

[0074] Therefore, this solution has the following beneficial effects:

[0075] The acquisition module monitors various devices in the factory in real time and transmits the video signal to the recognition module. The recognition module analyzes and processes the acquired images to identify the type and parameters of the equipment, thereby realizing rapid remote and non-contact acquisition of on-site data and improving data processing efficiency.

[0076] Figure 4 FIG. 4 is a schematic diagram of the structure of an industrial data processing device 400 provided in an embodiment of the present disclosure. Figure 4 As shown, the industrial data processing device includes:

[0077] An acquisition unit 410 is used to acquire an equipment status image of a factory area;

[0078] An identification unit 420 is used to identify equipment parameters of the plant equipment based on the equipment status image, where the equipment parameters include equipment type and status parameters;

[0079] The first transmission unit 430 is used to transmit the device parameters to the control module; and is also used to store the device parameters in the database cluster.

[0080] A control unit 440 is used to adjust parameters of the plant equipment based on the equipment parameters;

[0081] The second transmission unit 450 is used to store the device parameters in the database cluster.

[0082] In some embodiments of the present disclosure, the identification unit 420 is also used to determine the first local feature based on the equipment status image, the equipment sub-identification module, and the parameter identification sub-module to determine the second local feature, the first local feature is used to indicate the contour feature of the factory equipment, and the second local feature is used to indicate the regional feature of the equipment; based on the first local feature, the equipment identification sub-module identifies the equipment type of the factory equipment; based on the second local feature, the parameter identification sub-module identifies the equipment parameters of the factory equipment.

[0083] In some embodiments of the present disclosure, the identification unit 420 is further configured to generate an alarm message when the device parameter identified by the parameter identification submodule exceeds a preset range, and send the alarm message to the database cluster.

[0084] Optionally, the first transmission unit 430 and the second transmission unit 450 may be the same unit or different units, which is not limited in the present disclosure.

[0085] In summary, the industrial data processing device proposed in the present disclosure includes: an acquisition unit for acquiring an equipment status image of a factory; an identification unit for identifying equipment parameters of factory equipment based on the equipment status image, wherein the equipment parameters include equipment type and status parameters; a first transmission unit for transmitting the equipment parameters to a control module; and also for storing the equipment parameters in a database cluster. A control unit for adjusting parameters of factory equipment based on the equipment parameters; and a second transmission unit for storing the equipment parameters in a database cluster. The device of the present disclosure monitors various equipment in the factory in real time and transmits video signals to the identification unit. The identification module identifies the type and parameters of the equipment by analyzing and processing the collected images, thereby realizing rapid remote and contactless collection of field data and improving data processing efficiency.

[0086] It should be noted that: the industrial data processing device provided in the above embodiment only uses the division of the above-mentioned program modules as an example when performing industrial data processing. In actual applications, the above-mentioned processing can be assigned to different program modules as needed, that is, the internal structure of the industrial data processing device is divided into different program modules to complete all or part of the processing described above.

[0087] Since the device provided in the embodiment of the present disclosure corresponds to the methods provided in the above-mentioned embodiments, the implementation of the method is also applicable to the device provided in the embodiment and will not be described in detail in this embodiment.

[0088] In the embodiments provided in the present application, the methods and devices provided in the embodiments of the present application are introduced. In order to implement the functions in the methods provided in the embodiments of the present application, the electronic device may include a hardware structure and a software module, and implement the functions in the form of a hardware structure, a software module, or a hardware structure plus a software module. A function of the functions may be executed in the form of a hardware structure, a software module, or a hardware structure plus a software module.

[0089] Figure 5 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present disclosure is shown in FIG. Figure 5 As shown, the electronic device 500 includes at least one processor 502; and a memory 501 communicatively connected to the at least one processor 502; wherein the memory 501 stores instructions executable by the at least one processor 502, and the instructions are executed by the at least one processor 502 to implement the steps of the industrial data processing method described in the embodiment of the present disclosure; or, the instructions are executed by the at least one processor 502 to implement the steps of the industrial data processing method described in the embodiment of the present disclosure.

[0090] It is understood that the electronic device also includes a communication interface. The various components in the electronic device are coupled together through a bus system. It is understood that the bus system is used to achieve connection and communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus and a status signal bus.

[0091] It can be understood that the memory 501 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAMbus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 501 described in this embodiment of the present solution is intended to include, but is not limited to, these and any other suitable types of memory.

[0092] The method disclosed in the above embodiment of the present disclosure may be applied to the processor 502, or implemented by the processor 502. The processor 502 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method may be completed by an integrated logic circuit of hardware in the processor 502 or an instruction in the form of software.

[0093] The processor 502 described above may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 502 may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this solution. A general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiments of this solution, it may be directly embodied as being executed by a hardware decoding processor, or executed by a combination of hardware and software modules in a decoding processor. The software module may be located in a storage medium, which is located in the memory 501, and the processor 502 reads the information in the memory 501 and completes the steps of the aforementioned method in combination with its hardware.

[0094] In an exemplary embodiment, the electronic device may be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), FPGA, general purpose processor, controller, MCU, microprocessor, or other electronic components to execute the aforementioned method.

[0095] The embodiment of the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the steps of the industrial data processing method described in the embodiment of the present solution when the computer instructions are executed.

[0096] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0097] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiments or examples are included in at least one embodiment or example of the present solution. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0098] Any process or method description in the flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiment of the present scheme includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present scheme belong.

[0099] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (control method), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0100] It should be understood that the various parts of the implementation of the present solution can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned implementation, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another implementation, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0101] A person skilled in the art may understand that all or part of the steps in the above-mentioned embodiment method may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0102] In addition, each functional unit in each embodiment of the present solution can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc.

[0103] Although the implementation methods of the present scheme have been shown and described above, it can be understood that the above implementation methods are exemplary and cannot be understood as limitations on the present scheme. Ordinary technicians in this field can change, modify, replace and modify the above implementation methods within the scope of the present scheme.

Claims

1. An industrial data processing system, characterized in that: The system comprises: A collection module, the collection module is used to obtain equipment status images of the factory area; An identification module, used to identify equipment parameters of plant equipment from the equipment status image, wherein the equipment parameters include equipment type and status parameters; A transmission module, used for transmitting the device parameters to a control module; A control module, used for adjusting parameters of the plant equipment based on the equipment parameters; The database cluster includes a plurality of databases, and the transmission module stores the device parameters in the database cluster.

2. The system according to claim 1, characterized in that The acquisition module at least includes a high-definition camera.

3. The system according to claim 1, characterized in that The identification module includes: a device identification submodule and a parameter identification submodule. The device identification submodule is used to identify the device type in the device status image. The parameter identification submodule is used to identify the status parameters in the device status image.

4. An industrial data processing method, characterized in that: The method is applied to the industrial data processing system according to any one of claims 1 to 3, and the method comprises: The acquisition module acquires equipment status images of the factory area; Based on the equipment status image, the identification module identifies equipment parameters of the plant equipment, wherein the equipment parameters include equipment type and status parameters; The transmission module transmits the device parameters to the control module; Based on the equipment parameters, the control module adjusts the parameters of the plant equipment; The transmission module stores the device parameters in the database cluster.

5. The method according to claim 4, characterized in that Based on the equipment status image, the identification module identifies equipment parameters of the factory equipment, including: Based on the equipment status image, the equipment sub-recognition module determines a first local feature, and the parameter recognition sub-module determines a second local feature, wherein the first local feature is used to indicate a contour feature of the plant equipment, and the second local feature is used to indicate a regional feature of the equipment; Based on the first local feature, the device identification submodule identifies the device type of the plant equipment; Based on the second local feature, the parameter identification submodule identifies equipment parameters of the factory equipment.

6. The method according to claim 4, characterized in that: The method further comprises: When the device parameter identified by the parameter identification submodule exceeds a preset range, the identification module generates an alarm message and sends the alarm message to the database cluster.

7. An industrial data processing device, characterized in that: The device comprises: An acquisition unit, used for acquiring equipment status images of a factory area; An identification unit, configured to identify equipment parameters of the plant equipment based on the equipment status image, wherein the equipment parameters include equipment type and status parameters; The first transmission unit is used to transmit the device parameters to the control module; and is also used to store the device parameters in the database cluster. A control unit, used for adjusting parameters of the plant equipment based on the equipment parameters; The second transmission unit is used to store the device parameters in a database cluster.

8. An electronic device, characterized in that: include: A processor and a memory for storing a computer program that can be run on the processor, wherein the processor is configured to execute the method according to any one of claims 4 to 6 when running the computer program.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 4-6.

10. A computer program product, characterized in that It comprises a computer program which, when executed by a processor, implements the method according to any one of claims 4 to 6.

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