CN115037766B - Industrial equipment Internet of things data acquisition method and device - Google Patents
Industrial equipment Internet of things data acquisition method and device Download PDFInfo
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Abstract
The invention relates to the technical field of data acquisition, and particularly discloses a method and a device for acquiring data of an industrial device Internet of things, wherein the method comprises the steps of establishing a connection channel with each point in an Internet of things network, and acquiring state data of each point based on the connection channel; randomly intercepting network data packets in each connecting channel, detecting the network data packets, and determining transmission parameters of each point location; determining a motion instruction according to the transmission parameters, and sending the motion instruction to a mobile terminal; and receiving scene data fed back by the mobile terminal in real time, and counting the scene data and the state data to obtain acquisition data of each point bit. According to the method, the state data of each point location is received, the transmission process is analyzed and monitored, the mobile terminal is controlled to acquire a line image according to the analysis and monitoring result, and then the data of each point location is acquired from multiple dimensions, so that the point location state can be reflected more truly and completely.
Description
Technical Field
The invention relates to the technical field of data acquisition, in particular to a method and a device for acquiring data of industrial equipment Internet of things.
Background
The industrial Internet of things is characterized in that various acquisition and control sensors or controllers with sensing and monitoring capabilities, mobile communication, intelligent analysis and other technologies are continuously integrated into various links of an industrial production process, so that the manufacturing efficiency is greatly improved, the product quality is improved, the product cost and the resource consumption are reduced, and finally the traditional industry is improved to an intelligent new stage. From the application form, the application of the industrial Internet of things has the characteristics of instantaneity, automation, embedded (software), security, information intercommunication and interconnection and the like.
It can be thought that various microprocessors in the industrial internet of things are numerous, if the state of the industrial internet of things is required to be analyzed, the states of the various microprocessors need to be acquired, but the existing acquisition process is to install information acquisition equipment in the microprocessors directly, receive data acquired by the information acquisition equipment and store the data; the method is convenient and quick, has high data cost performance, but can only measure the 'internal' state of the microprocessor from the system perspective, and does not relate to the 'external' state.
Disclosure of Invention
The invention aims to provide a method and a device for acquiring data of industrial equipment Internet of things, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
an industrial equipment internet of things data acquisition method, the method comprising:
establishing a connection channel with each point in the internet of things network, and acquiring state data of each point based on the connection channel; wherein, the status data is sent in a data packet format;
randomly intercepting network data packets in each connecting channel, obtaining the transmission time of the network data packets, and classifying the network data packets according to the transmission time;
counting the number of different types of network data packets in the same connecting channel, and determining transmission parameters of each point location according to the counting result;
determining a motion instruction according to the transmission parameters, and sending the motion instruction to a mobile terminal;
and receiving scene data fed back by the mobile terminal in real time, and counting the scene data and the state data to obtain acquisition data of each point bit.
As a further scheme of the invention: the step of establishing a connection channel with each point in the internet of things network and acquiring the state data of each point based on the connection channel comprises the following steps:
establishing a connection channel with each point in the internet of things network, and sequentially acquiring task linked lists of each point; the task linked list contains time items and task items;
reading task items in the task linked list, and acquiring time items corresponding to the task items to determine data extraction frequency;
acquiring all data tags of the same point location, and extracting a target tag from the data tags according to the task item;
and acquiring state data of the point location based on the data extraction frequency and the target tag.
As a further scheme of the invention: the step of obtaining the state data of the point location based on the data extraction frequency and the target tag comprises the following steps:
performing weight assignment on other tags in the target tag and the data tag;
distributing the data extraction frequency according to the weight assignment result;
acquiring data corresponding to each data tag in the point location based on the allocated data extraction frequency;
and counting the data corresponding to each data tag to obtain state data.
As a further scheme of the invention: the step of counting the number of different types of network data packets in the same connecting channel and determining the transmission parameters of each point location according to the counting result comprises the following steps:
counting the number of different types of network data packets within a preset time range to obtain a transmission array; wherein, the subscript of the transmission array and the type of the network data packet are in a mapping relation, and the value of the transmission array is the number;
determining coordinate points in a preset coordinate system according to the transmission array, and fitting the coordinate points to obtain a transmission curve;
and determining a transmission function according to the transmission curve, and determining transmission parameters according to the transmission function.
As a further scheme of the invention: the step of determining a motion instruction according to the transmission parameter and sending the motion instruction to a mobile terminal comprises the following steps:
determining the abnormal value of each point location according to the transmission parameters, and acquiring the position data of the point location when the abnormal value reaches a preset abnormal threshold;
acquiring position data of a mobile terminal, and determining a motion area according to the position data of the point location and the position data of the mobile terminal;
acquiring size data of a mobile terminal, generating a segmentation grid according to the size data, and segmenting the motion region according to the segmentation grid to obtain a motion region containing the segmentation grid;
and determining a traveling path according to the motion area containing the segmentation grid, determining a motion instruction according to the traveling path, and sending the motion instruction to a mobile terminal.
As a further scheme of the invention: the step of determining a travel path according to the motion area containing the segmentation grid comprises the following steps:
reading and displaying a motion area containing a segmentation grid, opening a touch screen signal receiving port containing an input mode, and obtaining a touch screen signal; wherein the input modes include a travel path input mode and a virtual wall input mode;
when the input mode is a travel path input mode, determining a travel path according to the touch screen signal;
and when the input mode is a virtual wall input mode, determining a virtual wall according to the touch screen signal, and determining a travelling path according to the virtual wall and the movement area.
As a further scheme of the invention: the step of acquiring scene data by the mobile terminal comprises the following steps:
reading the position data of the point location and the position data of the mobile terminal, and calculating the distance and the direction in real time according to the position data of the point location and the position data of the mobile terminal;
determining an acquisition point according to the distance and a preset acquisition frequency;
when the position data of the mobile terminal is overlapped with the acquisition point, adjusting the shooting angle of the mobile terminal according to the direction to acquire a scene image;
performing contour recognition on the scene image, and calculating the image duty ratio of the point location area;
marking the scene image when the image duty ratio reaches a preset duty ratio threshold;
and counting the marked scene images, and inputting a preset data extraction model to obtain scene data.
The technical scheme of the invention also provides an industrial equipment internet of things data acquisition device, which comprises:
the system comprises a state data acquisition module, a state data processing module and a state data processing module, wherein the state data acquisition module is used for establishing a connection channel with each point in the Internet of things network and acquiring state data of each point based on the connection channel; wherein, the status data is sent in a data packet format;
the data packet classification module is used for randomly intercepting network data packets in each connection channel, acquiring the transmission time of the network data packets and classifying the network data packets according to the transmission time;
the transmission parameter calculation module is used for counting the number of different types of network data packets in the same connecting channel and determining the transmission parameters of each point location according to the counting result;
the motion instruction determining module is used for determining a motion instruction according to the transmission parameters and sending the motion instruction to the mobile terminal;
and the data induction module is used for receiving the scene data fed back by the mobile terminal in real time, and counting the scene data and the state data to obtain the acquisition data of each point bit.
As a further scheme of the invention: the status data acquisition module includes:
the task linked list acquisition unit is used for establishing a connection channel with each point in the Internet of things network and sequentially acquiring task linked lists of each point; the task linked list contains time items and task items;
the frequency determining unit is used for reading task items in the task linked list, acquiring time items corresponding to the task items and determining data extraction frequency;
the tag extraction unit is used for acquiring all the data tags of the same point location and extracting target tags from the data tags according to the task item;
and the data positioning and extracting unit is used for acquiring the state data of the point location based on the data extraction frequency and the target tag.
As a further scheme of the invention: the data positioning and extracting unit comprises:
the weight assignment subunit is used for carrying out weight assignment on the target label and other labels in the data label;
an allocation subunit, configured to allocate the data extraction frequency according to a weight assignment result;
an acquisition subunit, configured to acquire data corresponding to each data tag in the point location based on the allocated data extraction frequency;
and the statistics subunit is used for counting the data corresponding to each data tag to obtain state data.
Compared with the prior art, the invention has the beneficial effects that: according to the method, the state data of each point location is received, the transmission process is analyzed and monitored, the mobile terminal is controlled to acquire a line image according to the analysis and monitoring result, and then the data of each point location is acquired from multiple dimensions, so that the point location state can be reflected more truly and completely.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present invention.
Fig. 1 is a flow chart diagram of an industrial equipment internet of things data acquisition method.
Fig. 2 is a first sub-flowchart of an industrial device internet of things data collection method.
Fig. 3 is a second sub-flowchart of the data acquisition method of the internet of things of the industrial device.
Fig. 4 is a third sub-flowchart of the data acquisition method of the internet of things of the industrial device.
Fig. 5 is a block diagram of the composition structure of the data acquisition device of the internet of things of the industrial equipment.
Fig. 6 is a block diagram of the structure of a status data acquisition module in the data acquisition device of the internet of things of the industrial equipment.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1
Fig. 1 is a flow chart of an industrial equipment internet of things data acquisition method, in an embodiment of the invention, the method includes steps S100 to S500:
step S100: establishing a connection channel with each point in the internet of things network, and acquiring state data of each point based on the connection channel; wherein, the status data is sent in a data packet format;
each point of the internet of things corresponds to each microprocessor with a data transmission function, and the microprocessors are collectively called as each point of the internet of things; the data generated by these microprocessors is the status data.
Step S200: randomly intercepting network data packets in each connecting channel, obtaining the transmission time of the network data packets, and classifying the network data packets according to the transmission time;
during the transmission of data, the data is not transmitted continuously, but is transmitted in a 'granular' form; in the technical scheme of the invention, a transmission mode with larger granularity is adopted, namely, a microprocessor packs data and transmits the packed data to a general control center; it should be noted that the amount of data packed is not necessarily the same, and it is often referenced to time, i.e., packed once in a certain time, or packed by some special character information;
step S300: counting the number of different types of network data packets in the same connecting channel, and determining transmission parameters of each point location according to the counting result;
the packed network data packet is transmitted in the connecting channels, and when the transmission speed of each connecting channel is not greatly fluctuated, the transmission process can reflect the state of each point position;
step S400: determining a motion instruction according to the transmission parameters, and sending the motion instruction to a mobile terminal;
step S500: receiving scene data fed back by a mobile terminal in real time, and counting the scene data and the state data to obtain acquisition data of each point bit;
after the states of the points are obtained, the points with problems can be determined according to the states of the points, the points with problems are obtained, the data of the points are further obtained through the mobile terminal with the mobile function, the supplementary data of the points can be obtained, the supplementary data and the state data can reflect the conditions of the points from two dimensions, and the supplementary data and the state data are combined to be used for collecting the points.
Fig. 2 is a first sub-flowchart of an industrial device internet of things data collection method, wherein the step of establishing a connection channel with each point in the internet of things network and obtaining status data of each point based on the connection channel includes steps S101 to S104:
step S101: establishing a connection channel with each point in the internet of things network, and sequentially acquiring task linked lists of each point; the task linked list contains time items and task items;
step S102: reading task items in the task linked list, and acquiring time items corresponding to the task items to determine data extraction frequency;
step S103: acquiring all data tags of the same point location, and extracting a target tag from the data tags according to the task item;
step S104: and acquiring state data of the point location based on the data extraction frequency and the target tag.
Step S101 to step S104 specifically limit the acquisition process of the state data, firstly, determining a task linked list of each point position, wherein the generated state data are different when the point positions are in different tasks; then, calculating the processing time of the task according to the time item, and determining the data extraction frequency according to the processing time, wherein the aim of the process is to prevent excessive extracted data, because the processing time of some tasks is long, if the data extraction frequency is unchanged, the state number corresponding to the task is large, the system hopes that the extracted state data is as uniform as possible, and the state data corresponding to the task with longer time is more but not excessive; and finally, determining the importance of the point location data according to the task item, and distributing the data extraction frequency according to the importance so as to acquire the state data.
As a preferred embodiment of the present invention, the step of obtaining the status data of the point location based on the data extraction frequency and the target tag includes:
performing weight assignment on other tags in the target tag and the data tag;
distributing the data extraction frequency according to the weight assignment result;
acquiring data corresponding to each data tag in the point location based on the allocated data extraction frequency;
and counting the data corresponding to each data tag to obtain state data.
The above defines a process of extracting state data, in which each point corresponds to a microprocessor, and the data generated by the microprocessor has a plurality of kinds, some are important, some are not so important, the importance is determined by a data tag, the data extraction frequency of the point is fixed, the data extraction frequency is the amount of state data extracted in a unit time, and the data extraction frequency is allocated according to the data tag.
Fig. 3 is a second sub-flowchart of an industrial device internet of things data collection method, wherein the step of counting the number of different types of network data packets in the same connection channel and determining transmission parameters of each point location according to the counted result includes steps S301 to S303:
step S301: counting the number of different types of network data packets within a preset time range to obtain a transmission array; wherein, the subscript of the transmission array and the type of the network data packet are in a mapping relation, and the value of the transmission array is the number;
step S302: determining coordinate points in a preset coordinate system according to the transmission array, and fitting the coordinate points to obtain a transmission curve;
step S303: and determining a transmission function according to the transmission curve, and determining transmission parameters according to the transmission function.
The judging process of the transmission parameters is simpler, namely, the type of the data packet passing through the connecting channel and the quantity under the type are judged within a preset time range, the type of the data packet and the quantity under the type are stored by a transmission array, coordinate points are determined according to the transmission array, a transmission curve and a transmission function corresponding to the transmission curve can be determined according to a list-point tracing method, and the transmission parameters can be determined by analyzing some mathematical properties of the function.
Fig. 4 is a third sub-flowchart of the data collection method of the internet of things of the industrial device, and the step of determining a motion instruction according to the transmission parameter and sending the motion instruction to the mobile terminal includes steps S401 to S404:
step S401: determining the abnormal value of each point location according to the transmission parameters, and acquiring the position data of the point location when the abnormal value reaches a preset abnormal threshold;
step S402: acquiring position data of a mobile terminal, and determining a motion area according to the position data of the point location and the position data of the mobile terminal;
step S403: acquiring size data of a mobile terminal, generating a segmentation grid according to the size data, and segmenting the motion region according to the segmentation grid to obtain a motion region containing the segmentation grid;
step S404: and determining a traveling path according to the motion area containing the segmentation grid, determining a motion instruction according to the traveling path, and sending the motion instruction to a mobile terminal.
Step S401 to step S404 specifically limit the control process of the mobile terminal, and the principle is that the motion instruction is adjusted so as to control the mobile terminal; firstly, identifying transmission parameters, determining an abnormal value of a certain point, and acquiring position data of the point when the point is abnormal enough as a destination; then, position data of the mobile terminal is acquired as an initial place, and a travel path is determined according to the initial place and the destination, so that a working instruction can be determined.
Specifically, the determining process of the travelling path is to segment the moving area according to the size of the moving end, and then connect the small area obtained by segmentation to determine the travelling path.
As a preferred embodiment of the present invention, the step of determining the travel path according to the motion area including the segmentation grid includes:
reading and displaying a motion area containing a segmentation grid, opening a touch screen signal receiving port containing an input mode, and obtaining a touch screen signal; wherein the input modes include a travel path input mode and a virtual wall input mode;
when the input mode is a travel path input mode, determining a travel path according to the touch screen signal;
and when the input mode is a virtual wall input mode, determining a virtual wall according to the touch screen signal, and determining a travelling path according to the virtual wall and the movement area.
The above content is an expansion of the technical scheme of the invention, improves the interactivity with users, and the users can participate in the path planning process, on one hand, the users can directly prescribe the running path, and of course, the running path is an initial path, and in the running process, the running path is updated when encountering obstacles; on the other hand, the user may set a virtual wall, i.e. the user sets some virtual obstacles, thereby indirectly adjusting the movement of the device.
As a preferred embodiment of the present invention, the step of obtaining scene data by the mobile terminal includes:
reading the position data of the point location and the position data of the mobile terminal, and calculating the distance and the direction in real time according to the position data of the point location and the position data of the mobile terminal;
determining an acquisition point according to the distance and a preset acquisition frequency;
when the position data of the mobile terminal is overlapped with the acquisition point, adjusting the shooting angle of the mobile terminal according to the direction to acquire a scene image;
performing contour recognition on the scene image, and calculating the image duty ratio of the point location area;
marking the scene image when the image duty ratio reaches a preset duty ratio threshold;
and counting the marked scene images, and inputting a preset data extraction model to obtain scene data.
The acquisition point is the point at which the image is acquired, and at the acquisition point, the hardware equipment for acquiring the image starts to work; the image acquisition process needs to adjust the angle and aim at the point location, and then the scene image is acquired; under the condition of fixed image magnification, the point location areas have different duty ratios in the scene images along with the change of the distance, and the images with the too large or too small duty ratio have little reference meaning and are invalid images which need to be removed.
Example 2
Fig. 5 is a block diagram of a composition structure of an internet of things data acquisition device of an industrial device, in an embodiment of the present invention, an internet of things data acquisition device of an industrial device, the device 10 includes:
the state data acquisition module 11 is configured to establish a connection channel with each point in the internet of things network, and acquire state data of each point based on the connection channel; wherein, the status data is sent in a data packet format;
the data packet classification module 12 is configured to randomly intercept network data packets in each connection channel, obtain transmission time of the network data packets, and classify the network data packets according to the transmission time;
the transmission parameter calculation module 13 is used for counting the number of different types of network data packets in the same connection channel and determining the transmission parameters of each point location according to the counting result;
a motion instruction determining module 14, configured to determine a motion instruction according to the transmission parameter, and send the motion instruction to a mobile terminal;
and the data induction module 15 is used for receiving the scene data fed back by the mobile terminal in real time, and counting the scene data and the state data to obtain the acquisition data of each point bit.
Fig. 6 is a block diagram of the composition and structure of a status data acquisition module 11 in an internet of things data acquisition device of an industrial device, where the status data acquisition module 11 includes:
a task linked list obtaining unit 111, configured to establish a connection channel with each point in the internet of things network, and sequentially obtain task linked lists of each point; the task linked list contains time items and task items;
a frequency determining unit 112, configured to read task items in the task linked list, obtain time items corresponding to the task items, and determine a data extraction frequency;
a tag extraction unit 113, configured to obtain all data tags at the same point location, and extract a target tag from the data tags according to the task item;
a data positioning extraction unit 114, configured to obtain status data of the point location based on the data extraction frequency and the target tag.
Further, the data positioning and extracting unit 114 includes:
the weight assignment subunit is used for carrying out weight assignment on the target label and other labels in the data label;
an allocation subunit, configured to allocate the data extraction frequency according to a weight assignment result;
an acquisition subunit, configured to acquire data corresponding to each data tag in the point location based on the allocated data extraction frequency;
and the statistics subunit is used for counting the data corresponding to each data tag to obtain state data.
The functions which can be realized by the industrial equipment Internet of things data acquisition method are all completed by computer equipment, the computer equipment comprises one or more processors and one or more memories, at least one program code is stored in the one or more memories, and the program code is loaded and executed by the one or more processors to realize the industrial equipment Internet of things data acquisition method.
The processor takes out instructions from the memory one by one, analyzes the instructions, then completes corresponding operation according to the instruction requirement, generates a series of control commands, enables all parts of the computer to automatically, continuously and cooperatively act to form an organic whole, realizes the input of programs, the input of data, the operation and the output of results, and the arithmetic operation or the logic operation generated in the process is completed by the arithmetic unit; the Memory comprises a Read-Only Memory (ROM) for storing a computer program, and a protection device is arranged outside the Memory.
For example, a computer program may be split into one or more modules, one or more modules stored in memory and executed by a processor to perform the present invention. One or more of the modules may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program in the terminal device.
It will be appreciated by those skilled in the art that the foregoing description of the service device is merely an example and is not meant to be limiting, and may include more or fewer components than the foregoing description, or may combine certain components, or different components, such as may include input-output devices, network access devices, buses, etc.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is the control center of the terminal device described above, and which connects the various parts of the entire user terminal using various interfaces and lines.
The memory may be used for storing computer programs and/or modules, and the processor may implement various functions of the terminal device by running or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as an information acquisition template display function, a product information release function, etc.), and the like; the storage data area may store data created according to the use of the berth status display system (e.g., product information acquisition templates corresponding to different product types, product information required to be released by different product providers, etc.), and so on. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
The modules/units integrated in the terminal device may be stored in a computer readable medium if implemented in the form of software functional units and sold or used as separate products. Based on this understanding, the present invention may implement all or part of the modules/units in the system of the above-described embodiments, or may be implemented by instructing the relevant hardware by a computer program, which may be stored in a computer-readable medium, and which, when executed by a processor, may implement the functions of the respective system embodiments described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (7)
1. An industrial equipment internet of things data acquisition method is characterized by comprising the following steps: establishing a connection channel with each point in the internet of things network, and acquiring state data of each point based on the connection channel; wherein, the status data is sent in a data packet format;
randomly intercepting network data packets in each connecting channel, obtaining the transmission time of the network data packets, and classifying the network data packets according to the transmission time;
counting the number of different types of network data packets in the same connecting channel, and determining transmission parameters of each point location according to the counting result;
determining a motion instruction according to the transmission parameters, and sending the motion instruction to a mobile terminal;
receiving scene data fed back by a mobile terminal in real time, and counting the scene data and the state data to obtain acquisition data of each point bit;
the step of determining a motion instruction according to the transmission parameter and sending the motion instruction to a mobile terminal comprises the following steps:
determining the abnormal value of each point location according to the transmission parameters, and acquiring the position data of the point location when the abnormal value reaches a preset abnormal threshold;
acquiring position data of a mobile terminal, and determining a motion area according to the position data of the point location and the position data of the mobile terminal;
acquiring size data of a mobile terminal, generating a segmentation grid according to the size data, and segmenting the motion region according to the segmentation grid to obtain a motion region containing the segmentation grid;
determining a traveling path according to the motion area containing the segmentation grid, determining a motion instruction according to the traveling path, and sending the motion instruction to a mobile terminal;
the step of determining a travel path according to the motion area containing the segmentation grid comprises the following steps:
reading and displaying a motion area containing a segmentation grid, opening a touch screen signal receiving port containing an input mode, and obtaining a touch screen signal; wherein the input modes include a travel path input mode and a virtual wall input mode;
when the input mode is a travel path input mode, determining a travel path according to the touch screen signal;
when the input mode is a virtual wall input mode, determining a virtual wall according to the touch screen signal, and determining a travel path according to the virtual wall and the movement area;
the step of acquiring scene data by the mobile terminal comprises the following steps:
reading the position data of the point location and the position data of the mobile terminal, and calculating the distance and the direction in real time according to the position data of the point location and the position data of the mobile terminal;
determining an acquisition point according to the distance and a preset acquisition frequency;
when the position data of the mobile terminal is overlapped with the acquisition point, adjusting the shooting angle of the mobile terminal according to the direction to acquire a scene image;
performing contour recognition on the scene image, and calculating the image duty ratio of the point location area;
marking the scene image when the image duty ratio reaches a preset duty ratio threshold;
and counting the marked scene images, and inputting a preset data extraction model to obtain scene data.
2. The method for acquiring data of the internet of things of industrial equipment according to claim 1, wherein the step of establishing a connection channel with each point in the internet of things network and acquiring the status data of each point based on the connection channel comprises:
establishing a connection channel with each point in the internet of things network, and sequentially acquiring task linked lists of each point; the task linked list contains time items and task items;
reading task items in the task linked list, and acquiring time items corresponding to the task items to determine data extraction frequency;
acquiring all data tags of the same point location, and extracting a target tag from the data tags according to the task item;
and acquiring state data of the point location based on the data extraction frequency and the target tag.
3. The method for acquiring the data of the internet of things of industrial equipment according to claim 2, wherein the step of acquiring the status data of the point location based on the data extraction frequency and the target tag comprises:
performing weight assignment on other tags in the target tag and the data tag;
distributing the data extraction frequency according to the weight assignment result;
acquiring data corresponding to each data tag in the point location based on the allocated data extraction frequency;
and counting the data corresponding to each data tag to obtain state data.
4. The method for collecting internet of things data of industrial equipment according to claim 1, wherein the step of counting the number of different types of network data packets in the same connection channel and determining transmission parameters of each point location according to the counted result comprises:
counting the number of different types of network data packets within a preset time range to obtain a transmission array; wherein, the subscript of the transmission array and the type of the network data packet are in a mapping relation, and the value of the transmission array is the number;
determining coordinate points in a preset coordinate system according to the transmission array, and fitting the coordinate points to obtain a transmission curve;
and determining a transmission function according to the transmission curve, and determining transmission parameters according to the transmission function.
5. An industrial equipment internet of things data acquisition device, the device comprising:
the system comprises a state data acquisition module, a state data processing module and a state data processing module, wherein the state data acquisition module is used for establishing a connection channel with each point in the Internet of things network and acquiring state data of each point based on the connection channel; wherein, the status data is sent in a data packet format;
the data packet classification module is used for randomly intercepting network data packets in each connection channel, acquiring the transmission time of the network data packets and classifying the network data packets according to the transmission time;
the transmission parameter calculation module is used for counting the number of different types of network data packets in the same connecting channel and determining the transmission parameters of each point location according to the counting result;
the motion instruction determining module is used for determining a motion instruction according to the transmission parameters and sending the motion instruction to the mobile terminal;
the data induction module is used for receiving the scene data fed back by the mobile terminal in real time, and counting the scene data and the state data to obtain acquisition data of each point bit;
the content for determining the motion instruction according to the transmission parameters and sending the motion instruction to the mobile terminal comprises the following steps:
determining the abnormal value of each point location according to the transmission parameters, and acquiring the position data of the point location when the abnormal value reaches a preset abnormal threshold;
acquiring position data of a mobile terminal, and determining a motion area according to the position data of the point location and the position data of the mobile terminal;
acquiring size data of a mobile terminal, generating a segmentation grid according to the size data, and segmenting the motion region according to the segmentation grid to obtain a motion region containing the segmentation grid;
determining a traveling path according to the motion area containing the segmentation grid, determining a motion instruction according to the traveling path, and sending the motion instruction to a mobile terminal;
the determining the content of the travelling path according to the motion area containing the segmentation grid comprises the following steps:
reading and displaying a motion area containing a segmentation grid, opening a touch screen signal receiving port containing an input mode, and obtaining a touch screen signal; wherein the input modes include a travel path input mode and a virtual wall input mode;
when the input mode is a travel path input mode, determining a travel path according to the touch screen signal;
when the input mode is a virtual wall input mode, determining a virtual wall according to the touch screen signal, and determining a travel path according to the virtual wall and the movement area;
the mobile terminal obtaining the content of the scene data comprises the following steps:
reading the position data of the point location and the position data of the mobile terminal, and calculating the distance and the direction in real time according to the position data of the point location and the position data of the mobile terminal;
determining an acquisition point according to the distance and a preset acquisition frequency;
when the position data of the mobile terminal is overlapped with the acquisition point, adjusting the shooting angle of the mobile terminal according to the direction to acquire a scene image;
performing contour recognition on the scene image, and calculating the image duty ratio of the point location area;
marking the scene image when the image duty ratio reaches a preset duty ratio threshold;
and counting the marked scene images, and inputting a preset data extraction model to obtain scene data.
6. The industrial device internet of things data collection apparatus of claim 5, wherein the status data acquisition module comprises:
the task linked list acquisition unit is used for establishing a connection channel with each point in the Internet of things network and sequentially acquiring task linked lists of each point; the task linked list contains time items and task items;
the frequency determining unit is used for reading task items in the task linked list, acquiring time items corresponding to the task items and determining data extraction frequency;
the tag extraction unit is used for acquiring all the data tags of the same point location and extracting target tags from the data tags according to the task item;
and the data positioning and extracting unit is used for acquiring the state data of the point location based on the data extraction frequency and the target tag.
7. The industrial equipment internet of things data acquisition device of claim 6, wherein the data positioning extraction unit comprises:
the weight assignment subunit is used for carrying out weight assignment on the target label and other labels in the data label;
an allocation subunit, configured to allocate the data extraction frequency according to a weight assignment result;
an acquisition subunit, configured to acquire data corresponding to each data tag in the point location based on the allocated data extraction frequency;
and the statistics subunit is used for counting the data corresponding to each data tag to obtain state data.
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| CN116072282B (en) * | 2023-04-06 | 2023-06-13 | 吉林大学 | Remote intelligent detection and analysis method and system for CT equipment |
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