CN112199418B - State identification method, device and equipment for industrial object - Google Patents
State identification method, device and equipment for industrial object Download PDFInfo
- Publication number
- CN112199418B CN112199418B CN202011059582.2A CN202011059582A CN112199418B CN 112199418 B CN112199418 B CN 112199418B CN 202011059582 A CN202011059582 A CN 202011059582A CN 112199418 B CN112199418 B CN 112199418B
- Authority
- CN
- China
- Prior art keywords
- target
- object state
- value
- industrial
- factor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Probability & Statistics with Applications (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application is suitable for the technical field of industrial Internet of things, and provides a state identification method of an industrial object, which comprises the following steps: acquiring an operation value of a target factor; and determining the object state corresponding to the running value according to the relation between the target factor and the object state. According to the scheme, a large amount of analysis and processing on the operation value are not needed, the equipment can directly determine the object state of the industrial object according to the obtained operation value of the target factor, the processing efficiency is improved, and the workload is reduced.
Description
Technical Field
The application belongs to the technical field of industrial Internet of things, and particularly relates to a method, a device and equipment for identifying the state of an industrial object.
Background
With the advent of the industrial internet era, various industrial devices are arranged on industrial sites, so that the quantity of collected industrial data is increased. The existing industrial Internet of things platform has the disadvantages that the processing efficiency of industrial data is too low due to too large quantity of industrial data and complex analysis processing process, when an industrial scene is analyzed, a large quantity of analysis needs to be carried out on the industrial data calculation result to obtain an analysis reference result of the industrial scene, the processing efficiency is too low, the workload is large, and the object state of an industrial object to be obtained is difficult to directly obtain according to the obtained industrial data calculation result.
Disclosure of Invention
The embodiment of the application provides a method, a device and equipment for identifying the state of an industrial object, which can solve the problems that when industrial data are analyzed, the processing efficiency is too low, the workload is large, and the object state of the industrial object to be obtained is difficult to directly obtain according to the obtained industrial data calculation result.
In a first aspect, an embodiment of the present application provides a method for identifying a state of an industrial object, including:
acquiring an operation value of a target factor;
and determining the object state corresponding to the running value according to the relation between the target factor and the object state.
Further, the determining the object state corresponding to the running value according to the relationship between the target factor and the object state includes:
determining the coordinates of a target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor;
determining a target Thiessen polygon where the target point is located according to the coordinates of the target point;
and taking the preset object state corresponding to the target Thiessen polygon as the object state corresponding to the running value.
Further, before determining the object state corresponding to the running value according to the relationship between the target factor and the object state, the method further includes:
acquiring a historical value of the target factor and an object state corresponding to the historical value;
and establishing a Thiessen polygon according to the historical value and the object state corresponding to the historical value.
Further, before the obtaining the operation value of the target factor, the method further includes:
and acquiring the category of the target factor corresponding to the state of the object to be identified.
Further, the target factors are incremental estimation information and skewness estimation information; the object state includes a need to clean the deposit or no need to clean the deposit.
Further, the target factors are stability estimation information and a change speed; the object state includes a category of production issues.
Further, after determining the object state corresponding to the running value according to the relationship between the target factor and the object state, the method further includes:
and if the object state corresponding to the running value cannot be determined according to the relation between the target factor and the object state, performing warning operation.
In a second aspect, an embodiment of the present application provides an apparatus for identifying a state of an industrial object, including:
a first obtaining unit for obtaining an operation value of a target factor;
and the first determining unit is used for determining the object state corresponding to the running value according to the relation between the target factor and the object state.
Further, the first determination unit includes:
the second determining unit is used for determining the coordinates of the target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor;
a third determining unit, configured to determine a target thiessen polygon where the target point is located according to the coordinates of the target point;
and the first processing unit is used for taking a preset object state corresponding to the target Thiessen polygon as an object state corresponding to the running value.
Further, the state recognition device of the industrial object further comprises:
the second acquisition unit is used for acquiring a historical value of the target factor and an object state corresponding to the historical value;
and the second processing unit is used for establishing a Thiessen polygon according to the historical value and the object state corresponding to the historical value.
Further, the state recognition device of the industrial object further comprises:
and the third acquisition unit is used for acquiring the category of the target factor corresponding to the state of the object to be identified.
Further, the target factors are incremental estimation information and skewness estimation information; the object state includes a need to clean the deposit or no need to clean the deposit.
Further, the target factors are stability estimation information and a change speed; the object state includes a category of the production issue.
Further, the state recognition device of the industrial object further comprises:
and the warning unit is used for performing warning operation if the object state corresponding to the running value cannot be determined according to the relation between the target factor and the object state.
In a third aspect, an embodiment of the present application provides a state identification device for an industrial object, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the state identification method for the industrial object according to the first aspect when executing the computer program.
In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements the method for identifying the state of the industrial object according to the first aspect.
In the embodiment of the application, the operation value of the target factor is obtained; and determining the object state corresponding to the running value according to the relation between the target factor and the object state. According to the technical scheme, a large amount of analysis and processing on the operation value are not needed, the equipment can directly determine the object state of the industrial object according to the obtained operation value of the target factor, the processing efficiency is improved, and the workload is reduced.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic flow chart diagram of a method for identifying a state of an industrial object according to a first embodiment of the present application;
FIG. 2 is a schematic flowchart of a refinement of S102 in a method for identifying a state of an industrial object according to a first embodiment of the present application;
FIG. 3 is a schematic diagram of a target Thiessen polygon in a method for identifying a state of an industrial object according to a first embodiment of the present application;
fig. 4 is a schematic flowchart of S1024 to S1025 in a method for identifying a state of an industrial object according to a first embodiment of the present application;
FIG. 5 is a schematic view of a state identification device for an industrial object according to a second embodiment of the present application;
fig. 6 is a schematic diagram of a state recognition device for an industrial object according to a third embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.
Reference throughout this specification to "one embodiment" or "some embodiments," or the like, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," or the like, in various places throughout this specification are not necessarily all referring to the same embodiment, but rather "one or more but not all embodiments" unless specifically stated otherwise. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless otherwise specifically stated.
Referring to fig. 1, fig. 1 is a schematic flow chart of a method for identifying a state of an industrial object according to a first embodiment of the present application. An execution subject of the state recognition method of the industrial object in the present embodiment is a device having a state recognition function of the industrial object, for example, a server or the like. The state recognition method of the industrial object as shown in fig. 1 may include:
s101: and acquiring the running value of the target factor.
In an actual industrial site, various industrial devices may exist, and various industrial scenes may be generated. Various industrial data can be acquired according to different industrial scenes, and the industrial data can be analyzed and calculated in order to know the conditions and problems of industrial equipment in the operation and production process in the industrial scenes, but the direct conclusion of the industrial data and the standard quantity calculation result thereof is difficult to obtain.
In the embodiment, an industrial object is constructed in an industrial scene, the industrial object is constructed by combining different scene requirements of an industrial field, the industrial object is directed at different industrial scenes, and the industrial object is obtained by abstracting the industrial field and industrial equipment. The industrial object may be constructed from one industrial device or may be constructed from a plurality of industrial devices. The industrial object may include only a model of the industrial equipment, or may include a model of instruments and sensors around the industrial equipment. Further, environmental factors such as temperature, pressure, etc. of the environmental space may also be included in the industrial object.
When the device identifies the state of the industrial object, it is necessary to acquire a target factor associated with the state of the industrial object in advance. Therefore, before S101, the method may further include: and acquiring the category of the target factor corresponding to the state of the object to be identified. Different object states to be identified correspond to different categories of the target factors, and after the categories of the target factors are determined, the equipment acquires the running values of the target factors.
The objective factor is an important factor affecting the state of the industrial object, for example, when the state of the industrial object is a category of a production problem, the important factor affecting the category of the production problem may be stability estimation information and a change speed of the industrial object, and the stability estimation information and the change speed serve as the objective factor identified at this time. The number of the target factors may be 1 or more, and is not limited herein.
The equipment acquires the operation value of the target factor, the operation value of the target factor is the actual data of the target factor, and the operation value of the target factor can be obtained by calculation according to the actual industrial data of the industrial object. For example, if the target factor is the incremental estimation information, the operation value of the target factor is 7720.72; the objective factor is the skew estimation information, and the operation value of the objective factor is 2.577.
S102: and determining the object state corresponding to the running value according to the relation between the target factor and the object state.
The device pre-stores the relationship between the target factors and the object states, and can classify the operation values of the target factors, wherein the operation values of different types of target factors correspond to different object states, for example, when the operation values of the target factors are in a first interval, the operation values correspond to the first object state, and when the device obtains the operation values and falls into the first interval, the first object state is the object state of the industrial object.
In one embodiment, the relationship between the target factor and the object state can be represented by a Thiessen polygon, so that the object state of the industrial object can be acquired more accurately. It is understood that the relationship between the target factor and the object state is represented by a Thiessen polygon, which is only one implementation manner, and there are many ways to represent the relationship between the target factor and the object state, and the present invention is not limited thereto. In this embodiment, S102 may include S1021 to S1023, and as shown in fig. 2, S1021 to S1023 are specifically as follows:
s1021: and determining the coordinates of the target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor.
In this embodiment, the device stores in advance a target Thiessen polygon, which is also called Feng Luo Noew map, which is a set of continuous polygons composed of perpendicular bisectors connecting two adjacent point line segments. Any point within a Thiessen polygon is less distant from the control points that make up the polygon than from the control points of other polygons. The Thiessen polygon is a subdivision of a spatial plane, and is characterized in that any position in the polygon is closest to a sampling point of the polygon and is far away from the sampling point in an adjacent polygon, and each polygon contains only one sampling point. As shown in fig. 3, fig. 3 is a schematic diagram of a target thiessen polygon, in which a coordinate system is a preset coordinate system, and horizontal and vertical coordinates of the preset coordinate system respectively correspond to two target factor increment estimation information ^ jk Y And skewness estimation information E (X).
The equipment determines coordinates of a target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor, wherein coordinate axes of the preset coordinate system respectively correspond to the target factor, and the coordinates of the target point corresponding to the target factor are the running value.
S1022: and determining a target Thiessen polygon where the target point is located according to the coordinates of the target point.
And the equipment determines the position of the target point according to the coordinates of the target point, wherein the target Thiessen polygon in which the target point falls is the target Thiessen polygon in which the target point is positioned.
S1023: and taking the preset object state corresponding to the target Thiessen polygon as the object state corresponding to the running value.
In this embodiment, each Thiessen polygon corresponds to a preset object state, and when the target point falls into the Thiessen polygon, the corresponding preset object state can be obtained as the current object state of the industrial object. And the equipment takes the preset object state corresponding to the target Thiessen polygon as the object state corresponding to the running value.
For example, when the preset object state corresponding to the thiessen polygon is "to clean the deposit", and when the target point falls into the thiessen polygon, the object state corresponding to the operation value is "to clean the deposit".
In this embodiment, the tessen polygon pre-stored in the device may be pre-established according to the history data, and before S1021 to S1023, S1024 to S1025 may be further included, as shown in fig. 4, where S1024 to S1025 are specifically as follows:
s1024: and acquiring the historical value of the target factor and the object state corresponding to the historical value.
The device can acquire a historical value of the target factor and an object state corresponding to the historical value in advance, wherein the historical value is the value of the target factor in the past industrial object operation process, and the object state corresponding to the historical value is judged through actual conditions and can be artificially judged and set according to the conditions of an industrial field.
For example, the target factors are incremental estimation information and skewed estimation information, the object state includes that sediment needs to be cleaned or sediment does not need to be cleaned, and the historical values of the target factors acquired by the equipment are as follows: the incremental estimation information is 3954.94, the skewness estimation information is 1.830, and the object state corresponding to the historical value obtained through judgment of the industrial site is that sediment does not need to be cleaned.
It can be understood that the more the number of the historical values and the object states corresponding to the historical values is, the more accurate the built Thiessen polygon is in object state recognition. In addition, after the operation value of the target factor is actually recognized, the target thieson polygon may be corrected again using the operation value of the target factor and the recognized object state.
S1025: and establishing a Thiessen polygon according to the historical value and the object state corresponding to the historical value.
The equipment can acquire a plurality of groups of historical values and corresponding object states thereof, and establish the Thiessen polygon according to the plurality of groups of historical values and the corresponding object states thereof. The device can use the historical value as coordinate information, perform point tracing in a preset coordinate system, and establish the Thiessen polygon. The relationship between the target factors and the object states can be represented by the Thiessen polygons established by the multiple groups of historical values and the corresponding object states, and after the relationship between the target factors and the object states is established by the equipment, the object states of the industrial objects can be identified by acquiring the target factors.
In this embodiment, if the object state corresponding to the operation value cannot be determined according to the relationship between the target factor and the object state, which indicates that a new object state may occur and a new problem that has not occurred before may occur, an alarm operation is performed. Prompting the user to take measures in time.
The following describes the data transmission method provided in this embodiment with reference to specific applications:
in one embodiment, the target factors are stability estimation information and rate of change; the object state includes a category of the production issue. In the actual production process, some production problems are not obtained in real time, the production process is difficult to control, and the judgment can be carried out only by producing products after the production is finished, but once a problem occurs, the products are unqualified, and the resource waste is caused. In this implementation, the target factors affecting the production problem can be summarized and analyzed according to the actual situation, the device sets the target factors of the production problem as the stability estimation information and the change speed, the device obtains the stability estimation information and the change speed history value and the type of the production problem corresponding to the stability estimation information and the change speed history value, and then the Thiessen polygon is constructed according to the stability estimation information and the change speed history value and the type of the production problem corresponding to the stability estimation information and the change speed history value. In actual production, the stability estimation information and the operation value of the change speed are obtained, the operation value is used as coordinate information, the position of a target point in a preset coordinate system is obtained, the object state corresponding to a target polygon in which a coordinate point corresponding to the operation value falls is obtained, and then the type of the currently occurring production problem can be known.
In one embodiment, the target factors are incremental estimation information and skewed estimation information; the object state includes a need to clean the deposit or no need to clean the deposit. In the implementation, the target factors of whether the sediment needs to be cleaned can be summarized, analyzed and obtained according to the actual situation, the equipment sets the target factors of whether the sediment needs to be cleaned to be the incremental estimation information and the skewness estimation information, the equipment obtains the historical values of the incremental estimation information and the skewness estimation information and the types of the production problems corresponding to the historical values, and then the Thiessen polygon is constructed according to the historical values of the incremental estimation information and the skewness estimation information and the types of the results of whether the sediment needs to be cleaned or not. In actual production, an operation value of whether the sediment needs to be cleaned is obtained, the operation value is used as coordinate information, the position of a target point in a preset coordinate system is obtained, an object state corresponding to a target polygon into which a coordinate point corresponding to the operation value falls is obtained, and whether the sediment needs to be cleaned at present can be known.
In the embodiment of the application, the operation value of the target factor is obtained; and determining the object state corresponding to the running value according to the relation between the target factor and the object state. According to the technical scheme, a large amount of analysis and processing on the operation value are not needed, the equipment can directly determine the object state of the industrial object according to the obtained operation value of the target factor, the processing efficiency is improved, and the workload is reduced.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Referring to fig. 5, fig. 5 is a schematic view of a state identification device for an industrial object according to a second embodiment of the present application. The units are included for executing the steps in the embodiments corresponding to fig. 1-2 and 4. Please refer to the related description of the embodiments corresponding to fig. 1-2 and fig. 4. For convenience of explanation, only the portions related to the present embodiment are shown. Referring to fig. 5, the state recognition apparatus 5 of the industrial object includes:
a first obtaining unit 510, configured to obtain a running value of a target factor;
a first determining unit 520, configured to determine an object state corresponding to the running value according to a relationship between the target factor and the object state.
Further, the first determining unit 520 includes:
the second determining unit is used for determining the coordinates of the target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor;
a third determining unit, configured to determine a target thiessen polygon where the target point is located according to the coordinates of the target point;
and the first processing unit is used for taking a preset object state corresponding to the target Thiessen polygon as an object state corresponding to the running value.
Further, the state recognition device 5 for industrial objects further includes:
the second acquisition unit is used for acquiring a historical value of the target factor and an object state corresponding to the historical value;
and the second processing unit is used for establishing a Thiessen polygon according to the historical value and the object state corresponding to the historical value.
Further, the state recognition device 5 for industrial object further includes:
and the third acquisition unit is used for acquiring the category of the target factor corresponding to the state of the object to be identified.
Further, the target factors are incremental estimation information and skewness estimation information; the object state includes a need to clean the deposit or no need to clean the deposit.
Further, the target factors are stability estimation information and a change speed; the object state includes a category of production issues.
Further, the state recognition device 5 for industrial object further includes:
and the warning unit is used for performing warning operation if the object state corresponding to the operation value cannot be determined according to the relation between the target factor and the object state.
Fig. 6 is a schematic diagram of a state recognition device for industrial objects according to a third embodiment of the present application. As shown in fig. 6, the state recognition device 6 of the industrial object of the embodiment includes: a processor 60, a memory 61 and a computer program 62, such as a state identification program of an industrial object, stored in said memory 61 and executable on said processor 60. The processor 60, when executing the computer program 62, implements the steps in the above-described embodiments of the method for identifying the status of each industrial object, such as the steps 101 to 102 shown in fig. 1. Alternatively, the processor 60, when executing the computer program 62, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 510 to 520 shown in fig. 5.
Illustratively, the computer program 62 may be partitioned into one or more modules/units that are stored in the memory 61 and executed by the processor 60 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program 62 in the state recognition device 6 of the industrial object. For example, the computer program 62 may be divided into a first obtaining unit and a first determining unit, and each unit has the following specific functions:
a first obtaining unit for obtaining an operation value of a target factor;
and the first determining unit is used for determining the object state corresponding to the running value according to the relation between the target factor and the object state.
The state recognition device of the industrial object may include, but is not limited to, a processor 60, a memory 61. It will be understood by those skilled in the art that fig. 6 is merely an example of the state recognition device 6 of an industrial object, and does not constitute a limitation of the state recognition device 6 of an industrial object, and may include more or less components than those shown, or some components in combination, or different components, for example, the state recognition device of an industrial object may also include input-output devices, network access devices, buses, etc.
The Processor 60 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the state recognition device 6 of the industrial object, such as a hard disk or a memory of the state recognition device 6 of the industrial object. The memory 61 may also be an external storage device of the status recognition device 6 of the industrial object, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the status recognition device 6 of the industrial object. Further, the state recognition device 6 of the industrial object may also include both an internal storage unit and an external storage device of the state recognition device 6 of the industrial object. The memory 61 is used for storing the computer program and other programs and data required by the state recognition device of the industrial object. The memory 61 may also be used to temporarily store data that has been output or is to be output.
It should be noted that, for the information interaction, execution process, and other contents between the above devices/units, the specific functions and technical effects thereof based on the same concept as those of the method embodiment of the present application can be specifically referred to the method embodiment portion, and are not described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
An embodiment of the present application further provides a network device, where the network device includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, the processor implementing the steps of any of the various method embodiments described above when executing the computer program.
The embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps in the above-mentioned method embodiments.
The embodiments of the present application provide a computer program product, which when running on a mobile terminal, enables the mobile terminal to implement the steps in the above method embodiments when executed.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal device, recording medium, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunication signals, and software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other ways. For example, the above-described apparatus/network device embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present application, and they should be construed as being included in the present application.
Claims (5)
1. A method of identifying a state of an industrial object, comprising:
acquiring an operation value of a target factor; the target factors are incremental estimation information and skewness estimation information; the object state comprises that the sediment needs to be cleaned or the sediment does not need to be cleaned, or the target factors are stability estimation information and change speed; the object state comprises a category of a production issue;
determining an object state corresponding to the running value according to the relation between the target factor and the object state;
the determining the object state corresponding to the running value according to the relationship between the target factor and the object state includes:
determining the coordinates of a target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor; the coordinate axes of the preset coordinate system respectively correspond to target factors, and the coordinates of target points corresponding to the target factors are the operation values;
determining a target Thiessen polygon where the target point is located according to the coordinates of the target point; the target Thiessen polygon in which the target point falls is the target Thiessen polygon in which the target point is located;
taking a preset object state corresponding to the target Thiessen polygon as an object state corresponding to the running value; each Thiessen polygon corresponds to a preset object state;
before determining the object state corresponding to the running value according to the relationship between the target factor and the object state, the method further includes:
acquiring a historical value of the target factor and an object state corresponding to the historical value;
establishing a Thiessen polygon according to the historical value and the object state corresponding to the historical value;
after the object state corresponding to the running value is determined according to the relationship between the target factor and the object state, the method further includes:
and if the object state corresponding to the running value cannot be determined according to the relation between the target factor and the object state, performing warning operation.
2. The method for status recognition of an industrial object according to claim 1, further comprising, prior to the obtaining the running value of the target factor:
and acquiring the category of the target factor corresponding to the state of the object to be identified.
3. An apparatus for recognizing a state of an industrial object, comprising:
a first obtaining unit for obtaining an operation value of a target factor; the target factors are incremental estimation information and skewness estimation information; the object state comprises that sediment needs to be cleaned or sediment does not need to be cleaned, or the target factors are stability estimation information and change speed; the object state comprises a category of production issues;
a first determining unit, configured to determine an object state corresponding to the running value according to a relationship between the target factor and the object state;
the first determination unit includes:
the second determining unit is used for determining the coordinates of the target point corresponding to the target factor in a preset coordinate system according to the running value of the target factor; the coordinate axes of the preset coordinate system respectively correspond to target factors, and the coordinates of target points corresponding to the target factors are the operation values;
a third determining unit, configured to determine a target thiessen polygon where the target point is located according to the coordinates of the target point; the target Thiessen polygon in which the target point falls is the target Thiessen polygon in which the target point is located;
the first processing unit is used for taking a preset object state corresponding to the target Thiessen polygon as an object state corresponding to the running value; each Thiessen polygon corresponds to a preset object state;
the second acquisition unit is used for acquiring a historical value of the target factor and an object state corresponding to the historical value;
the second processing unit is used for establishing a Thiessen polygon according to the historical value and the object state corresponding to the historical value;
and the warning unit is used for performing warning operation if the object state corresponding to the operation value cannot be determined according to the relation between the target factor and the object state.
4. A state recognition device of an industrial object, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to claim 1 or 2 when executing the computer program.
5. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to claim 1 or 2.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011059582.2A CN112199418B (en) | 2020-09-30 | 2020-09-30 | State identification method, device and equipment for industrial object |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011059582.2A CN112199418B (en) | 2020-09-30 | 2020-09-30 | State identification method, device and equipment for industrial object |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112199418A CN112199418A (en) | 2021-01-08 |
| CN112199418B true CN112199418B (en) | 2023-03-03 |
Family
ID=74007252
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011059582.2A Active CN112199418B (en) | 2020-09-30 | 2020-09-30 | State identification method, device and equipment for industrial object |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112199418B (en) |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP4349367B2 (en) * | 2003-10-30 | 2009-10-21 | 日本電気株式会社 | Estimation system, estimation method, and estimation program for estimating the position and orientation of an object |
| US8375032B2 (en) * | 2009-06-25 | 2013-02-12 | University Of Tennessee Research Foundation | Method and apparatus for predicting object properties and events using similarity-based information retrieval and modeling |
| CN103489053A (en) * | 2013-05-13 | 2014-01-01 | 湖南云控科技有限公司 | Intelligent water resource control platform based on cloud computing and expert system |
| US9552408B2 (en) * | 2014-01-24 | 2017-01-24 | Facebook, Inc. | Nearest neighbor clustering determination and estimation algorithm that hashes centroids into buckets and redistributes vectors between clusters |
| CN106339820B (en) * | 2016-08-31 | 2023-06-06 | 中国电建集团昆明勘测设计研究院有限公司 | Real-time dynamic multidimensional analysis method and system for hydraulic building based on virtual reality |
| CN108242203A (en) * | 2016-12-23 | 2018-07-03 | 中兴通讯股份有限公司 | A kind of region partitioning method and device |
| JP6976080B2 (en) * | 2017-05-22 | 2021-12-01 | 三菱パワー株式会社 | State analyzer, state analysis method, and program |
| JP6721550B2 (en) * | 2017-08-04 | 2020-07-15 | 株式会社ソニー・インタラクティブエンタテインメント | Information processing apparatus and position information acquisition method |
| CN108762212A (en) * | 2018-05-31 | 2018-11-06 | 深圳汇创联合自动化控制有限公司 | Substation equipment intelligent monitor system based on Internet of Things |
| CN109743740B (en) * | 2019-02-27 | 2021-10-15 | 西北师范大学 | Directional sensor network target monitoring method based on 3D-Voronoi subdivision |
| CN110322694A (en) * | 2019-07-16 | 2019-10-11 | 青岛海信网络科技股份有限公司 | A kind of method and device of urban traffic control piece Division |
| CN111405478A (en) * | 2020-03-02 | 2020-07-10 | Oppo广东移动通信有限公司 | Service providing method, device, terminal and storage medium |
-
2020
- 2020-09-30 CN CN202011059582.2A patent/CN112199418B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN112199418A (en) | 2021-01-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116188821B (en) | Copyright detection method, system, electronic device and storage medium | |
| CN110839016A (en) | Abnormal flow monitoring method, device, equipment and storage medium | |
| CN110471409B (en) | Robot inspection method and device, computer readable storage medium and robot | |
| CN109165657A (en) | A kind of image feature detection method and device based on improvement SIFT | |
| CN115830010B (en) | Method and device for detecting crossing distance of transmission wires and computer equipment | |
| CN108955901A (en) | A kind of infrared measurement of temperature method, system and terminal device | |
| CN105354721A (en) | Method and device for identifying machine operation behavior | |
| CN118094450B (en) | Fault early warning method and related equipment | |
| CN110609864B (en) | Chemical supply chain-oriented data visualization management method and device | |
| CN112198878A (en) | Instant map construction method and device, robot and storage medium | |
| CN106651803A (en) | House type data identification method and device | |
| CN114003796A (en) | Industrial control asset discovery method and device and electronic equipment | |
| CN112199418B (en) | State identification method, device and equipment for industrial object | |
| CN112629828A (en) | Optical information detection method, device and equipment | |
| CN116957310A (en) | Intelligent manufacturing data management system and method based on cloud computing technology | |
| CN110751141A (en) | Meter reading identification method and device, terminal equipment and storage medium | |
| CN108629219B (en) | Method and device for identifying one-dimensional code | |
| CN115412346A (en) | Message detection method and device, electronic equipment and storage medium | |
| CN112858725B (en) | Vehicle speed consistency detection method, terminal equipment and storage medium | |
| CN114494960A (en) | Video processing method and device, electronic equipment and computer readable storage medium | |
| CN112816959B (en) | Clustering method, device, equipment and storage medium for vehicles | |
| CN112633143B (en) | Image processing system, method, head-mounted device, processing device, and storage medium | |
| CN114842228A (en) | Speckle pattern partitioning method, device, equipment and medium | |
| CN112416128B (en) | Gesture recognition method and terminal equipment | |
| CN114036721A (en) | Method and device for constructing three-dimensional temperature cloud field of micro-module |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |