CN117370319A - Data accuracy detection method, device, equipment and storage medium - Google Patents
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Abstract
The present disclosure relates to a data accuracy detection method, apparatus, device, and storage medium, the method comprising: acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range; comparing the data real-time value with the data valid range; and judging whether the data real-time value is effective data or not based on the quantitative relation between the data real-time value and the data effective range. According to the embodiment of the disclosure, after the effective range and the real-time value of the data to be detected are obtained, whether the real-time value is the effective data is judged through the quantity relation between the real-time value and the effective range, so that the validity of the data of the detection point can be calculated quickly and intuitively, manual operation is avoided, and waste of manpower and material resources is avoided.
Description
Technical Field
The present disclosure relates to the field of computer processing technologies, and in particular, to a method, an apparatus, a device, and a storage medium for detecting data accuracy.
Background
The data acquisition and monitoring system (Supervisory ControI And Data AcquiSition System, SCADA) is widely applied to the industrial field, relates to a plurality of traditional industries such as petroleum, electric power, energy, chemical industry, semiconductors and the like and emerging intelligent manufacturing fields, plays an important role in digital transformation processes of digital intelligent factories and traditional factories at present, and becomes an important component of industrial Internet.
The SCADA system is mainly used for collecting and analyzing data of field devices, and the data collection is more important than monitoring, and especially the accuracy of the data collection can directly influence the monitoring effect. Currently, data collection software in the market mainly adopts a Server/Client (C/S) architecture, and the data collection mode mainly comprises two modes of collection from a programmable logic controller (Programmable Logic Controller, PLC) and collection through a gateway. The measurement point data collected in the two modes are directly stored in a database, and effective data cleaning is not performed in time, so that the problems of incorrect display of configuration pictures, abnormal alarm triggering and the like can be caused.
In the related art, whether the collected detection point data is correct or not is judged, the database is required to be queried manually, and then whether the detection point data is correct or not is judged manually, so that a large amount of manpower and material resources are wasted.
Disclosure of Invention
In order to solve the technical problems, the embodiments of the present disclosure provide a data accuracy detection method, a device and a storage medium, which can quickly and intuitively calculate the validity of detection point data, avoid manual operation, and avoid waste of manpower and material resources.
In a first aspect, an embodiment of the present disclosure provides a data accuracy detection method, including: acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range; comparing the data real-time value with the data valid range; and judging whether the data real-time value is effective data or not based on the quantitative relation between the data real-time value and the data effective range.
In one embodiment of the disclosure, determining whether the data real-time value is valid data based on a quantitative relationship between the data real-time value and the data valid range includes determining that the data real-time is valid data if the data real-time value is within the data valid range; and if the data real-time value is not in the data valid range, determining that the data is invalid in real time.
In one embodiment of the present disclosure, the data attribute value further includes: collecting frequency; acquiring the actual acquisition quantity of the data acquired by the target detection point in a preset time period; calculating the data target acquisition quantity based on the preset time period and the sampling frequency; and judging whether the data missing acquisition exists in the target detection point in the preset time period or not based on the quantitative relation between the actual data acquisition quantity and the data target acquisition quantity.
In one embodiment of the present disclosure, based on a quantitative relationship between the actual collection number of data and the target collection number of data, determining whether the target detection point has data missing in the preset time period includes: if the actual data acquisition quantity is greater than or equal to the data target acquisition quantity, determining that the target detection point does not have data missing acquisition in the preset time period; and if the actual data acquisition quantity is smaller than the data target acquisition quantity, determining that the target detection point has data missing acquisition in the preset time period.
In one embodiment of the present disclosure, the method further comprises: and taking the difference value between the data target acquisition quantity and the data actual acquisition quantity as the data missing acquisition quantity.
In one embodiment of the present disclosure, the method further comprises displaying a data detection result in the data detection interface, wherein the data detection result comprises at least one of: the name of the target detection point, the real-time value of the data, whether the real-time value of the data is valid or not, and the number of invalid data; whether data missing is existed or not, and the data missing is counted.
In one embodiment of the present disclosure, the method further comprises: displaying a detection point selection control in a data detection interface; responding to the operation of selecting a control along with the detection point, and acquiring and displaying a plurality of detection points to be selected; and responding to the selection operation of the plurality of detection points to be selected, and selecting at least one target detection point from the detection points to be selected.
In a second aspect, an embodiment of the present disclosure provides a data accuracy detecting apparatus, including: the data value acquisition module is used for acquiring data attribute values and data real-time values of the target detection points, wherein the data attribute values comprise data effective ranges; the effective range comparison module is used for judging whether the data real-time value is in the data effective range or not; and the effective data judging module is used for judging whether the data real-time value is effective data or not based on the quantity relation between the data real-time value and the data effective range.
In one embodiment of the present disclosure, the valid data determination module includes: a valid data determining unit, configured to determine that the data is valid data in real time if the data real-time value is within the data valid range; and the invalid data determining unit is used for determining that the data is invalid data in real time if the real-time value of the data is not in the valid range of the data.
In one embodiment of the present disclosure, the data attribute value further includes: collecting frequency; the apparatus further comprises: the actual acquisition quantity acquisition module is used for acquiring the actual acquisition quantity of the data acquired by the target detection point in a preset time period; the target acquisition quantity calculation module is used for calculating the data target acquisition quantity based on the preset time period and the sampling frequency; and the data missing acquisition judging module is used for judging whether the data missing acquisition exists in the target detection point in the preset time period based on the quantity relation between the actual data acquisition quantity and the data target acquisition quantity.
In one embodiment of the present disclosure, a data missing acquisition judgment module is configured to include: the missing acquisition determining unit is used for determining that the target detection point does not have data missing acquisition in the preset time period if the actual data acquisition number is greater than or equal to the data target acquisition number; and the missing acquisition determining unit is used for determining that the target detection point has missing data acquisition in the preset time period if the actual data acquisition number is smaller than the target data acquisition number.
In one embodiment of the present disclosure, the apparatus further comprises: and the missing acquisition quantity determining unit is used for taking the difference value between the data target acquisition quantity and the data actual acquisition quantity as the data missing acquisition quantity.
In one embodiment of the present disclosure, the apparatus further comprises: the detection result display module is used for displaying a data detection result in the data detection interface, wherein the data detection result comprises at least one of the following steps: the name of the target detection point, the real-time value of the data, whether the real-time value of the data is valid or not, and the number of invalid data; whether data missing is existed or not, and the data missing is counted.
In one embodiment of the present disclosure, the apparatus further comprises: the selection control display module is used for displaying a detection point selection control in the data detection interface; the detection point to be selected display module is used for responding to the operation of selecting a control along with the detection point to acquire and display a plurality of detection points to be selected; the target detection point selection module is used for responding to the selection operation of the plurality of detection points to be selected and selecting at least one target detection point from the detection points to be selected.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including:
One or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data accuracy detection method of any of the first aspects described above.
In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the data accuracy detection method according to any one of the first aspects above.
The embodiment of the disclosure provides a data accuracy detection method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range; comparing the data real-time value with the data valid range; and judging whether the data real-time value is effective data or not based on the quantitative relation between the data real-time value and the data effective range. According to the embodiment of the disclosure, after the effective range and the real-time value of the data to be detected are obtained, whether the real-time value is the effective data is judged through the quantity relation between the real-time value and the effective range, so that the validity of the data of the detection point can be calculated quickly and intuitively, manual operation is avoided, and waste of manpower and material resources is avoided.
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The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.
FIG. 1 is a schematic diagram of a network architecture of a SCADA system according to an embodiment of the present disclosure;
FIG. 2 is a flow chart of a method for detecting data accuracy in an embodiment of the disclosure;
FIG. 3 is a flow chart of a method for detecting data accuracy in an embodiment of the disclosure;
FIG. 4 is a schematic page view of a data detection interface provided by an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a data accuracy detecting device according to an embodiment of the disclosure;
fig. 6 is a schematic structural diagram of an electronic device in an embodiment of the disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been shown in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. Related definitions of other terms will be given in the description below.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units. The references to "a" and "an" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The data acquisition and monitoring system (Supervisory ControI And Data AcquiSitionSystem, SCADA) is widely applied to the industrial field, relates to a plurality of traditional industries such as petroleum, electric power, energy, chemical industry, semiconductor and the like and emerging intelligent manufacturing fields, plays an important role in digital transformation processes of digital intelligent chemical plants and traditional factories at present, and becomes an important component of industrial Internet.
From the development history of SCADA systems, four generations have been currently experienced:
the first generation SCADA system is mainly a customized system developed based on a special computer and an operating system; the second generation SCADA system is already adapted to a general computer, and an operating system is mainly UNIX and is widely applied in the power industry; the first two generations of SCADA systems have the common disadvantage that the systems are not open and therefore are difficult to maintain, upgrade and operate. With the help of internet wave, the maturation of database technology and the appearance of distributed computers, the third generation SCADA system is generated, and is also the fastest growing period of the SCADA system, and is widely applied in the fields of power grid construction and power system automation. The fourth generation SCADA system integrates the technologies of intelligent sensor equipment, big data, a neural network, a real-time database and the like, and simultaneously interfaces with factory systems such as an enterprise asset management system (Enterprise Asset Management, EAM) and an electric energy management system (Energy Management System, EMS).
As shown in fig. 1, the SCADA system is generally divided into an upper computer, a communication network and a lower computer from the view of a network architecture, wherein the lower computer mainly comprises a PLC, a gateway, acquisition equipment, various instruments and meters, and the like, and focuses on data acquisition and control; the network layer is used for communication between the upper computer and the lower computer and supports wired transmission and wireless transmission; the upper computer mainly comprises a human-machine interface (Human Machine Interface, HMI), configuration software, a client, a database and the like, and focuses on remote monitoring, alarm processing, data report generation and the like.
The SCADA system is mainly used for collecting and analyzing data of field devices, and the data collection is more important than monitoring, and especially the accuracy of the data collection can directly influence the monitoring effect. Currently, data collection software in the market mainly adopts a Server/Client (C/S) architecture, and the data collection mode mainly comprises two modes of collection from a programmable logic controller (Programmable Logic Controller, PLC) and collection through a gateway. The measurement point data collected in the two modes are directly stored in a database, and effective data cleaning is not performed in time, so that the problems of incorrect display of configuration pictures, abnormal alarm triggering and the like can be caused.
In the related art, whether the collected detection point data is correct or not is judged, the database is required to be queried manually, and then whether the detection point data is correct or not is judged manually, so that a large amount of manpower and material resources are wasted.
In order to solve the above technical problems, an embodiment of the present disclosure provides a data accuracy detection method, which mainly includes: acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range; comparing the data real-time value with the data valid range; and judging whether the data real-time value is effective data or not based on the quantitative relation between the data real-time value and the data effective range.
According to the embodiment of the disclosure, after the effective range and the real-time value of the data to be detected are obtained, whether the real-time value is the effective data is judged through the quantity relation between the real-time value and the effective range, so that the validity of the data of the detection point can be calculated quickly and intuitively, manual operation is avoided, and waste of manpower and material resources is avoided.
Fig. 2 is a flowchart of a data accuracy detection method in an embodiment of the disclosure, where the embodiment is applicable to detecting accuracy of data collected in a SCADA system, and the method may be performed by a data accuracy detection device, where the data accuracy detection device may be implemented in software and/or hardware.
As shown in fig. 2, the data accuracy detection method provided in the embodiment of the present disclosure mainly includes steps S101 to S103.
S101, acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range.
The target detection point is a detection point in the SCADA system, where data needs to be collected. The target detection point may be a point of the device under test, for example: the destination point may be an A-th current detector, a B-th voltage detector, a C-th speed detector, a D-th temperature detector, etc.
Further, the data attribute value may be understood as a numerical value for characterizing the validity and integrity of the data at the target detection point. The real-time data value may be understood as a value currently detected by the target detection point. Further, the data attribute value includes a data valid range, where the data valid range may be a continuous interval or may be a plurality of intermittent intervals, which is not specifically limited in the embodiments of the present disclosure.
In one embodiment of the present disclosure, the method further comprises: displaying a detection point selection control in a data detection interface; responding to the operation of selecting a control along with the detection point, and acquiring and displaying a plurality of detection points to be selected; and responding to the selection operation of the plurality of detection points to be selected, and selecting at least one target detection point from the detection points to be selected.
In the embodiment of the application, a detection point selection control is displayed in a data detection cleaning face of the SCADA system, and all detection points in the SCADA system are displayed as detection points to be selected in response to triggering operation of the detection point selection control by a user. The user may select one or more target detection points from the candidate detection points. It should be noted that, the data attribute values corresponding to each target detection point are different.
Furthermore, the effective range of the data can be set by a user according to actual experience, and can also be calculated by counting the measured value of the target detection point data within a certain period of time.
In one implementation manner of the application, after the lower computer collects the data real-time values of the multiple detection points, the data implementation values of the multiple detection points are stored in a database of the upper computer, and the data accuracy detection device in the embodiment of the application reads the data real-time values of the target detection points from the database.
In one implementation manner of the present application, the data accuracy detecting device in the embodiment of the present application directly receives the real-time value of the data detected from the lower computer.
S102, comparing the data real-time value with the data valid range.
In the embodiment of the application, for the target detection point, the acquired real-time data value is compared with the effective data range.
And S103, judging whether the data real-time value is effective data or not based on the quantity relation between the data real-time value and the data effective range.
In one embodiment of the present disclosure, if the data real-time value is within the data valid range, determining that the data real-time is valid data; and if the data real-time value is not in the data valid range, determining that the data is invalid in real time.
In an embodiment of the present application, if the data real-time value is within the data valid range, the data real-time value is marked as valid. If the data real-time value is not in the data valid range, the data real-time value is marked as invalid, or the data real-time value in the data valid range is directly discarded.
In one embodiment of the present application, the number of valid data and the number of invalid data within a preset time period are counted. Illustratively, if the data real-time value is within the data valid range, the number of currently valid data is increased by 1, and if the data real-time value is not within the data valid range, the number of currently invalid data is increased by 1.
The embodiment of the disclosure provides a data accuracy detection method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range; comparing the data real-time value with the data valid range; and judging whether the data real-time value is effective data or not based on the quantitative relation between the data real-time value and the data effective range. According to the embodiment of the disclosure, after the effective range and the real-time value of the data to be detected are obtained, whether the real-time value is the effective data is judged through the quantity relation between the real-time value and the effective range, so that the validity of the data of the detection point can be calculated quickly and intuitively, manual operation is avoided, and waste of manpower and material resources is avoided.
Fig. 2 is a flowchart of a data accuracy detection method in an embodiment of the present disclosure, and as shown in fig. 2, the data accuracy detection method provided in the embodiment of the present disclosure mainly includes steps S201 to S204.
S201, acquiring a data attribute value of a target detection point, wherein the data attribute value comprises: the frequency is acquired.
The collection frequency refers to the frequency of the target detection point for collecting the measured value. For example: the acquisition frequency may be 30 measurements per second, i.e. the acquisition frequency of the target detection point is 30 measurements per second. Furthermore, the above-mentioned acquisition frequency may be set by the user according to the actual situation of the detection device or the detected point, which is not limited in detail in the embodiment of the present application.
S202, acquiring the actual acquisition quantity of the data acquired by the target detection point in a preset time period.
The preset time period may be a time period selected by a user and from a current time point to a past time point; for example: the current time point is divided into 8 am and 00. The preset time period may also be a past time period selected by a user, for example: 8.00 am to 10.00 am. The preset time period may also be a plurality of interval time periods selected by a user, for example: each 9.00 am to 11.00 am.
S203, calculating the data target acquisition quantity based on the preset time period and the sampling frequency.
In the embodiment of the application, a preset time length included in a preset time period is calculated, and the product of the preset time length and the sampling frequency is used as target sampling data.
S204, judging whether the data missing acquisition exists in the target detection point in the preset time period or not based on the number relation between the actual data acquisition number and the data target acquisition number.
In one embodiment of the present disclosure, based on a quantitative relationship between the actual collection number of data and the target collection number of data, determining whether the target detection point has data missing in the preset time period includes: if the actual data acquisition quantity is greater than or equal to the data target acquisition quantity, determining that the target detection point does not have data missing acquisition in the preset time period; and if the actual data acquisition quantity is smaller than the data target acquisition quantity, determining that the target detection point has data missing acquisition in the preset time period.
In one embodiment of the present disclosure, the method further comprises: and taking the difference value between the data target acquisition quantity and the data actual acquisition quantity as the data missing acquisition quantity.
In the embodiment of the application, the acquisition frequency corresponding to the target detection point is acquired, the data target acquisition quantity is calculated according to the actual acquisition time length and the acquisition frequency, the data actual acquisition quantity is compared with the data target acquisition quantity, if the data actual acquisition quantity is greater than or equal to the data target acquisition quantity, the non-missing acquisition is determined, and if the data actual acquisition quantity is less than the data target acquisition quantity, the missing acquisition is determined.
Missing is understood to mean that the measured value that was supposed to be acquired is not acquired for some reason. In one embodiment of the present disclosure, the method further comprises displaying a data detection result in the data detection interface, wherein the data detection result comprises at least one of: the name of the target detection point, the real-time value of the data, whether the real-time value of the data is valid or not, and the number of invalid data; whether data missing is existed or not, and the data missing is counted.
FIG. 4 is a schematic page view of a data detection interface provided by an embodiment of the present disclosure; as shown in fig. 4, the detection results of a plurality of detection points may be displayed in the data detection interface, for example: detection point 1, detection point 2, detection 3, … …, detection point N. Each detection point displays a corresponding data detection result, wherein the data detection result comprises: the data valid range (upper and lower detection points as shown in fig. 4), the acquisition frequency, the detection point real-time value, and whether the acquired real-time value is valid, the number of invalid values, whether there is missed acquisition, the number of missed acquisition, and the like.
Further, as shown in fig. 4, the data detection interface further includes: the data detection system enables/disables the control, and when the data detection system is in a disabled state, the data detection system is in an enabled state in response to a trigger operation of the data detection system enabling/disabling the control. When the data detection system is in the enabled state, the data detection system is in the disabled state in response to a trigger operation of the enable/disable control of the data detection system. And when the data detection system is in a disabled state, the acquired numerical values of the detection points are not detected any more. And when the data detection system is in an enabling state, detecting the acquired numerical value of the detection point and displaying the numerical value in an interface of the data detection system.
Further, the data detection interface further comprises a detection frequency control, and the detection frequency of the data detection system can be set in response to the input operation of the detection frequency control, wherein the detection frequency is the frequency of the data detection system executing the data accuracy detection method provided by the embodiment of the application. The detection frequency is smaller than the minimum value of the acquisition frequencies corresponding to all detection points, and optionally, the detection frequency is the minimum value of the acquisition frequencies corresponding to all detection points.
Further, as shown in fig. 4, a time period selection control is further included in the data detection interface, and a time period for data acquisition, that is, a preset time period described in the above embodiment, is set in response to a triggering operation of the time period selection control. The data detection interface also comprises a detection point selection control, and all detection points in the SCADA system are displayed as detection points to be selected in response to the triggering operation of the user on the detection point selection control. The user may select one or more target detection points from the candidate detection points. Fig. 5 is a schematic structural diagram of a data accuracy detecting device in an embodiment of the present disclosure, where the embodiment is applicable to detecting accuracy of data collected in a SCADA system, and the data accuracy detecting device may be implemented in a software and/or hardware manner.
As shown in fig. 5, the data accuracy detecting apparatus provided in the embodiment of the present disclosure includes: a data value acquisition module 51, a valid range comparison module 52, and a valid data judgment module 53.
The data value obtaining module 51 is configured to obtain a data attribute value and a data real value of the target detection point, where the data attribute value includes a data valid range; an effective range comparing module 52, configured to determine whether the real-time data value is within the effective range of the data; and an effective data judging module 53, configured to judge whether the real-time data value is effective data based on the quantitative relation between the real-time data value and the effective data range.
In one embodiment of the present disclosure, the data attribute value further includes: collecting frequency; the apparatus further comprises: the actual acquisition quantity acquisition module is used for acquiring the actual acquisition quantity of the data acquired by the target detection point in a preset time period; the target acquisition quantity calculation module is used for calculating the data target acquisition quantity based on the preset time period and the sampling frequency; and the data missing acquisition judging module is used for judging whether the data missing acquisition exists in the target detection point in the preset time period based on the quantity relation between the actual data acquisition quantity and the data target acquisition quantity.
In one embodiment of the present disclosure, a data missing acquisition judgment module is configured to include: the missing acquisition determining unit is used for determining that the target detection point does not have data missing acquisition in the preset time period if the actual data acquisition number is greater than or equal to the data target acquisition number; and the missing acquisition determining unit is used for determining that the target detection point has missing data acquisition in the preset time period if the actual data acquisition number is smaller than the target data acquisition number.
In one embodiment of the present disclosure, the apparatus further comprises: and the missing acquisition quantity determining unit is used for taking the difference value between the data target acquisition quantity and the data actual acquisition quantity as the data missing acquisition quantity.
In one embodiment of the present disclosure, the apparatus further comprises: the detection result display module is used for displaying a data detection result in the data detection interface, wherein the data detection result comprises at least one of the following steps: the name of the target detection point, the real-time value of the data, whether the real-time value of the data is valid or not, and the number of invalid data; whether data missing is existed or not, and the data missing is counted.
In one embodiment of the present disclosure, the apparatus further comprises: the selection control display module is used for displaying a detection point selection control in the data detection interface; the detection point to be selected display module is used for responding to the operation of selecting a control along with the detection point to acquire and display a plurality of detection points to be selected; the target detection point selection module is used for responding to the selection operation of the plurality of detection points to be selected and selecting at least one target detection point from the detection points to be selected.
The data accuracy detection device provided by the embodiment of the present disclosure may perform the steps performed in the data accuracy detection method provided by the embodiment of the present disclosure, and the performing steps and the beneficial effects are not described herein.
Fig. 6 is a schematic structural diagram of an electronic device in an embodiment of the disclosure. Referring now in particular to fig. 6, a schematic diagram of an electronic device 600 suitable for use in implementing embodiments of the present disclosure is shown. The electronic device 600 in the embodiments of the present disclosure may include, but is not limited to, a device such as a supercomputer. The electronic device shown in fig. 6 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
As shown in fig. 6, the electronic device 600 may include a processing means (e.g., a central processing unit, a graphic processor, etc.) 601 that may perform various suitable actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603 to implement a data accuracy detection method of an embodiment as described in the present disclosure. In the RAM 603, various programs and data required for the operation of the terminal apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
In general, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, and the like; an output device 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, magnetic tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the terminal device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 shows a terminal device 600 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flowcharts, thereby implementing the data accuracy detection method as described above. In such an embodiment, the computer program may be downloaded and installed from a network via communication means 609, or from storage means 608, or from ROM 602. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing device 601.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
In a possible implementation of the disclosure, the computer readable medium carries one or more programs, which when executed by the terminal device, enable the terminal device to implement the data accuracy detection method according to any one of the foregoing embodiments.
In a possible implementation of the present disclosure, the terminal device may also perform other steps described in the above embodiments when the above one or more programs are executed by the terminal device.
Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).
Moreover, although operations are depicted in a particular order, this should not be requiring that such operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (10)
1. A method for detecting accuracy of data, comprising:
acquiring a data attribute value and a data real-time value of a target detection point, wherein the data attribute value comprises a data effective range;
comparing the data real-time value with the data valid range;
and judging whether the data real-time value is effective data or not based on the quantitative relation between the data real-time value and the data effective range.
2. The data accuracy detection method according to claim 1, wherein determining whether the data real-time value is valid data based on a quantitative relationship between the data real-time value and the data valid range, comprises:
if the data real-time value is within the data effective range, determining that the data is effective data in real time;
and if the data real-time value is not in the data valid range, determining that the data is invalid in real time.
3. The method of claim 1, wherein the data attribute value further comprises: collecting frequency;
acquiring the actual acquisition quantity of the data acquired by the target detection point in a preset time period;
calculating the data target acquisition quantity based on the preset time period and the sampling frequency;
and judging whether the data missing acquisition exists in the target detection point in the preset time period or not based on the quantitative relation between the actual data acquisition quantity and the data target acquisition quantity.
4. The method according to claim 3, wherein determining whether or not the target detection point has data missing in the preset period based on a quantitative relation between the actual collection quantity of the data and the target collection quantity of the data, comprises:
if the actual data acquisition quantity is greater than or equal to the data target acquisition quantity, determining that the target detection point does not have data missing acquisition in the preset time period;
and if the actual data acquisition quantity is smaller than the data target acquisition quantity, determining that the target detection point has data missing acquisition in the preset time period.
5. The method of claim 4, further comprising:
and taking the difference value between the data target acquisition quantity and the data actual acquisition quantity as the data missing acquisition quantity.
6. The method of claim 2, 4 or 5, further comprising:
displaying a data detection result in a data detection interface, wherein the data detection result comprises at least one of the following: the name of the target detection point, the real-time value of the data, whether the real-time value of the data is valid or not, and the number of invalid data; whether data missing is existed or not, and the data missing is counted.
7. The method of claim 1, further comprising:
displaying a detection point selection control in a data detection interface;
responding to the operation of selecting a control along with the detection point, and acquiring and displaying a plurality of detection points to be selected;
and responding to the selection operation of the plurality of detection points to be selected, and selecting at least one target detection point from the detection points to be selected.
8. A data accuracy detecting apparatus, comprising:
The data value acquisition module is used for acquiring data attribute values and data real-time values of the target detection points, wherein the data attribute values comprise data effective ranges;
the effective range comparison module is used for judging whether the data real-time value is in the data effective range or not;
and the effective data judging module is used for judging whether the data real-time value is effective data or not based on the quantity relation between the data real-time value and the data effective range.
9. An electronic device, the electronic device comprising:
one or more processors;
a storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data accuracy detection method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements the data accuracy detection method according to any one of claims 1-7.
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| CN202311207225.XA CN117370319A (en) | 2023-09-18 | 2023-09-18 | Data accuracy detection method, device, equipment and storage medium |
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| CN202311207225.XA CN117370319A (en) | 2023-09-18 | 2023-09-18 | Data accuracy detection method, device, equipment and storage medium |
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