CN111241475B - Power consumption classification processing method, device, storage medium and processor - Google Patents
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Abstract
The invention discloses a power consumption classification processing method, a device, a storage medium and a processor. Wherein the method comprises the following steps: collecting power consumption data for a plurality of times within a period of time, wherein the power consumption data are collected by the equipment in a normal working state; determining the minimum value and the maximum value in a plurality of acquired power consumption data; selecting a value between the maximum value and the minimum value as a threshold value; and dividing the power consumption data into two types of static power consumption and dynamic power consumption according to the threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value. The invention solves the technical problem that the power consumption data of the equipment cannot be effectively distinguished in the prior art.
Description
Technical Field
The present invention relates to the field of data processing, and in particular, to a method and apparatus for classifying and processing power consumption, a storage medium, and a processor.
Background
Nowadays, performance indexes of static power consumption and dynamic power consumption are often provided for various electronic devices in engineering application, for example, the power consumption of the device when receiving and transmitting radio frequency signals is dynamic power consumption, and the power consumption of the device when receiving and transmitting radio frequency signals is not dynamic power consumption. In order to distinguish static and dynamic power consumption, in the measurement process, the prior art needs to apply an intervention to the working state of the equipment to enable the equipment to be in a static or dynamic working mode, but in some cases, the intervention cannot be realized or is inconvenient to realize; the power consumption of the equipment is acquired, and the acquired power consumption data not only comprises data in static working but also comprises data in dynamic working, so that the existing method cannot be distinguished.
The existing power consumption measuring method has the following defects:
(1) Existing power consumption measurement methods need to limit the tested device to be in a static operation mode (such as no radio frequency signal transceiving) or a dynamic operation mode (such as radio frequency signal transceiving), and the actual device usually works in a static state or a dynamic state randomly and alternately, and cannot or is inconvenient to control.
(2) The power consumption data acquired by the existing power consumption measuring method not only comprises static data, but also comprises dynamic data, and cannot be effectively distinguished.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a power consumption classification processing method, a device, a storage medium and a processor, which are used for at least solving the technical problem that the power consumption data of equipment cannot be effectively distinguished in the prior art.
According to an aspect of an embodiment of the present invention, there is provided a power consumption classification processing method, including: collecting power consumption data for a plurality of times within a period of time, wherein the power consumption data are collected by equipment in a normal working state; determining the minimum value and the maximum value in a plurality of acquired power consumption data; selecting a value between the maximum value and the minimum value as a threshold value; dividing the power consumption data into two types of static power consumption and dynamic power consumption according to the threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value; selecting a value between the maximum value and the minimum value as the threshold value includes: acquiring a predetermined number of multiple thresholds between the maximum value and the minimum value, wherein the multiple thresholds are different; acquiring variances between two types of power consumption data divided by each threshold, wherein the power consumption data smaller than or equal to the threshold are one type of power consumption data, and the power consumption data larger than the threshold are the other type of power consumption data; taking a threshold value with minimum variance as a threshold value selected between the maximum value and the minimum value;
the threshold with the smallest variance as the threshold selected between the maximum value and the minimum value comprises:wherein q 1 (t) probability of being one type of power consumption data, q 2 (t) probability of another type of power consumption data, μ 1 (t) is the average value of a class of power consumption data, μ 2 (t) is the average value of another type of power consumption data, t is a threshold value, < >>Is the variance between classes.
Optionally, obtaining a predetermined number of multiple thresholds between the maximum value and the minimum value comprises: and taking each integer between the maximum value and the minimum value as a threshold value, wherein the plurality of threshold values comprise a plurality of integers.
Optionally, the threshold value is taken as the maximum static power consumption of the device, and the maximum value is taken as the maximum dynamic power consumption of the device.
According to another aspect of the embodiment of the present invention, there is also provided a power consumption classification processing apparatus, including: the acquisition module is used for acquiring power consumption data for a plurality of times within a period of time, wherein the power consumption data are acquired by the equipment in a normal working state; the determining module is used for determining the minimum value and the maximum value in the acquired multiple power consumption data; a selection module for selecting a value between the maximum value and the minimum value as a threshold value; the dividing module is used for dividing the power consumption data into two types of static power consumption and dynamic power consumption according to the threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value; the selection module comprises: a first acquisition unit configured to acquire a predetermined number of multiple thresholds between the maximum value and the minimum value, wherein the multiple thresholds are different; a second obtaining unit, configured to obtain a variance between two types of power consumption data divided by each threshold, where the power consumption data is less than or equal to the threshold and the power consumption data is greater than the threshold; a processing unit for taking a threshold value with minimum variance as a threshold value selected between the maximum value and the minimum value; the threshold with the smallest variance as the threshold selected between the maximum value and the minimum value comprises:wherein q 1 (t) probability of being one type of power consumption data, q 2 (t) probability of another type of power consumption data, μ 1 (t) is the average value of a class of power consumption data, μ 2 (t) is the average value of another type of power consumption data, t is a threshold value, < >>Is the variance between classes.
Optionally, the first acquisition unit includes: and a processing subunit configured to take each integer between the maximum value and the minimum value as a threshold, where the plurality of thresholds includes a plurality of integers.
According to another aspect of the embodiment of the present invention, there is further provided a storage medium, where the storage medium includes a stored program, and when the program runs, the device where the storage medium is controlled to execute any one of the above-mentioned power consumption classification processing methods.
According to another aspect of the embodiment of the present invention, there is further provided a processor, configured to execute a program, where the program executes any one of the above methods for classifying power consumption.
In the embodiment of the invention, the power consumption data are acquired for a plurality of times within a period of time, wherein the power consumption data are acquired by the equipment in a normal working state; determining the minimum value and the maximum value in a plurality of acquired power consumption data; selecting a value between the maximum value and the minimum value as a threshold value; the power consumption data are divided into two types of static power consumption and dynamic power consumption according to the threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value, and the acquired power consumption data are divided by a maximum inter-class variance threshold value dividing method, so that the purpose of accurately distinguishing the static power consumption from the dynamic power consumption is achieved, the technical effects of automatically and effectively distinguishing the static power consumption and the dynamic power consumption of tested equipment without adding other interventions are achieved, and the technical problem that the power consumption data of the equipment cannot be effectively distinguished in the prior art is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of a power consumption classification processing method according to an embodiment of the invention;
fig. 2 is a schematic diagram of a power consumption classification processing apparatus according to an embodiment of the invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
According to an embodiment of the present invention, there is provided an embodiment of a power consumption classification processing method, it being noted that the steps shown in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in an order other than that shown or described herein.
Fig. 1 is a flowchart of a power consumption classification processing method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, collecting power consumption data for a plurality of times within a period of time, wherein the power consumption data are collected by the equipment in a normal working state;
as an alternative embodiment, the power consumption data is collected for a period of time under the normal working state of the device, during which the device works in static and dynamic modes randomly and alternately, the collected data is stored in an array according to the power consumption value, the subscript of the array is the power consumption value, and the value of the array element is the number of times of collecting the power consumption statistics corresponding to the subscript, so that a histogram of the power consumption data is formed.
It should be noted that during the measurement period, the device under test is in a normal working state, and no special control and operation are required.
Step S104, determining the minimum value and the maximum value in the acquired multiple power consumption data;
step S106, selecting a value between the maximum value and the minimum value as a threshold value;
and S108, dividing the power consumption data into two types of static power consumption and dynamic power consumption according to a threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value.
Through the steps, the power consumption data can be acquired for a plurality of times within a period of time, wherein the power consumption data are acquired by the equipment in a normal working state; determining the minimum value and the maximum value in a plurality of acquired power consumption data; selecting a value between the maximum value and the minimum value as a threshold value; the method comprises the steps of dividing power consumption data into two types of static power consumption and dynamic power consumption according to a threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value, dividing the acquired power consumption data by a maximum inter-class variance threshold value dividing method, so that the purpose of accurately distinguishing the static power consumption from the dynamic power consumption is achieved, the static power consumption and the dynamic power consumption of tested equipment are automatically and effectively distinguished, the technical effect of other intervention is not required to be added, and the technical problem that the power consumption data of the equipment cannot be effectively distinguished in the prior art is solved.
Optionally, selecting a value between the maximum value and the minimum value as the threshold value includes: acquiring a predetermined number of multiple thresholds between a maximum value and a minimum value, wherein the multiple thresholds are different; acquiring variances between two types of power consumption data divided by each threshold, wherein the power consumption data smaller than or equal to the threshold are one type of power consumption data, and the power consumption data larger than the threshold are the other type of power consumption data; the threshold with the smallest variance is taken as the threshold selected between the maximum value and the minimum value.
By a predetermined number of the plurality of threshold values, the power consumption data can be more effectively divided, and the division result is more accurate.
Optionally, obtaining a predetermined number of the plurality of thresholds between the maximum value and the minimum value comprises: each integer between the maximum value and the minimum value is taken as a threshold value, wherein the plurality of threshold values comprises a plurality of integers.
In determining the threshold value, the number of threshold values is not limited in any way, and as an alternative embodiment, each integer between the maximum value and the minimum value may be taken as the threshold value, so that there is at least one threshold value. When the threshold value is multiple, each threshold value can be uniquely corresponding to an integer.
Optionally, taking the threshold with the smallest variance as the threshold selected between the maximum value and the minimum value includes:wherein q 1 (t) probability of being one type of power consumption data, q 2 (t) probability of another type of power consumption data, μ 1 (t) is the average value of a class of power consumption data, μ 2 (t) is the average value of another type of power consumption data, t is a threshold value, < >>Is the variance between classes.
As an alternative implementation manner, the selected threshold value is t, the power consumption data is divided into two types by the threshold value t, C1 and C2, C1 represents the data with the power consumption value within the range of [ MIN, t ], and C2 represents the data with the power consumption value within the range of [ t+1, max ], and the specific solving mode is as follows:
the probabilities of C1 and C2 are respectively:
the average values of C1 and C2 are respectively:
the variances within the C1 and C2 classes are:
the inter-class variance is:
by traversing the power consumption values in [ MIN, MAX ], the power consumption value with the largest inter-class variance is obtained as the threshold t, i.e., the power consumption data is divided into a static power consumption class and a dynamic power consumption class. Alternatively, the power consumption value that minimizes the intra-class variance may be used as the threshold value.
Optionally, the threshold value is taken as the maximum static power consumption of the device, and the maximum value is taken as the maximum dynamic power consumption of the device.
Example 2
According to another aspect of the embodiment of the present invention, there is provided a power consumption classification processing apparatus, fig. 2 is a schematic diagram of the power consumption classification processing apparatus according to the embodiment of the present invention, as shown in fig. 2, the power consumption classification processing apparatus includes: the system comprises an acquisition module 22, a determination module 24, a selection module 26 and a division module 28. The power consumption classification processing apparatus will be described in detail below.
The acquisition module 22 is configured to acquire power consumption data multiple times within a period of time, where the power consumption data is acquired by the device in a normal working state;
as an alternative embodiment, the power consumption data is collected for a period of time under the normal working state of the device, during which the device works in static and dynamic modes randomly and alternately, the collected data is stored in an array according to the power consumption value, the subscript of the array is the power consumption value, and the value of the array element is the number of times of collecting the power consumption statistics corresponding to the subscript, so that a histogram of the power consumption data is formed.
It should be noted that during the measurement period, the device under test is in a normal working state, and no special control and operation are required.
A determining module 24, connected to the collecting module 22, for determining a minimum value and a maximum value of the collected multiple power consumption data;
a selection module 26, coupled to the determination module 24, for selecting a value between a maximum value and a minimum value as a threshold value;
the dividing module 28 is connected to the selecting module 26, and is configured to divide the power consumption data into two types of static power consumption and dynamic power consumption according to a threshold value, where the static power consumption is less than or equal to the threshold value, and the dynamic power consumption is greater than the threshold value.
Here, the above-mentioned acquisition module 22, determination module 24, selection module 26 and division module 28 correspond to steps S102 to S108 in embodiment 1, and the above-mentioned modules are the same as examples and application scenarios implemented by the corresponding steps, but are not limited to those disclosed in embodiment 1. It should be noted that the modules described above may be implemented as part of an apparatus in a computer system, such as a set of computer-executable instructions.
The modules in the device are combined, and the acquired power consumption data is segmented by a maximum inter-class variance threshold segmentation method, so that the purpose of accurately distinguishing static power consumption from dynamic power consumption is achieved, the static power consumption and the dynamic power consumption of tested equipment are automatically and effectively distinguished, the technical effect of other interventions is not required to be added, and the technical problem that the power consumption data of the equipment cannot be effectively distinguished in the prior art is solved.
Optionally, the selecting module includes: a first acquisition unit configured to acquire a predetermined number of multiple thresholds between a maximum value and a minimum value, wherein the multiple thresholds are different; the second acquisition unit is used for acquiring the variance between the two types of power consumption data divided by each threshold value, wherein the power consumption data is one type of power consumption data smaller than or equal to the threshold value, and the power consumption data is the other type of power consumption data larger than the threshold value; and the processing unit is used for taking the threshold value with the minimum variance as the threshold value selected between the maximum value and the minimum value.
The power consumption data can be more effectively segmented through a plurality of thresholds with preset quantity in the module, and the segmentation result is more accurate.
Optionally, the first acquisition unit includes: and the processing subunit is used for taking each integer between the maximum value and the minimum value as a threshold value, wherein the plurality of threshold values comprise a plurality of integers.
In determining the threshold value, the number of threshold values is not limited in any way, and as an alternative embodiment, each integer between the maximum value and the minimum value may be taken as the threshold value, so that there is at least one threshold value. When the threshold value is multiple, each threshold value can be uniquely corresponding to an integer.
Optionally, taking the threshold with the smallest variance as the threshold selected between the maximum value and the minimum value includes:wherein q 1 (t) probability of being one type of power consumption data, q 2 (t) is another type of Power consumption dataProbability of mu 1 (t) is the average value of a class of power consumption data, μ 2 (t) is the average value of another type of power consumption data, t is a threshold value, < >>Is the variance between classes.
As an alternative implementation manner, the selected threshold value is t, the power consumption data is divided into two types by the threshold value t, C1 and C2, C1 represents the data with the power consumption value within the range of [ MIN, t ], and C2 represents the data with the power consumption value within the range of [ t+1, max ], and the specific solving mode is as follows:
the probabilities of C1 and C2 are respectively:
the average values of C1 and C2 are respectively:
the variances within the C1 and C2 classes are:
the inter-class variance is:
by traversing the power consumption values in [ MIN, MAX ], the power consumption value with the largest inter-class variance is obtained as the threshold t, i.e., the power consumption data is divided into a static power consumption class and a dynamic power consumption class. Alternatively, the power consumption value that minimizes the intra-class variance may be used as the threshold value.
Optionally, the threshold value is taken as the maximum static power consumption of the device, and the maximum value is taken as the maximum dynamic power consumption of the device.
Example 3
According to another aspect of the embodiment of the present invention, there is also provided a storage medium, the storage medium including a stored program, wherein the device in which the storage medium is controlled to execute any one of the above-described power consumption classification processing methods when the program runs.
Example 4
According to another aspect of the embodiment of the present invention, there is also provided a processor, configured to execute a program, where the program executes any one of the above power consumption classification processing methods.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (7)
1. A power consumption classification processing method, characterized by comprising:
collecting power consumption data for a plurality of times within a period of time, wherein the power consumption data are collected by equipment in a normal working state;
determining the minimum value and the maximum value in a plurality of acquired power consumption data;
selecting a value between the maximum value and the minimum value as a threshold value;
dividing the power consumption data into two types of static power consumption and dynamic power consumption according to the threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value;
wherein selecting a value between the maximum value and the minimum value as the threshold value comprises:
acquiring a predetermined number of multiple thresholds between the maximum value and the minimum value, wherein the multiple thresholds are different;
acquiring variances between two types of power consumption data divided by each threshold, wherein the power consumption data smaller than or equal to the threshold are one type of power consumption data, and the power consumption data larger than the threshold are the other type of power consumption data;
taking a threshold value with minimum variance as a threshold value selected between the maximum value and the minimum value;
wherein taking the threshold with the smallest variance as the threshold selected between the maximum value and the minimum value comprises:
wherein q 1 (t) probability of being one type of power consumption data, q 2 (t) probability of another type of power consumption data, μ 1 (t) is the average value of a class of power consumption data, μ 2 (t) is the average value of another type of power consumption data, t is a threshold value,is the variance between classes.
2. The method of claim 1, wherein obtaining a predetermined number of multiple thresholds between the maximum value and the minimum value comprises:
and taking each integer between the maximum value and the minimum value as a threshold value, wherein the plurality of threshold values comprise a plurality of integers.
3. The method according to claim 1 or 2, characterized in that the threshold value is taken as the maximum static power consumption of the device and the maximum value is taken as the maximum dynamic power consumption of the device.
4. A power consumption classification processing apparatus, characterized by comprising:
the acquisition module is used for acquiring power consumption data for a plurality of times within a period of time, wherein the power consumption data are acquired by the equipment in a normal working state;
the determining module is used for determining the minimum value and the maximum value in the acquired multiple power consumption data;
a selection module for selecting a value between the maximum value and the minimum value as a threshold value;
the dividing module is used for dividing the power consumption data into two types of static power consumption and dynamic power consumption according to the threshold value, wherein the static power consumption is smaller than or equal to the threshold value, and the dynamic power consumption is larger than the threshold value;
the selection module comprises:
a first acquisition unit configured to acquire a predetermined number of multiple thresholds between the maximum value and the minimum value, wherein the multiple thresholds are different;
a second obtaining unit, configured to obtain a variance between two types of power consumption data divided by each threshold, where the power consumption data is less than or equal to the threshold and the power consumption data is greater than the threshold;
a processing unit for taking a threshold value with minimum variance as a threshold value selected between the maximum value and the minimum value;
wherein taking the threshold with the smallest variance as the threshold selected between the maximum value and the minimum value comprises:
wherein q 1 (t) probability of being one type of power consumption data, q 2 (t) probability of another type of power consumption data, μ 1 (t) is the average value of a class of power consumption data, μ 2 (t) is the average value of another type of power consumption data, t is a threshold value,is the variance between classes.
5. The apparatus of claim 4, wherein the first acquisition unit comprises:
and a processing subunit configured to take each integer between the maximum value and the minimum value as a threshold, where the plurality of thresholds includes a plurality of integers.
6. A storage medium comprising a stored program, wherein the program, when run, controls a device in which the storage medium is located to execute the power consumption classification processing method according to any one of claims 1 to 3.
7. A processor for executing a program, wherein the program executes the power consumption classification processing method according to any one of claims 1 to 3.
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