CN111929586B - Method and equipment for evaluating charging state of passive wireless monitoring device - Google Patents
Method and equipment for evaluating charging state of passive wireless monitoring device Download PDFInfo
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
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Abstract
The application discloses a charging state evaluation method and equipment of a passive wireless monitoring device, which are used for solving the technical problems that the existing charging state evaluation method wastes a great deal of manpower and material resources and the evaluation process is complicated. The method comprises the following steps: preprocessing log data uploaded by the passive wireless monitoring device to obtain microclimate data and charging data corresponding to the passive wireless monitoring device; determining the output power of the solar panel of the passive wireless monitoring device through the corresponding relation between pre-stored microclimate data and the output power of the solar panel; according to the charging data, the charging power of the passive wireless monitoring device is calculated; and determining a charging state evaluation value of the passive wireless monitoring device according to the relation between the output power and the charging power and a preset evaluation coefficient. According to the method, the charging state is quantitatively evaluated, the abnormal charging device can be processed in advance, and the efficient and simple charging state evaluation method is realized.
Description
Technical Field
The application relates to the technical field of passive wireless monitoring devices, in particular to a method and equipment for evaluating the charging state of a passive wireless monitoring device.
Background
Because of the special charging mode, the passive wireless monitoring device can only adopt passive modes such as a solar panel and the like for charging. However, the efficiency of charging by solar energy is closely related to the weather conditions of the place where the passive wireless monitoring device is located, and when the sunlight is insufficient, the charging efficiency is low easily. The acquisition state of the solar panel determines whether the storage battery of the passive wireless monitoring device can acquire sufficient electric quantity, and further the monitoring function of the monitoring device is affected. Therefore, it is important to evaluate the state of charge of the passive wireless monitoring device.
However, in the prior art, in the charge state evaluation of the passive wireless monitoring device, a manual log inquiry mode is generally adopted, so that a great deal of manpower, time and energy are wasted, and the evaluation process is tedious and complex.
Disclosure of Invention
The embodiment of the application provides a method and equipment for evaluating the charging state of a passive wireless monitoring device, which are used for solving the technical problems that a great deal of manpower and time are wasted and the evaluation process is complicated when the charging state of the passive wireless monitoring device is evaluated in the prior art.
In one aspect, an embodiment of the present application provides a method for evaluating a charging state of a passive wireless monitoring device, including: preprocessing log data uploaded by the passive wireless monitoring device to obtain microclimate data and charging data corresponding to the passive wireless monitoring device; wherein the microclimate data comprises at least any one of the following: temperature, light radiation illuminance; the charging data includes at least any one of the following: charging current, charging voltage; determining the output power of the solar panel of the passive wireless monitoring device through the corresponding relation between the pre-stored microclimate data and the output power of the solar panel of the passive wireless monitoring device; according to the charging data, the charging power of the passive wireless monitoring device is calculated; and determining a charging state evaluation value of the passive wireless monitoring device according to the relation between the output power and the charging power and a preset evaluation coefficient.
According to the charging state evaluation method provided by the embodiment of the application, the log data of the passive wireless monitoring device is cleaned and screened to obtain the corresponding microclimate data and charging data; and obtaining the charging power of the passive wireless monitoring device and the output power of the solar panel based on the microclimate data and the charging data, thereby obtaining the relationship between the two. And calculating an evaluation value of the state of charge based on a preset evaluation coefficient. The quantitative evaluation is realized on the charging state, the quantitative change is dynamically changed along with factors such as the environment where the monitoring device is located, and the real evaluation of the charging state of the monitoring device can be given out in real time, so that the device with abnormal charging state can be focused on in a targeted manner, and the purposes of pre-estimating and diagnosing in advance are achieved. The charging state evaluation value is determined through the relation between the output power and the charging power and the preset evaluation coefficient, so that a simple and efficient evaluation mode is provided, human participation is reduced, and a quick and efficient evaluation process is realized.
In one implementation manner of the present application, preprocessing log data uploaded by a passive wireless monitoring device specifically includes: filtering and cleaning the log data, and removing abnormal log data to obtain first log data; and screening the content of the first log data, and extracting microclimate data and the charging data contained in the first log data.
In one implementation of the present application, the method further comprises: determining output power corresponding to different moments in each hour in a first preset mode based on microclimate data at different moments in each hour by taking the hour as a minimum unit; determining charging power corresponding to different moments in each hour according to charging data at different moments in each hour in a second preset mode; and calculating the mean square error between the output power and the charging power corresponding to each hour according to the output power and the charging power corresponding to each hour.
In one implementation of the present application, the method further comprises: screening the first log data content, and extracting geographic position data and season-related data contained in the first log data; and acquiring a preset evaluation coefficient of the passive wireless monitoring device from an evaluation coefficient database according to the geographic position data and the season related data.
In one implementation of the application, the geographic location data includes the longitude and latitude of the location where the passive wireless monitoring device is located; the season-related data mainly includes any one or more of the following: season, sunrise time, sunset time.
In one implementation of the present application, the method further comprises: the mean square error and the preset evaluation coefficient are in a matrix form; multiplying the mean square error matrix with a preset evaluation coefficient matrix to obtain a result matrix; and calculating determinant values corresponding to the result matrix to obtain a charging state evaluation value of the passive wireless monitoring device. By combining the mean square error with a preset evaluation coefficient, a simple and efficient method for obtaining the evaluation value is realized, and an effective method is provided for the evaluation process of the charging state of the passive wireless monitoring device.
In one implementation of the present application, the preset evaluation coefficient matrix is a 24×1 matrix; wherein 24 elements are respectively in one-to-one correspondence with 24 hours; the 1 st to 9 th and 16 th to 24 th element values in the 24 elements are rounded to zero. The charging process of the solar cell panel is mainly concentrated in the time period from 10 hours to 15 hours, so that the rest elements except the 10 th to 15 th elements in the preset evaluation coefficient are set to be close to zero values, namely the rest elements are rounded to be zero values, the actual situation is fully combined, and the charging state evaluation value obtained by the method provided by the embodiment of the application is ensured to be more close to the actual state.
In one implementation of the present application, after determining the state of charge evaluation value of the passive wireless monitoring device, the method further includes: and calculating a difference value between the charge state evaluation value and the mean square error standard value, determining that the passive wireless monitoring device is abnormal in charge under the condition that the difference value is larger than a preset threshold value, and sending the abnormal charge information to the mobile terminal. And the abnormal information when the charge state evaluation value is abnormal is timely sent to the mobile terminal, so that the technical effect of pre-estimating and pre-judging the charge state abnormal monitoring device in advance is achieved.
In one implementation of the present application, the method further comprises: under the condition that the passive wireless monitoring device normally operates, calculating the mean square error between the output power and the charging power which are respectively corresponding in each hour within a preset number of days; and averaging the mean square errors to obtain a mean square error standard value.
On the other hand, the embodiment of the application also provides a charging state evaluation device of the passive wireless monitoring device, which comprises: a processor; and a memory having executable code stored thereon that, when executed, causes the processor to perform a method of evaluating a state of charge of a passive wireless monitoring device as described above.
According to the charging state evaluation equipment of the passive wireless monitoring device, provided by the embodiment of the application, the mean square error between the charging power of the passive wireless monitoring device and the output power of the solar panel and the preset evaluation coefficient are determined through the microclimate data, the charging data, the geographic position information data and the season related data obtained by processing the log data, so that the evaluation value of the charging state is obtained. The quantitative evaluation of the charging state is realized, the quantitative evaluation dynamically changes along with the change of factors such as the environment where the passive wireless monitoring device is located, and the real evaluation of the charging state of the monitoring device can be given in real time, so that the device with abnormal charging state can be focused in a targeted manner, and the purposes of pre-estimating and diagnosing in advance are achieved. The method provides a simplified and efficient evaluation mode by combining the difference value and a preset evaluation coefficient, reduces human participation, and realizes a quick and efficient evaluation process.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
fig. 1 is a flowchart of a method for evaluating a charging state of a passive wireless monitoring device according to an embodiment of the present application;
fig. 2 is a schematic diagram of an internal structure of a charge state evaluation device of a passive wireless monitoring device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Because of the specificity of the power supply mode, the passive wireless monitoring device can only adopt passive modes such as a solar panel and the like for charging, and the efficiency of the power supply mode is closely related to the meteorological conditions of the position of the passive wireless monitoring device. The acquisition state of the solar cell panel determines whether the storage battery can acquire sufficient electric quantity, and then the monitoring function of the passive wireless monitoring device is affected.
Passive wireless monitoring devices have no good solution for charge state evaluation, and in most cases, the monitoring device only finds that the running state of the monitoring device is abnormal after the monitoring device shoots the abnormal state or no log is uploaded. In the running state anomaly analysis and statistics process, the charging state anomalies occupy a large proportion. In the tracing process, more people look for a great number of past journals to find the reasons of abnormality and evaluate the charging state. This approach not only wastes a lot of manpower and materials, but also makes the evaluation process of the state of charge cumbersome and complicated.
The embodiment of the application provides a charging state evaluation method and equipment of a passive wireless monitoring device, which are used for obtaining the charging power of the passive wireless monitoring device and the output power of a solar panel by analyzing log data. And then calculating an evaluation value of the charging state through a relation between the two and a preset evaluation coefficient, and carrying out quantitative evaluation on the charging state. The technical problems that the existing assessment method wastes a great deal of manpower and time cost and the assessment process is complex and complicated are solved.
The following describes the technical scheme provided by the embodiment of the application in detail through the attached drawings.
Fig. 1 is a flowchart of a method for evaluating a charging state of a passive wireless monitoring device according to an embodiment of the present application. As shown in fig. 1, the evaluation method provided by the embodiment of the present application mainly includes the following steps:
and step 101, the server receives the log data of the monitoring device and preprocesses the log data.
And the server receives the log data uploaded by the passive wireless monitoring device in real time and preprocesses the log data. The preprocessing of the log data mainly comprises the following steps:
firstly, filtering and cleaning log data, and removing abnormal log data.
The log data of the anomaly here mainly includes any one of the following: the log content is incomplete and obviously not in line with the actual situation.
Then, the log data content after filtering and cleaning is filtered. Extracting microclimate data and charging data in the step 2; and geographic location data, season-related data in step 4.
And 102, obtaining microclimate data and charging data corresponding to the passive wireless monitoring device.
And extracting the content in the log data to obtain microclimate data and charging data corresponding to the passive wireless monitoring device.
The micro meteorological data mainly comprises the ambient temperature T around the passive wireless monitoring device and the light radiation illuminance L of the passive wireless monitoring device; the charging data mainly comprises battery charging current I and battery charging voltage V of the passive wireless monitoring device.
And step 103, calculating to obtain the mean square error between the output power of the solar panel and the charging power of the passive wireless monitoring device according to the microclimate data and the charging data.
Inquiring an ideal output power reference value table of the solar panel according to the temperature T and the light radiation illuminance L to obtain the output power of the solar panel under the conditions of the temperature T and the light radiation illuminance L。
Then, according to the charging current I and the charging voltage V, the charging power of the passive wireless monitoring device is calculated by the following formula：
In one embodiment of the application, the output power is respectively corresponding to different time points in each hour with the hour as the minimum unitCharging power->The mean square error corresponding to each hour is calculated by the following formula:
where n is the number of times at different times within each hour.
And 104, obtaining geographic position related data and season related data corresponding to the passive wireless monitoring device.
And screening the log data to obtain microclimate data and charging data, and screening out geographic position data and season related data.
The geographic position data includes, but is not limited to, longitude and latitude of the current position of the passive wireless monitoring device. It can be clear to those skilled in the art that the geographic position related data can be obtained by a GPS unit built in the passive wireless monitoring device, and the embodiments of the present application will not be described herein. And may be obtained by other modules or units related to the acquisition location, which is not limited by the comparison of the embodiment of the present application.
The season-related data includes any one or more of: season, sunrise time, sunset time.
The passive wireless monitoring device in the embodiment of the application is charged through the solar panel, and the charging capacity of the solar panel is closely related to the data such as illumination time, illumination intensity and the like. Therefore, the sunrise time and the sunset time contained in the log data are obtained, and the illumination time length in one day is further obtained; the seasonal data is acquired so as to obtain a time period with the strongest illumination intensity in a day corresponding to the current season, and then the power taking capacity of the solar panel in the day under the current season can be determined.
Step 105, determining a preset evaluation coefficient according to the geographic position data and the season related data.
And (4) comprehensively considering the battery charging capacities of the passive wireless monitoring devices in different time periods according to the season-related data and the geographic position-related data obtained in the step (104) to obtain a preset evaluation coefficient.
In one embodiment of the application, the predetermined evaluation coefficients are a series of predetermined values in the form of a 24 x 1 matrix. I.e. in the form of a matrix of 24 rows and 1 column, wherein each element corresponds to an hour point in 24 hours.
In another embodiment of the present application, since the period of time in which the intensity of solar light is strongest is 10 to 15 hours in one day, that is, the period of time in which the battery charging capability is strongest is 10 to 15 hours. Therefore, the specific gravity of the charging power is mainly concentrated in the time period of 10 hours to 15 hours, and therefore, the sum of 10 th to 15 th elements in the matrix of the preset evaluation coefficients is approximately equal to 1, and 1 st to 9 th and 16 th to 24 th elements occupy relatively low, close to zero values. Thus, the 1 st to 9 th, 16 th to 24 th element values are rounded to zero.
In the actual charge state evaluation process, a preset evaluation coefficient corresponding to the current environment data is obtained from an evaluation coefficient database according to the current longitude and latitude information, the current season information and the like of the passive wireless monitoring device. That is, the preset evaluation coefficient matrix in the embodiment of the application is not always unchanged, but correspondingly changed according to different geographic position data and season related data, so as to ensure that the evaluation value finally obtained for the charging state of the passive wireless monitoring device can truly reflect the charging state.
It should be noted that, according to the geographic position data of different passive wireless monitoring devices, the obtained preset evaluation coefficient matrixes are different. And the same passive wireless monitoring device has different corresponding preset evaluation coefficient matrixes under different seasons and illumination conditions.
And 106, calculating to obtain a charge state evaluation value according to a preset evaluation coefficient and a mean square error.
And calculating to obtain an evaluation value of the charging state after obtaining a mean square error between the output power of the solar cell panel and the charging power of the passive wireless monitoring device and a preset evaluation coefficient.
In one embodiment of the present application, the preset evaluation coefficient matrix is in the form of a matrix of 24×1; the mean square error is also in the form of a matrix, which is in particular a matrix of 1 x 24.
Specifically, 24 elements in the mean square error matrix correspond one-to-one with 24 hours in a day. For example, the 10 th element in the mean square error matrix corresponds to the mean square error between the charging power of the passive wireless monitoring device at 10 and the output power of the solar panel at 10.
Further, multiplying the mean square error matrix with a preset evaluation coefficient matrix, and calculating determinant values of the multiplication result matrix to obtain the charging state evaluation value of the passive wireless monitoring device.
Step 107, judging whether the evaluation value is larger than a preset threshold.
After the evaluation value of the state of charge is obtained, the magnitude relation between the evaluation value and a preset evaluation threshold value is determined.
Specifically, the size between the two is determined by a relatively large and small method. And determining whether the charging state of the passive wireless monitoring device is abnormal according to the comparison result.
In one embodiment of the application, the elements in the preset evaluation coefficient matrix are given in the form of percentages.
Thus, a method for judging whether the charge state of the passive wireless monitoring device is abnormal is as follows:
determining a mean square error standard value between the output power of the solar panel and the charging power of the passive wireless monitoring device。
Wherein, the mean square error standard valueIs determined by the following process:
firstly, a plurality of log data of the passive wireless monitoring device in a normal running state are obtained.
The passive wireless monitoring device is in a normal running state, namely, the microclimate data and the charging data of each hour in a plurality of days determined according to a plurality of log data are in a normal state under the condition that the charging state is not abnormal.
Then, according to the microclimate data and the charging data, determining the mean square error of different time periods of multiple daysThen for a plurality of->Taking the mean value to obtain the standard value of the mean square error +.>。
Further, it is determined whether the evaluation value of the state of charge is greater than the mean square error criterion valueAnd then determines whether the charging state of the passive wireless monitoring device is normal.
Step 108, determining that the charging state of the passive wireless monitoring device is not abnormal.
In the case where the evaluation value of the state of charge is smaller than the preset evaluation value, or the evaluation value of the state of charge is smaller than the mean square error criterion valueUnder 60% of the conditions, the state of charge evaluation value is determined to belong to a normal range, and then the state of charge of the passive wireless monitoring device is determined to be abnormal.
Step 109, determining that the evaluation value is abnormal, and transmitting the charge state abnormality information.
In the case where the evaluation value of the state of charge is greater than or equal to the preset evaluation value, or the evaluation value of the state of charge is greater than or equal to the mean square error criterion valueUnder 60% of the conditions, the state of charge evaluation value is determined to be abnormal, and then the state of charge of the passive wireless monitoring device is determined to be abnormal.
In one embodiment of the application, after the abnormal state of charge is determined, charging abnormality information is sent to the mobile terminal of the on-site patrol staff, so that the patrol staff can process the passive wireless monitoring device in time.
The mobile terminal of the patrol staff at least comprises any one of the following: cell phone, tablet, hand-held terminal.
The following is a method for evaluating the charging state of the passive wireless monitoring device provided by the embodiment of the application, and the implementation process of the comprehensive charging state of a certain device with a serial number of 860723043349881 is evaluated on the 3 rd month and 27 th day of 2020 and 11 am.
And the first step, cleaning the real-time log, and screening out microclimate data, charging data, geographic position data and season related data contained in the log data. Meanwhile, the ideal output power reference value table of the solar panel is queried to obtain the reference value table at the current temperatureIlluminance of light radiation->Output power value +.>。
Charging current obtained from log dataCharging voltage->Microclimate data, and an output power value determined from the microclimate data>As shown in the following table.
TABLE 1
Second, calculating the mean square error through microclimate data and charging data。
Thus, the first and second substrates are bonded together,matrix of components->。
Thirdly, acquiring a preset evaluation coefficient matrix。
Obtaining a preset evaluation coefficient matrix according to geographic position data and season related data obtained from the matrix data。
Wherein, geographic location data longitude and latitude: (36.27,114.54);
sunrise time: 06:17:00; sunset time: 18:39:00;
season: spring;
according to the condition information, a preset evaluation coefficient matrix is obtained from a plurality of pre-stored evaluation coefficient matrices as follows:
wherein, the mean square error matrix U and the preset evaluation coefficient matrixEach of which contains 24 elements.
And a fourth step of calculating a state of charge evaluation value.
The mean square error matrix U and a preset evaluation coefficient matrixPerforming multiplication operation to obtain a result matrix; and taking a determinant value to obtain an evaluation value e of the charging state.
Fifth, judging whether the charge state evaluation value e is greater thanMean square error standard value60% of (A), wherein the mean square error criterion value +.>0.121.
Thus, it is possible to determine that the state of charge evaluation value of the passive wireless monitoring device at 11 is smaller than the mean square error standard value60% of (C).
Therefore, the charging state of the passive wireless monitoring device can be determined not to be abnormal at 11 am through the calculation process.
The above is a method embodiment of the present application, based on the same inventive concept, and the embodiment of the present application further provides a charging state evaluation device of a passive wireless monitoring device, where an internal structure of the charging state evaluation device is shown in fig. 2.
Fig. 2 is a schematic diagram of an internal structure of a charge state evaluation device of a passive wireless monitoring device according to an embodiment of the present application. As shown in fig. 2, the apparatus includes a processor 201; and a memory 202 having executable code stored thereon that, when executed, causes the processor 201 to perform a method of evaluating the state of charge of a passive wireless monitoring device as described above.
In one embodiment of the present application, the processor 201 is configured to pre-process log data uploaded by the passive wireless monitoring device to obtain microclimate data and charging data corresponding to the passive wireless monitoring device; wherein the microclimate data comprises at least any one of the following: temperature, light radiation illuminance; the charging data includes at least any one of the following: charging current, charging voltage; the method comprises the steps of acquiring micro-meteorological data, and determining the output power of a solar panel of a passive wireless monitoring device according to the corresponding relation between the pre-stored micro-meteorological data and the output power of the solar panel of the passive wireless monitoring device; according to the charging data, the charging power of the passive wireless monitoring device is calculated; and the system is also used for determining the charge state evaluation value of the passive wireless monitoring device according to the relation between the output power and the charge power and the preset evaluation coefficient.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (5)
1. A method for evaluating a state of charge of a passive wireless monitoring device, the method comprising:
preprocessing log data uploaded by a passive wireless monitoring device, specifically, filtering and cleaning the log data, and removing abnormal log data to obtain first log data; screening the first log data content, and extracting microclimate data and charging data contained in the first log data; wherein the microclimate data includes at least any one of: temperature, light radiation illuminance; the charging data includes at least any one of the following: charging current, charging voltage;
determining the output power of the solar panel of the passive wireless monitoring device through the corresponding relation between pre-stored microclimate data and the output power of the solar panel of the passive wireless monitoring device; according to the charging data, the charging power of the passive wireless monitoring device is calculated;
according to the relation between the output power and the charging power and a preset evaluation coefficient, determining a charging state evaluation value of the passive wireless monitoring device specifically comprises the following steps:
determining output power corresponding to different moments in each hour in a first preset mode based on the microclimate data at different moments in each hour by taking the hour as a minimum unit; determining charging power corresponding to different time points in each hour in a second preset mode based on the charging data at different time points in each hour;
according to the output power and the charging power which are respectively corresponding to different moments in each hour, calculating to obtain the mean square error between the output power and the charging power which are respectively corresponding to each hour; wherein the mean square error and the preset evaluation coefficient are in a matrix form;
multiplying the mean square error matrix with a preset evaluation coefficient matrix to obtain a result matrix;
calculating determinant values corresponding to the result matrix to obtain a charging state evaluation value of the passive wireless monitoring device;
the preset evaluation coefficient matrix is a 24 x 1 matrix; wherein 24 elements are respectively in one-to-one correspondence with 24 hours;
the 1 st to 9 th and 16 th to 24 th element values in the 24 elements are rounded to zero;
the method further comprises the steps of:
screening the first log data content, and extracting geographic position data and season-related data contained in the first log data;
and acquiring a preset evaluation coefficient of the passive wireless monitoring device from an evaluation coefficient database according to the geographic position data and the season related data.
2. The method for evaluating the charge state of a passive wireless monitoring device according to claim 1, wherein the geographical position data includes the longitude and latitude of the position where the passive wireless monitoring device is located;
the season-related data mainly comprises any one or more of the following: season, sunrise time, sunset time.
3. The method for evaluating the state of charge of a passive wireless monitoring device according to claim 1, wherein after determining the state of charge evaluation value of the passive wireless monitoring device, the method further comprises:
and calculating a difference value between the charging state evaluation value and a mean square error standard value, determining that the passive wireless monitoring device is abnormal in charging under the condition that the difference value is larger than a preset threshold value, and sending charging abnormality information to the mobile terminal.
4. A method of assessing the state of charge of a passive wireless monitoring device of claim 3, further comprising:
under the condition that the passive wireless monitoring device normally operates, calculating the mean square error between the output power and the charging power which are respectively corresponding to each hour within a preset number of days;
and averaging a plurality of mean square errors to obtain the mean square error standard value.
5. A state of charge evaluation apparatus of a passive wireless monitoring device, the apparatus comprising: a processor;
and a memory having executable code stored thereon that, when executed, causes the processor to perform a method of assessing the state of charge of a passive wireless monitoring device as claimed in any one of claims 1 to 4.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008141918A (en) * | 2006-12-05 | 2008-06-19 | Nippon Telegr & Teleph Corp <Ntt> | Device, method, and program for evaluating photovoltaic power generation system |
| WO2011058806A1 (en) * | 2009-11-12 | 2011-05-19 | シャープ株式会社 | Solar cell panel and electric apparatus provided with storage cell thereof |
| CN102073791A (en) * | 2011-01-12 | 2011-05-25 | 东南大学 | Local solar energy resource abundance evaluating system for design of photovoltaic power station |
| JP2012186877A (en) * | 2011-03-03 | 2012-09-27 | Panasonic Corp | Battery state detector for photovoltaic generation battery system |
| JP2013225579A (en) * | 2012-04-20 | 2013-10-31 | Eko Instruments Trading Co Ltd | Apparatus and method for solar cell characteristic evaluation |
| CN103678872A (en) * | 2013-09-27 | 2014-03-26 | 国家电网公司 | Photovoltaic power generation system performance evaluation method and device |
| WO2016166991A1 (en) * | 2015-04-17 | 2016-10-20 | パナソニックＩｐマネジメント株式会社 | Diagnostic system for photovoltaic power generation equipment, and program |
| CN108564223A (en) * | 2018-04-23 | 2018-09-21 | 中国农业大学 | The combination evaluation method and device of photovoltaic power generation power prediction method |
| CN109284882A (en) * | 2017-07-21 | 2019-01-29 | 中国电力科学研究院 | A kind of method and system that photovoltaic module performance determines |
| CN110390481A (en) * | 2019-07-22 | 2019-10-29 | 河海大学常州校区 | A kind of horizontal plane sun scattering irradiation appraisal procedure and device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10411495B2 (en) * | 2012-06-13 | 2019-09-10 | Clear Blue Technologies Inc. | System for the monitoring and maintenance of remote autonomously powered lighting installations |
-
2020
- 2020-06-22 CN CN202010575765.3A patent/CN111929586B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008141918A (en) * | 2006-12-05 | 2008-06-19 | Nippon Telegr & Teleph Corp <Ntt> | Device, method, and program for evaluating photovoltaic power generation system |
| WO2011058806A1 (en) * | 2009-11-12 | 2011-05-19 | シャープ株式会社 | Solar cell panel and electric apparatus provided with storage cell thereof |
| CN102073791A (en) * | 2011-01-12 | 2011-05-25 | 东南大学 | Local solar energy resource abundance evaluating system for design of photovoltaic power station |
| JP2012186877A (en) * | 2011-03-03 | 2012-09-27 | Panasonic Corp | Battery state detector for photovoltaic generation battery system |
| JP2013225579A (en) * | 2012-04-20 | 2013-10-31 | Eko Instruments Trading Co Ltd | Apparatus and method for solar cell characteristic evaluation |
| CN103678872A (en) * | 2013-09-27 | 2014-03-26 | 国家电网公司 | Photovoltaic power generation system performance evaluation method and device |
| WO2016166991A1 (en) * | 2015-04-17 | 2016-10-20 | パナソニックＩｐマネジメント株式会社 | Diagnostic system for photovoltaic power generation equipment, and program |
| CN109284882A (en) * | 2017-07-21 | 2019-01-29 | 中国电力科学研究院 | A kind of method and system that photovoltaic module performance determines |
| CN108564223A (en) * | 2018-04-23 | 2018-09-21 | 中国农业大学 | The combination evaluation method and device of photovoltaic power generation power prediction method |
| CN110390481A (en) * | 2019-07-22 | 2019-10-29 | 河海大学常州校区 | A kind of horizontal plane sun scattering irradiation appraisal procedure and device |
Non-Patent Citations (1)
| Title |
|---|
| Performance evaluation of lead acid batteries for use with solar panels;V. Alminauskas;Conference Record of the Twenty Third IEEE Photovoltaic Specialists Conference - 1993 (Cat. No.93CH3283-9);1258-1263 * |
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