CN111130009B - A method for determining the operation status of visual image equipment of transmission line channels - Google Patents
A method for determining the operation status of visual image equipment of transmission line channels Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02G1/00—Methods or apparatus specially adapted for installing, maintaining, repairing or dismantling electric cables or lines
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- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
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Abstract
本发明涉及输电线路检修技术领域，具体涉及一种输电线路通道可视化图像类设备运行状态的确定方法，包括以下步骤：a、对输电线路通道可视化图像类设备的工作时间进行统计存储；b、对输电线路通道可视化图像类设备回传的每一张图像资料进行时间记录的统计存储；c、对存库的数据进行统计分析，并汇总展示；本发明能自动确定输电线路通道可视化图像类设备的工作状态，可以人为的自定义离线标准的判定，可以根据不同的设备类型进行区别统计。
The invention relates to the technical field of transmission line maintenance, and in particular relates to a method for determining the operation state of a visual image equipment of a transmission line channel, comprising the following steps: a. Statistically storing the working time of the visual image equipment of a transmission line channel; b. Statistical storage of time records is performed for each image data returned by the transmission line channel visualization image equipment; c. Statistical analysis is performed on the data in the inventory, and a summary display is performed; the invention can automatically determine the transmission line channel visualization image equipment. The working status can be determined by human-defined offline standards, and statistics can be made according to different equipment types.
Description
Technical Field
The invention relates to the technical field of power transmission line maintenance, in particular to a method for determining the running state of visual image equipment of a power transmission line channel.
Background
With the improvement of the transmission line maintenance technology, the visual remote inspection of the transmission line channel is widely applied, the current equipment for visualization of the transmission line channel is mainly divided into two types of equipment, namely video equipment and image equipment, because the power transmission line channel visualization equipment is mainly installed on an outdoor high-voltage power tower and can only transmit data back through wireless communication technologies such as 4G and the like, the video equipment is generally provided with a battery box, the video monitoring operation can be carried out for a long time without considering the power consumption problem brought by the back data of the equipment, however, the battery capacity of the equipment configuration of the image class is relatively small, the communication connection can be actively carried out only when the image data is regularly returned, which causes the power consumption caused by the communication connection to be the main power consumption, in order to cope with severe outdoor extreme environments, factors such as 4G communication flow cost are considered, and a long connection mode is not generally adopted by transmission line channel visual image equipment.
In summary, how to obtain the operating state of the high-efficiency and reliable transmission line channel visual image equipment, so that the obtained operating state matches with the observation state of the transmission line maintainer on the actual returned data of the equipment, the equipment in an abnormal state can be maintained in time, and the problem that the site hidden danger cannot be found in time due to equipment failure is avoided, which is one of the problems to be solved by the technical personnel in the field at present.
Disclosure of Invention
In order to solve the deficiencies in the above technical problems, the present invention aims to: the method for determining the running state of the visual image equipment of the power transmission line channel solves the problem of calculating the running state of the equipment in real time by counting the image data returned by the equipment, analyzes the running time of the equipment and the change of the running state, and brings convenience for maintenance personnel of the power transmission line to maintain the image equipment.
The technical scheme adopted by the invention for solving the technical problem is as follows:
the method for determining the running state of the visual image equipment of the power transmission line channel comprises the following steps:
a. counting and storing the working time of the visual image equipment of the power transmission line channel;
b. carrying out statistical storage of time records on each image data returned by the visual image equipment of the power transmission line channel;
c. and carrying out statistical analysis on the data in the database, and summarizing and displaying.
2. The power transmission line scene semantic understanding method based on the deep learning technology of claim 1, wherein the step a comprises the following steps:
a 1: analyzing encrypted message information returned by the transmission line channel visual image equipment, extracting working time deviceWorkBeginTime (time: minutes: second/hh: mm: ss) of the transmission line channel visual image equipment from the encrypted message information, abbreviated as DWBT, ending working time deviceWorkEndTime (time: minutes: second/hh: mm: ss) of the transmission line channel visual image equipment, abbreviated as DWET, and photographing interval capturePod (unit/minute) of the transmission line channel visual image equipment, abbreviated as CP;
a 2: based on each morning (00: 00:00) of the day, DWBT and DWET were adjusted to 00: time 00:00 is converted to positive integers btm and etm in minutes;
a 3: and (3) introducing a self-defined offline time t, and taking minutes as a unit, namely determining the offline state according to the number of minutes of the equipment without uploading image data.
3. The method for determining the operation state of a power transmission line channel visualization image-like device according to claim 1, wherein step b comprises the steps of:
b 1: defining the image capture time picturescapureDT (year-month-day: minute: second/yy-MM-dd h: MM: ss) of the visual image equipment of the power transmission line channel by taking the name of image data returned by the visual image equipment of the power transmission line channel as a reference, abbreviated as PCD, receiving the image storage time pictureAvedT (year-month-day: minute: second/yy-MM-dd h: MM: ss) of the visual image equipment of the power transmission line channel defined by taking the time for finishing storing the image data as the reference by a background, abbreviated as PSD, and identifying whether the image data is returned data of the visual image equipment of the power transmission line channel or a mark bit cameraFlag of returned data of the visual image equipment of the power transmission line channel used in the daytime, abbreviated as CF;
b 2: comparing the difference value of the PCD and the PSD, setting a data return abnormal interval P in a self-defined manner, determining that network delay exists when the visual image equipment of the power transmission line channel returns image data when the P is larger than the difference value of the PCD and the PSD, representing a flag isDelay, and analyzing the reason of equipment off-line;
b 3: defining Off-Line-Time, called OLT for short, which is the Time before t work minutes calculated according to the user-defined Off-Line Time t.
Compared with the prior art, the invention has the following beneficial effects:
(1) the invention can automatically determine the working state of the visual image equipment of the transmission line channel, can artificially define the judgment of the off-line standard, and can carry out the distinguishing statistics according to different equipment types.
(2) The invention eliminates the device offline condition caused by the loss of wireless network signals.
(3) The invention adopts the dichotomy algorithm and the Hash diagram mode for storage, greatly improves the statistical efficiency, and can support the statistical analysis work with the minimum working interval of 5 minutes and 2 tens of thousands of devices.
Drawings
Fig. 1 is a schematic flow chart of a model for calculating an offline reference time in the present invention.
Detailed Description
The following further describes embodiments of the present invention:
example 1
As shown in fig. 1, the method for determining the operation state of a power transmission line channel visualization image device according to the present invention includes the following steps:
1. obtaining the self-defined offline duration t in the current time now of the system, a3, and changing DWBT and DWET to 00 in a 2: time 00:00 is converted into positive integers btm and etm in minutes, and the four values are passed as parameters to b3 as a callatestarttime ()
2. The main logic of the callatestarttime method comprises the following steps:
the current time now is converted into the number of minutes to the morning now _ Min, the required working time (unit: minute) work _ time in one day is calculated according to the difference between btm and etm, the total number of minutes day _ Min is 24 x 60 minutes, and the number of days of increase is required to be calculated, i.e. t/work _ time. The morning minutes time is defined as 0 x 60 minutes.
3. A temporary variable Temp is defined for storing the time value (the difference between the current time minus the working time and the starting working time) to be calculated, i.e., Temp — now _ Min- (t% work _ time) -btm.
Note: % represents the remainder operation
4. Comparing which time period in the day the current time is in;
a. if after the end of the working time of the day, now Min etm, now time is the current time minus the remainder of the end working time and t and work time, now the calculated time res _ DT should be:
times＝now_Min-(etm-(t％work_time))；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
thus, when t is larger than the working time, the working time point of the previous day is located.
b. If between the beginning working time and the ending time of the working time of the day, that is btm < ═ now _ Min < ═ etm, then the time at this time needs to judge the size of temp:
b1, if temp is positive, that is, the absolute value of the difference between the starting working time and the ending working time is less than the self-defined off-line time t, then time is the remainder of t and work _ time, and the calculated time res _ DT at this time should be:
times＝t％work_time；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
b2, if temp is negative, that is, the absolute value of the difference between the starting working time and the ending working time is greater than the off-line time t set by the user, then time at this time is the difference between the current time now _ Min and the non-working time of the previous day plus the difference between the working times, and the calculated time res _ DT at this time should be:
times＝now_Min-(etm-temp)；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
c. if before the start working time of the day, i.e. now _ Min < ═ btm, then time at this time is the current time minus the difference between the working time of the previous day and the non-working time and the remainder of t and work _ time, the time res _ DT calculated at this time should be:
times＝now_Min+day_Min-etm-(t％work_time)；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
thus, when t is larger than the working time, the working time point of the previous day is located.
5. After the offline reference time OLT of the image equipment is calculated, the PCD or PSD stored in the database of the equipment is only required to be sequenced, the largest piece of data is taken out and put into a cache, namely the latest piece of data of each equipment is stored in the cache, and then the PCD or PSD is used for comparing with the OLT, if the OLT is larger, the equipment is in an offline state, otherwise, if the OLT is smaller, the equipment is in an online state.
6. According to the calculation result, the states of all the devices are distinguished and stored in a library by using a zone bit, then the difference value of btm and etm is divided by CP, the number of the pictures which should be uploaded in the working time of the day can be calculated, the number of the pictures which are actually uploaded by the devices can be calculated according to the number of records in the database, therefore, the data is summarized and analyzed, the effective access rate statistical result of the devices is obtained, and the effective access rate statistics can be used for counting how many devices belong to the devices which are well accessed according to the mode of considering the set percentage. That is, the effective access rate is set to 95%, which means that if 100 pictures are uploaded every day by each device, the actual number of uploads exceeds 95 to be determined that the device is sound.
Example 2
On the basis of example 1, the following elucidation of the process is carried out in the form of simulation data:
assuming that the current device start operation time is 08:00:00 and the end operation time is 18:00:00, then the corresponding btm is 8 × 60-480, and etm is 18 × 60-1080, the total operation duration of the whole day is 24 × 60-1440, the current date is 10.1 days, and assuming that the offline duration is determined to be 12 hours (12 × 60 minutes), i.e., t > etm-btm, the following results can be obtained by calculation:
when the present time now 0< now < btm, now suppose 05:00
According to the description of the fourth item c, there are:
times＝now_Min+day_Min-etm-(t％work_time)；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
times＝5*60+1440-1080-(720％600)＝300+1440-1080-120＝540
res_DT＝300.addSecs(-60*(540+1440*1))
i.e., 540+1440 minutes ahead of the current time 300, i.e., 16:00 of the previous day
Example 3
On the basis of example 1, the following elucidation of the process is carried out in the form of simulation data:
when the present time now is after btm and before etm, i.e. btm < now < etm, assuming now 15:00:00 as described in the fourth b2, then:
temp＝now_Min-(t％work_time)-begin_Min if(temp>＝0)
{
times＝t％work_time；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
}else{
times＝day_Min-(end_Min-temp)；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
}
temp＝15*60-(12*60％(1080-480))-480＝300
times＝900-1080+300＝120
res_DT＝900.addSecs(-60*(120+1440*1))
i.e., 120+1440 minutes ahead of the current time 900, i.e., 13:00 of the previous day
According to the description of the fourth b1, there are: the modification t is 8 hours, then:
temp＝now_Min-(t％work_time)-begin_Min if(temp>＝0)
{
times＝t％work_time；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
}else{
times＝day_Min-(end_Min-temp)；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
}
temp＝15*60-(8*60％(1080-480))-480＝-60
times＝-60
res_DT＝900.addSecs(-60*(-60+1440*1))
i.e., the current time 900 is moved forward by-60 +1440 minutes, i.e., 17:00 of the previous day
Example 4
On the basis of example 1, the following elucidation of the process is carried out in the form of simulation data:
when the present time now is after etm, before etm, i.e. etm < now <24:00:00, it is assumed to now be 20:00:00
According to the description of the fourth b2, there are:
according to the description of the fourth a, there are:
times＝now_Min-(etm-(t％work_time))；
res_DT＝res_DT.addSecs(-60*(times+day_Min*dates))；
times＝20*60-(18*60-(12*60％600))＝240
res_DT＝1200.addSecs(-60*(240+1440*1))；
i.e., 240+1440 minutes ahead of the current time 1200, i.e., 16:00:00 of the previous day.
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