CN114513707A - Intelligent bus data acquisition method - Google Patents
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Abstract
The invention relates to an intelligent bus data acquisition method, which calculates the data variation of each instrument, weights the data variation with the time overhead of instrument acquisition, dynamically adjusts the priority of the bus equipment for acquiring instrument data, ensures the efficiency and the real-time of instrument acquisition through a priority queue, and ensures that each instrument can take turns to sampling. Compared with the prior art, the method and the device ensure the real-time performance of the acquired data, solve the problems of large quantity of repeated acquired data and untimely response of data change under a bus polling mechanism, effectively improve the efficiency of data acquisition, are favorable for further promoting data cross-professional fusion, information deep sharing and accurate user service, and have great significance in the field of power internet of things.
Description
Technical Field
The invention relates to the technical field of industrial bus meter reading, in particular to an intelligent bus data acquisition method.
Background
The bus equipment data acquisition is widely applied to the fields of power internet of things and the like and is the basis of point parameter analysis and statistics work. With the continuous development of the scale of the power internet of things and the accumulation of the collected data, the data processing capacity of a traditional data collection system is greatly challenged, so that the improvement of the collection efficiency of bus data is beneficial to further promoting the cross-professional fusion of data, the deep sharing of information and the accurate user service.
The physical layer of the traditional industrial acquisition bus is an RS485 bus, the RS485 bus has strong anti-interference capability, but the communication speed is low, the common baud rate is 9600bps, the speed and the communication distance have direct relation, and when the communication distance reaches more than hundreds of meters, the reliable communication speed is less than 1200 bps. The traditional gateway acquisition algorithm is a polling algorithm, equipment acquires each instrument in each round, the scheduling is simple, the actual carrying condition of the equipment is not needed to be concerned, but the bus polling time is prolonged if the equipment is offline or the response time is too long, the data variation of partial instruments on the bus in a period of time is very small, and in practical application, the real-time acquisition of data inevitably causes resource waste.
Therefore, how to improve the efficient data acquisition of the low-speed bus device becomes a technical problem to be solved.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an intelligent bus data acquisition method.
The purpose of the invention can be realized by the following technical scheme:
according to one aspect of the invention, the method calculates the data variation of each meter, weights the data variation with the time overhead of meter acquisition, dynamically adjusts the priority of the data acquired by the bus equipment, ensures the efficiency and real-time of meter acquisition through a priority queue, and ensures that each meter can take turns to sampling.
As a preferred technical scheme, the method specifically comprises the following steps:
step 1, inserting all bus devices into a task queue according to the priority P being 0;
Step 3, the bus equipment reads the data of all the meters again, and for the meter 1, the data is marked as T1(2) At this time, the data reading is recorded as D1(T1(2) For the instrument 2, this time denoted T2(2) At this time, the data reading is recorded as D2(T2(2) … …, for meter m, now denoted Tm(2) At this time, the data reading is recorded as Dm(Tm(2))；
And 4, taking out a task from the head of the queue, recording the priority of the task as P, subtracting P from the priority of other tasks in the task queue to achieve the aim of updating the priority of the queue, recording the number of the acquisition instrument of the task as m, and recording the acquisition time of the task as Tm(n) collecting data Dm(Tm(n)), wherein n is a time point greater than 2, and the response time of the meter is recorded as Rm；
Step 5, setting the maximum priority weighted value of the primary change rate of the task to be MAXdx；
Step 6, calculating T according to the following formulam(n) one time rate of change priority weight Pdx(Tm(n))：
Wherein k isdxA first-order rate of change inverse proportional priority weighting factor;
step 7, if Pdx(Tm(n))＞MAXdxIf the task is a task, updating the maximum priority weighted value of the change rate of the current task to be:
MAXdx＝Pdx(Tm(n))；
step 8, setting the maximum priority weighted value of the secondary change rate of the task to be MAXddx；
Step 9, calculating T according to the following formulam(n) secondary rate of change priority weighting P at time instantddx(Tm(n))：
Wherein k isddxWeighting coefficients for the second-order rate of change inverse proportional priorities;
step 10, if Pddx(Tm(n))＞MAXddxIf so, updating the maximum priority weighted value of the secondary change rate of the task to be:
MAXddx＝Pddx(Tm(n))；
step 11, setting the maximum priority weighted value of the response time of the meter to MAXr；
Step 12, calculating the response time length weight P of the meter m according to the following formular(m)：
Pr(m)=Kr*Rm，
Wherein, KrA priority weighting coefficient for the standby response time length;
step 13, if Pr(m)>MAXrIf so, updating the maximum priority weighted value of the response time of the task to be:
MAXr=Pr(m)；
step 14, calculating the priority weight P of the task P according to the following formulam：
Pm＝Pdx(Tm(n))+Pddx(Tm(n))+Pddx(Tm(n))+Pr(m)；
Step 15, inserting the tasks into the task queue according to the priority weight, and ensuring that the priorities of the tasks in the task queue are arranged from small to large;
and step 16, repeating the steps 4 to 15 until all tasks are completed.
Preferably, the MAX isdxThe setting method specifically comprises the following steps:
5A) setting the ratio of the first time change rate priority to the total priority to be Adx，0<Adx<1；
5B) Setting MAXdx＝Adx*a。
As a preferred technical scheme, the k isdxThe setting method specifically comprises the following steps:
6A) estimating the minimum value f of normal change frequency of measured datamin；
6B) Setting kdx＝fmin*a*Adx。
Preferably, the MAX isddxThe setting method specifically comprises the following steps:
8A) setting the ratio of the first time change rate priority to the total priority to be Addx，0<Addx<1；
8B) Setting MAXddx＝Addx*a。
As a preferred technical scheme, the k isddxThe setting method specifically comprises the following steps:
9A) estimating the minimum value V of the normal change speed of the measured datamin；
9B) Setting kddx＝Vmin*a*Addx。
Preferably, the MAX isrThe setting method specifically comprises the following steps:
11A) setting the ratio of the first time change rate priority to the total priority to be Ar，0<Ar<1；
11B) Setting MAXr＝Ar*a。
As a preferred technical scheme, the k isrThe setting method specifically comprises the following steps:
12A) predicting the maximum response time t of the measured instrumentmax；
12B) Setting up
As a preferred technical scheme, a is any value, and for any value a, a priority normalization interval (0, a) is determined first.
As a preferable technical proposal, A isdx、AddxAnd ArThe following formula is satisfied:
Adx+Addx+Ar＝1。
compared with the prior art, the invention has the following advantages:
according to the invention, the priority of the bus equipment for collecting the instrument data is dynamically adjusted by performing weighted analysis on the variable quantity of the instrument data and the time overhead of the collected data, the real-time property of the collected data is ensured, the problems of large quantity of repeated collected data and untimely response of data change under a bus polling mechanism are solved, the efficiency of data collection is effectively improved, the data cross-professional fusion, the information deep sharing and the accurate user service are further promoted, and the method has great significance in the field of the power Internet of things.
Drawings
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is an overall flow chart of the update queue priority of the present invention;
FIG. 3 is a flow chart of calculating task priority according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
As shown in fig. 1, the system structure of the present invention is: the physical layer of the system bus adopts an RS485 bus; the protocol adopts a ModBus protocol and is used for collecting instrument data; adopt a master station equipment on the 485 bus, record 485 master stations, 4 slave station equipment, record 485 slave station 1, 485 slave station 2, 485 slave station 3, 485 slave station 4. The algorithm is deployed on 485 master station equipment and used for collecting data of the 485 slave station equipment.
The 485 master station dynamically adjusts the ModBus acquisition message sending time of each 485 slave station according to the algorithm, and dynamically adjusts the next acquisition message sending time again according to the algorithm according to the feedback data and the response time of the 485 slave stations.
As shown in fig. 2, the overall workflow of the present invention is described in detail. The invention dynamically adjusts the priority of the bus equipment for collecting the instrument data by performing weighted analysis on the variable quantity of the instrument data and the time overhead of collecting the data, realizes the arrangement of tasks in a queue from small to large according to the priority, and achieves the purpose of improving the efficiency of data collection.
The whole implementation process of the invention is as follows:
(2.1) inserting all bus devices into the task queue with priority P ═ 0;
(2.2) the bus device reads the data of all meters, and for the meter 1, it is marked T1(1) At this time, the data reading is recorded as D1(T1(1) For the instrument 2, this time denoted T2(1n, where the data reads are denoted D2(T2(1) … …, for meter m, now denoted Tm(1) At this time, the data reading is recorded as Dm(Tm(1))；
(2.3) the bus device again reads the data of all meters, for meter 1, now denoted T1(2) At this time, the data reading is recorded as D1(T1(2) For the instrument 2, this time denoted T2(2) At this time, the data reading is recorded as D2(T2(2) … …, for meter m, now denoted Tm(2) At this time, the data reading is recorded as Dm(Tm(2))；
(2.4) updating queue priority:
(2.4.1) judging whether the number of tasks with the priorities which are not calculated is greater than 0, if so, circularly and iteratively calculating the priority weight of each task until all tasks are finished;
(2.4.2) respectively calculating the task at Tm(n) one time rate of change priority weight Pdx(Tm(n)), secondary rate of change priority weight Pddx(Tm(n)) and response time length weight P of meter mr(m)；
(2.4.3) calculating the priority weight of the task:
Pm＝Pdx(Tm(n))+Pddx(Tm(n))+Pddx(Tm(n))+Pr(m)；
(2.5) inserting the tasks into the task queue according to the priority weight, and ensuring that the priorities of the tasks in the task queue are arranged from small to large;
in updating the queue priority as described in (2.4), the more detailed steps are shown in fig. 3, and the process of calculating the priority of a task is as follows:
(3.1) taking a task from the head of the queue, and recording the priority of the task as P;
(3.2) subtracting P from the priority of other tasks in the task queue to achieve the purpose of updating the queue priority;
(3.3) recording some important parameters of the task: recording the number of an acquisition instrument of the task as m, and recording the acquisition time of the task as Tm(nn, data collected are Dm(Tm(n)) (n is a time point greater than 2), and the response time of the meter is recorded as Rm；
(3.4) setting a series of important parameters of the task:
(3.4.1) randomly taking a value a, and firstly determining a normalization interval (0, a);
(3.4.2) setting the ratio of the first order rate of change priority to the total priority to Adx(0<Adx<1) To obtain the maximum and excellent one-time change rate of the taskThe priority weighting value is MAXdx＝Adx*a；
(3.4.3) estimating the minimum value f of the normal change frequency of the measured dataminSetting an inverse proportional priority weighting coefficient k of the first order rate of changedx＝fmin*a*Adx；
(3.4.4) setting the ratio of the first order rate of change priority to the total priority to Addx(0<Addx<1) Obtaining the maximum priority weighted value of the secondary change rate of the task as MAXddx＝Addx*a；
(3.4.5) estimating the minimum value V of the normal change speed of the measured dataminSetting a quadratic rate of change inverse proportional priority weighting factor kddx＝Vmin*a*Addx；
(3.4.6) setting the ratio of the first order rate of change priority to the total priority to Ar(0<Ar<1) Calculating the maximum priority weighted value MAX of the response time length of the meterr＝Ar*a；
(3.4.7) estimating the maximum response time t of the measured instrumentmaxSetting a priority weighting coefficient of the standby response time duration
(3.4.8) wherein Adx+Addx+Ar＝1；
(3.5) determining whether to update MAXdx：
(3.5.1) calculating T according to the following formulam(n) one time rate of change priority weight Pdx(Tm(n))：
(3.5.2) if Pdx(Tm(n))＞MAXdxIf the task is a task, updating the maximum priority weighted value of the change rate of the current task to be:
MAXdx＝Pdx(Tm(n))；
(3.6) judging whether to update MAXddx：
(3.6.1) calculating T according to the following formulam(n) secondary rate of change priority weighting P at time instantddx(Tm(n))：
(3.6.2) if Pddx(Tm(n))＞MAXddxIf so, updating the maximum priority weighted value of the secondary change rate of the task to be:
MAXddx＝Pddx(Tm(n))；
(3.7) judging whether to update MAXr：
(3.7.1) calculating the response time length weight P of the meter m according to the following formular(m)：
Pr(m)＝Kr*Rm；
(3.7.2) if Pr(m)＞MAXrIf the task is a task with a priority value equal to the maximum priority weighted value of the response time length of the task:
MAXr＝Pr(m)；
(3.8) calculating the priority weight of the task P according to the following formula:
Pm＝Pdx(Tm(n))+Pddx(Tm(n))+Pddx(Tm(n))+Pr(m)；
therefore, the invention improves the problem of low communication efficiency of the low-speed bus in the industrial bus meter reading. According to the invention, through carrying out weighted analysis on the variable quantity of the meter data and the time overhead of the collected data, the priority of the bus equipment for collecting the meter data is dynamically adjusted, the real-time property of the collected data is ensured, the problems of large quantity of repeated data collected under a bus polling mechanism and untimely response of data change are solved, the efficiency of data collection is effectively improved, the data cross-professional fusion, the information deep sharing and the accurate user service are further promoted, and the method has great significance in the field of the power Internet of things.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An intelligent bus data acquisition method is characterized in that the method calculates the data variation of each meter, weights the data variation with the time overhead of meter acquisition, dynamically adjusts the priority of the bus equipment for acquiring the meter data, ensures the efficiency and the real-time of meter acquisition through a priority queue, and ensures that each meter can take turns to sampling.
2. The intelligent bus data acquisition method according to claim 1, characterized in that the method specifically comprises the steps of:
step 1, inserting all bus devices into a task queue according to the priority P being 0;
step 2, the bus equipment reads the data of all the meters, and for the meter 1, the data is marked as T1(1) At this time, the data reading is recorded as D1(T1(1) For the instrument 2, this time denoted T2(1) At this time, the data reading is recorded as D2(T2(1) Is., for meter m, now marked as Tm(1) At this time, the data reading is recorded as Dm(Tm(1))；
Step 3, the bus equipment reads the data of all the meters again, and for the meter 1, the data is marked as T1(2) At this time, the data reading is recorded as D1(T1(2) For the instrument 2, this time denoted T2(2) At this time, the data reading is recorded as D2(T2(2) Is., for meter m, now marked as Tm(2) At this time, the data reading is recorded as Dm(Tm(2))；
Step 4, from the head of the queueTaking out a task, recording the priority of the task as P, subtracting P from the priority of other tasks in the task queue to achieve the purpose of updating the queue priority, recording the number of an acquisition instrument of the task as m, and recording the acquisition time of the task as Tm(n) collecting data Dm(Tm(n)), wherein n is a time point greater than 2, and the response time of the meter is recorded as Rm；
Step 5, setting the maximum priority weighted value of the primary change rate of the task to be MAXdx；
Step 6, calculating T according to the following formulam(n) one time rate of change priority weighting value Pdx(Tm(n))：
Wherein k isdxA first-order rate of change inverse proportional priority weighting factor;
step 7, if Pdx(Tm(n))＞MAXdxIf the task is a task, updating the maximum priority weighted value of the change rate of the current task to be:
MAXdx＝Pdx(Tm(n))；
step 8, setting the maximum priority weighted value of the secondary change rate of the task to be MAXddx；
Step 9, calculating T according to the following formulam(n) quadratic rate of change priority weighting P at timeddx(Tm(n))：
Wherein k isddxWeighting coefficients for the quadratic change rate inverse proportional priorities;
step 10, if Pddx(Tm(n))＞MAXddxIf so, updating the maximum priority weighted value of the secondary change rate of the task to be:
MAXddx＝Pddx(Tm(n))；
step 11, setting the maximum priority weighted value of the response time of the meter to MAXr；
Step 12, calculating the response time length weight P of the meter m according to the following formular(m)：
Pr(m)＝Kr*Rm，
Wherein, KrA priority weighting coefficient for the standby response time length;
step 13, if Pr(m)＞MAXrIf the task is a task with a priority value equal to the maximum priority weighted value of the response time length of the task:
MAXr＝Pr(m)；
step 14, calculating the priority weight P of the task P according to the following formulam：
Pm＝Pdx(Tm(n))+Pddx(Tm(n))+Pddx(Tm(n))+Pr(m)；
Step 15, inserting the tasks into the task queue according to the priority weight, and ensuring that the priorities of the tasks in the task queue are arranged from small to large;
and step 16, repeating the steps 4 to 15 until all tasks are completed.
3. An intelligent bus data acquisition method as claimed in claim 2, wherein the MAX is a maximum valuedxThe setting method specifically comprises the following steps:
5A) setting the proportion of the primary rate of change priority to the total priority as Adx，0＜Adx＜1；
5B) Setting MAXdx＝Adx*a。
4. An intelligent bus data acquisition method as claimed in claim 2, wherein k isdxThe setting method specifically comprises the following steps:
6A) estimating the minimum value f of normal change frequency of measured datamin；
6B) Setting kdx＝fmin*a*Adx。
5. An intelligent bus data acquisition method as claimed in claim 2, wherein the MAX is a maximum valueddxThe setting method specifically comprises the following steps:
8A) setting the ratio of the first time change rate priority to the total priority to be Addx，0＜Addx＜1；
8B) Setting MAXddx＝Addx*a。
6. An intelligent bus data acquisition method as claimed in claim 2, wherein k isddxThe setting method specifically comprises the following steps:
9A) estimating the minimum value V of the normal change speed of the measured datamin；
9B) Setting kddx＝Vmin*a*Addx。
7. An intelligent bus data acquisition method as claimed in claim 2, wherein the MAX is a maximum valuerThe setting method specifically comprises the following steps:
11A) setting the ratio of the first time change rate priority to the total priority to be Ar，0＜Ar＜1；
11B) Setting MAXr＝Ar*a。
8. An intelligent bus data acquisition method as claimed in claim 2, wherein k isrThe setting method specifically comprises the following steps:
12A) predicting the maximum response time t of the measured instrumentmax；
12B) Setting up
9. An intelligent bus data collection method according to any one of claims 3 to 8, wherein a is any value, and for any value a, a priority normalization interval (0, a) is determined first.
10. An intelligent bus data acquisition method as claimed in claim 2, wherein A isdx、AddxAnd ArThe following formula is satisfied:
Adx+Addx+Ar＝1。
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