CN110647115A - Data acquisition method based on industrial internet operating system - Google Patents
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- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
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Abstract
The invention aims to provide a data acquisition method system based on an industrial internet operating system, which is applied to a business layer, reasonably acquires data in a communication network under limited bandwidth resources as far as possible, utilizes the bandwidth of a transmission network as far as possible, and improves the processing throughput of the system. In order to achieve the purpose, the technical scheme adopted by the invention is a data acquisition method based on an industrial internet operating system, which comprises the following steps: step 1, data acquisition and identification; step 2, defining adjustment parameters of data acquisition; and step 3: and detecting the real-time state of the communication network, and judging whether to adopt elastic control processing according to the network condition. Due to the adoption of the technical scheme, the invention can be matched with the service more closely based on the elastic data acquisition of the service layer, and has no special requirements on communication networks and communication equipment. The strategy does not need to be readjusted even if the application scene changes.
Description
Technical Field
The invention relates to the field of industrial control, Internet of things and industrial internet operating systems, in particular to a data acquisition method system based on an industrial internet operating system.
Background
In the field of industrial control and Internet of things, a large number of monitoring points which need to be monitored exist, and detected real-time data need to be timely and completely transmitted to a data processing server. When a network between a data acquisition end and a service processing server breaks down, real-time data needs to be stored on site, bandwidth resources of a communication network between the data acquisition end and the data processing server are limited, and the data uploading rate needs to be adjusted in real time according to the bandwidth, so that the real-time data and historical data can be transmitted timely and effectively.
For example, in an invention patent with a patent number CN103297191B in the prior art, a data acquisition method and a data acquisition system for automatically adjusting a wireless transmission rate are disclosed, wherein the method includes: acquiring the current bandwidth of a wireless transmission channel for transmitting the acquired data; acquiring the maximum acquisition rate of each data acquisition unit according to the current bandwidth of the wireless transmission channel and the proportion of the bandwidth respectively configured for one or more data acquisition units for data acquisition; and adjusting the transmission of the acquired data of each data acquisition device through the wireless transmission channel according to the maximum acquisition rate of each data acquisition device. The invention determines the current channel bandwidth by monitoring the signal-to-noise ratio in the wireless transmission channel, thereby adjusting the acquisition rate of the data acquisition unit to adapt to the current channel quality and bandwidth according to the current channel bandwidth.
However, only flow rate control of wireless network transmissions is described in the prior art, which is characterized by QOS-based rate control at the network layer. It is inconvenient to perform differential processing according to the service. This results in different processing schemes being designed for different application scenarios and control schemes being redesigned in case of environmental changes.
Disclosure of Invention
The invention aims to provide a data acquisition method system based on an industrial internet operating system, which is applied to a business layer, reasonably acquires data in a communication network under limited bandwidth resources as far as possible, utilizes the bandwidth of a transmission network as far as possible, and improves the processing throughput of the system. Meanwhile, various service data can be transmitted simultaneously, and the rate control can be always carried out according to preset conditions without exceeding, so that the stability and reliability of the system are ensured.
In order to achieve the purpose, the technical scheme adopted by the invention is a data acquisition method based on an industrial internet operating system, which comprises the following steps:
step 1, data acquisition and identification: identifying the grade of the data type in the communication network in advance, and sequencing according to the grade;
step 2, defining adjustment parameters of data acquisition: under the condition of the same bandwidth, the acquisition end with few data points properly reduces the transmission rate to ensure that the terminal with large data volume obtains more transmission bandwidth;
and step 3: detecting the real-time state of the communication network, and judging whether to adopt elastic control processing according to the network condition;
the elasticity control process includes:
1. controlling parameter input, and identifying factors influencing communication transmission, such as a data grade S, a data load D, a network state ST, a real-time state T of an acquisition end and a bandwidth set value SV;
2. according to a data model of an acquired object, predicting and analyzing data trend, and then compressing actually acquired data values according to a prediction analysis result M so as to reduce the data volume to be transmitted;
3. and calculating a data sending rate u, and carrying out data sending execution according to the adjusting rate:
k is the number of rate adjustments, u (k) is the sending rate, e (k) is the error between the input T and the set point (SV), Kp is the proportionality coefficient equal to S x D/ST x M, Kd is the differential time constant, Ki is the integral time constant;
4. receiving data sending feedback, updating the real-time state T, and re-executing control parameter input until the real-time state T is in a stable state;
5. and updating the data prediction model, optimizing the data trend prediction effect, performing regression verification on the model according to the later acquisition process, and further improving the prediction effect.
Preferably, when the environment changes or the adjusted parameter does not meet the expectation, the elasticity control process further includes:
6. and (3) optimizing: in a steady-state network environment, the adjustment effect is expected, after real-time data are collected, initialization is carried out according to the identified parameters, the initial control rate is calculated, the data transmission end carries out data transmission according to the control rate, and meanwhile, the real-time network state and the real-time state of the data collection end are fed back to the control algorithm.
Preferably, the data types are classified uniformly from high to low, and are marked sequentially, and the data with high grade has high priority processing weight in the acquisition and transmission process. The design can guarantee the transmission rate of main data during multi-task multiplexing.
Preferably, the determining of the status of the elastic control process includes: other types of data transmission states are retrieved in the communication network, the transmission rate is adjusted in real time according to the real-time state of the communication network, and when the communication network is busy, the rate is reduced, so that the impact on the communication network is reduced.
Preferably, the determining of the status of the elastic control process includes: the current state of the data acquisition end is judged to influence the data acquisition and transmission process, and the acquisition control algorithm also needs to be adjusted according to the current state, so that the transmission rate is increased or reduced.
Preferably, the determining of the status of the elastic control process includes: under the condition of communication network sharing, a maximum bandwidth occupation value is actively set, so that under the condition of combining various control parameters, the maximum bandwidth occupation value is adjusted after the maximum bandwidth occupation value is reached.
Preferably, a plurality of control parameters simultaneously act on the determination of the elasticity control process. The method can be used for carrying out data acquisition and control on a plurality of parameters, and other parameters except data grade, data load, network load and the current state of the system can influence the accuracy of the elastic control. The elasticity control process is thus automatically activated when an adjustment of one or more parameters occurs. When a plurality of parameters are commonly applied to the elasticity control process, the elasticity process accuracy is higher.
Compared with the prior art, the invention firstly realizes the application on the service layer. And through flexible control, not only the data transmission is transmitted at a smooth rate, but also the communication data transmission is performed according to the grade of the service data under the expectation of set conditions as far as possible in order to realize the optimization of the use of the communication network in the system under the condition of integrating various parameters. Relative to Qos rate control, the invention is based on elastic data acquisition of a service layer, can be matched with services more tightly, and has no special requirements on communication networks and communication equipment. The strategy does not need to be readjusted even if the application scene changes; 4. and in the data acquisition process, data trend prediction is carried out according to the model of the acquired object, and the data acquisition process is optimized and adjusted according to the prediction result.
Drawings
Fig. 1 is a schematic diagram of an elastic control flow of a data acquisition method based on an industrial internet operating system according to the present invention.
Fig. 2 is a schematic diagram of data acquired by the data acquisition method based on the industrial internet operating system, wherein marks are firstly measured values and secondly preset values.
Detailed Description
The ideal data acquisition process needs to guarantee the following points: 1. high priority data real-time: the data with the highest priority in the collected data can be uploaded to the server in time. 2: integrity: all the acquired data are required to be completely uploaded to the server, and the data received by the final server end are not lost due to the network, the server and the like. 3: real-time prioritization: when real-time data and historical data need to be transmitted simultaneously, the real-time data is preferentially ensured, and the influence of the historical data transmission on the real-time performance and the integrity of the real-time data transmission is avoided. 4: elasticity: and adjusting the data transmission rate according to the actual condition of data transmission, and adjusting the transmission rate in due time when the network state is not good so as to avoid further network congestion.
In the data acquisition method based on the industrial internet operating system, the grade of the data type in the communication network is identified in advance for data acquisition, and the data acquisition is performed with uniform grade from high grade to low grade (service, marked as S1, S2.), and the data with high grade needs to have high priority processing weight in the acquisition and transmission process.
Defining an adjustment parameter (labeled as D) for data acquisition, and reducing the transmission rate by a collection end with a small data point in a proper amount under the condition of the same bandwidth, so as to ensure that a terminal with a large data volume can obtain more transmission bandwidths.
The real-time state of the communication network is detected, in most cases, other types of data transmission may exist in the communication network, so that the transmission rate needs to be adjusted in real time according to the real-time state (labeled as T) of the communication network, and when the communication network is busy, the rate is reduced appropriately to reduce the impact on the communication network and avoid worsening the communication condition of the network.
And predicting the data trend, namely predicting the data change trend of the acquired object by combining with the data model of the acquired object so as to perform necessary data compression processing to reduce the actual data volume to be transmitted.
The current state (Status, marked as ST) of the data acquisition end may affect the data acquisition and transmission process, and the acquisition control algorithm also needs to be adjusted according to the current state to increase or decrease the transmission rate.
Under the condition of communication network sharing, in order to avoid a certain communication application from occupying a large amount of network bandwidth, a maximum bandwidth occupation value (SV) can be actively set, so that under the condition of combining various control parameters, the bandwidth is prevented from being maliciously occupied by the certain communication application to influence other systems. Other factors that may contribute to the data communication transmission process may be incorporated into the flexible control process.
As shown in fig. 1, the rate elasticity implementation step:
1. controlling parameter input, and identifying factors influencing communication transmission, such as a data grade S, a data load D, a network state ST, a real-time state T of an acquisition end and a bandwidth set value SV;
2. according to a data model of an acquired object, predicting and analyzing data trend, and then compressing actually acquired data values according to a prediction analysis result M so as to reduce the data volume to be transmitted;
3. and calculating a data sending rate u, and carrying out data sending execution according to the adjusting rate:
k is the number of rate adjustments, u (k) is the sending rate, e (k) is the error between the input T and the set point (SV), Kp is the proportionality coefficient equal to S x D/ST x M, Kd is the differential time constant, Ki is the integral time constant;
4. receiving data sending feedback, updating the real-time state T, and re-executing control parameter input until the real-time state T is in a stable state;
5. and updating the data prediction model, optimizing the data trend prediction effect, performing regression verification on the model according to the later acquisition process, and further improving the prediction effect.
When the environment changes or the adjusted parameters do not reach the expected conditions, the elasticity control processing further comprises 6, tuning: in a steady-state network environment, the adjustment effect is expected, after real-time data are collected, initialization is carried out according to the identified parameters, the initial control rate is calculated, the data transmission end carries out data transmission according to the control rate, and meanwhile, the real-time network state and the real-time state of the data collection end are fed back to the control algorithm.
The flexible control aims not to enable data transmission to be carried out at a smooth speed, but to optimize the use of the communication network in the system as much as possible under the condition of combining various parameters, and communication data transmission is carried out according to the grade of service data under the condition expectation as much as possible. Data acquisition must take into account several factors: data grade, network bandwidth, reserved bandwidth, the scale of points to be collected, current network load, current load of the data collector and other factors influencing data transmission and processing. The collection process integrates the key points and factors, data collection and transmission strategy processing are carried out, and the data collection process is guaranteed to be timely, effective and stable. The judging of the condition of adopting the elastic control processing comprises the following steps: other types of data transmission states are retrieved in the communication network, the transmission rate is adjusted in real time according to the real-time state of the communication network, and when the communication network is busy, the rate is reduced, so that the impact on the communication network is reduced. The current state of the data acquisition end is judged to influence the data acquisition and transmission process, and the acquisition control algorithm also needs to be adjusted according to the current state, so that the transmission rate is increased or reduced. Under the condition of communication network sharing, a maximum bandwidth occupation value is actively set, so that under the condition of combining various control parameters, the maximum bandwidth occupation value is adjusted after the maximum bandwidth occupation value is reached. Different from the way that various data can be transmitted simultaneously, the flexible control algorithm can provide different data transmission rates according to different data grades. The more control parameters in this process, the more accurate the elastic control process can be.
Fig. 2 is a schematic diagram of data collected by the present invention. As can be seen from the figure, the present invention controls the amplitude of the rate fluctuation to a smaller range in a shorter time.
The above description is only an embodiment of the present invention, but the technical features of the present invention are not limited thereto, and any changes or modifications within the technical field of the present invention by those skilled in the art are covered by the claims of the present invention.
Claims (7)
1. A data acquisition method based on an industrial Internet operating system comprises the following steps:
step 1, data acquisition and identification: identifying the grade of the data type in the communication network in advance, and sequencing according to the grade;
step 2, defining adjustment parameters of data acquisition: under the condition of the same bandwidth, the acquisition end with few data points properly reduces the transmission rate to ensure that the terminal with large data volume obtains more transmission bandwidth;
and step 3: detecting the real-time state of the communication network, and judging whether to adopt elastic control processing according to the network condition;
the method is characterized in that: the elasticity control process includes:
1. controlling parameter input, and identifying factors influencing communication transmission, such as a data grade S, a data load D, a network state ST, a real-time state T of an acquisition end and a bandwidth set value SV;
2. according to a data model of an acquired object, predicting and analyzing data trend, and then compressing actually acquired data values according to a prediction analysis result M so as to reduce the data volume to be transmitted;
3. and calculating a data sending rate u, and carrying out data sending execution according to the adjusting rate:
k is the number of rate adjustments, u (k) is the sending rate, e (k) is the error between the input T and the set point (SV), Kp is the proportionality coefficient equal to S x D/ST x M, Kd is the differential time constant, Ki is the integral time constant;
4. receiving data sending feedback, updating the real-time state T, and re-executing control parameter input until the real-time state T is in a stable state;
5. and updating the data prediction model, optimizing the data trend prediction effect, performing regression verification on the model according to the later acquisition process, and further improving the prediction effect.
2. The data acquisition method based on the industrial internet operating system as claimed in claim 1, wherein: when the environment changes or the adjusted parameters do not meet the expectation, the elasticity control process further includes:
6. and (3) optimizing: in a steady-state network environment, the adjustment effect is expected, after real-time data are collected, initialization is carried out according to the identified parameters, the initial control rate is calculated, the data transmission end carries out data transmission according to the control rate, and meanwhile, the real-time network state and the real-time state of the data collection end are fed back to the control algorithm.
3. The data acquisition and identification in the step 1 or 2 are specifically as follows: and carrying out uniform grade division according to the data types from high to low, sequentially marking, wherein the data with high grade has high priority processing weight in the acquisition and transmission process.
4. The data acquisition method based on the industrial internet operating system as claimed in claim 1 or 2, wherein: the judging of the condition of adopting the elastic control processing comprises the following steps: other types of data transmission states are retrieved in the communication network, the transmission rate is adjusted in real time according to the real-time state of the communication network, and when the communication network is busy, the rate is reduced, so that the impact on the communication network is reduced.
5. The data acquisition method based on the industrial internet operating system as claimed in claim 1 or 2, wherein: the judging of the condition of adopting the elastic control processing comprises the following steps: the current state of the data acquisition end is judged to influence the data acquisition and transmission process, and the acquisition control algorithm also needs to be adjusted according to the current state, so that the transmission rate is increased or reduced.
6. The data acquisition method based on the industrial internet operating system as claimed in claim 1 or 2, wherein: the judging of the condition of adopting the elastic control processing comprises the following steps: under the condition of communication network sharing, a maximum bandwidth occupation value is actively set, so that under the condition of combining various control parameters, the maximum bandwidth occupation value is adjusted after the maximum bandwidth occupation value is reached.
7. The data acquisition method based on the industrial internet operating system as claimed in claim 1 or 2, wherein: the plurality of control parameters simultaneously act on the judgment of the elastic control process.
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Cited By (7)
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| CN112486125A (en) * | 2020-12-02 | 2021-03-12 | 中国电力科学研究院有限公司 | Data center integrated intelligent management and control method and platform |
| CN112597139A (en) * | 2020-12-21 | 2021-04-02 | 江苏省未来网络创新研究院 | Data information acquisition method based on industrial internet |
| CN113014434A (en) * | 2021-03-09 | 2021-06-22 | 安徽超清科技股份有限公司 | Data acquisition method based on industrial Internet |
| CN113438116A (en) * | 2021-07-01 | 2021-09-24 | 国网山东省电力公司博兴县供电公司 | Power communication data management system and method |
| CN113873016A (en) * | 2021-09-07 | 2021-12-31 | 机械工业仪器仪表综合技术经济研究所 | Industrial network data scheduling system and uploading system |
| CN114817375A (en) * | 2022-06-24 | 2022-07-29 | 深圳市智联物联科技有限公司 | Industrial internet data acquisition management system |
| CN115903714A (en) * | 2023-01-06 | 2023-04-04 | 济南市计量检定测试院 | Industrial pollution source emission overall process monitoring and adjusting device and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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