CN107222551B - Data transmission and processing method, equipment and information processing center - Google Patents

Data transmission and processing method, equipment and information processing center Download PDF

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CN107222551B
CN107222551B CN201710485876.3A CN201710485876A CN107222551B CN 107222551 B CN107222551 B CN 107222551B CN 201710485876 A CN201710485876 A CN 201710485876A CN 107222551 B CN107222551 B CN 107222551B
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张源方
赵博
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Neusoft Corp
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Abstract

The application provides a data transmission and processing method, equipment and an information processing center, wherein the information processing center issues sensor data serving as independent variables, sensor data serving as dependent variables and an operation relation between the sensor data and the dependent variables, and the equipment only sends the sensor data serving as the independent variables to the information processing center under the condition that the acquired sensor data meet the association relation so as to reduce the sent data volume.

Description

Data transmission and processing method, equipment and information processing center
Technical Field
The present application relates to the field of electronic information, and in particular, to a data transmission and processing method, device, and information processing center.
Background
With the development of network technology and the application of various intelligent devices in enterprises, the technology of the internet of things brings great benefits to the development of the enterprises. Through the networking of various intelligent devices, enterprises can manage and monitor various key devices very conveniently, discover equipment abnormity and maintain the equipment rapidly in time, and economic loss is reduced. Meanwhile, enterprises can also utilize the collected real-time data of various intelligent devices, and various modes which can improve the utilization rate of the devices and reduce the operation and maintenance costs of the devices are analyzed by combining advanced algorithms such as artificial intelligence and the like, so that the enterprise benefits are improved.
In an internet of things system, various intelligent devices need to acquire attribute (including static attribute and dynamic attribute) data, the static attribute data is generally directly stored in a tag, and the dynamic attribute data needs to be detected by a sensor in real time. The equipment needs to periodically transmit attribute data (also called sensor data) detected in real time to the information processing center, and the amount of data to be uploaded is large under the condition that the number of sensors of the equipment is large and/or the acquisition frequency is high.
Disclosure of Invention
The application provides a data transmission and processing method, equipment and an information processing center, and aims to solve the problem that the data volume transmitted by equipment in the Internet of things is large.
In order to achieve the above object, the present application provides the following technical solutions:
a data transmission method is applied to equipment in the Internet of things and comprises the following steps:
acquiring an incidence relation of sensor data, wherein the incidence relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable;
searching for a dependent variable value and an independent variable value in the acquired sensor data, wherein the dependent variable value is the sensor data which is indicated by the association relation and is used as the dependent variable, and the independent variable value is the sensor data which is indicated by the association relation and is used as the independent variable;
and transmitting only the argument value when the argument value is obtained from the argument value by the operation relation.
Optionally, the method further includes:
and transmitting the dependent variable value and the independent variable value when the dependent variable value and the independent variable value do not satisfy the association relationship.
A data processing method is applied to an information processing center of the Internet of things and comprises the following steps:
receiving historical sensor data, the sensor data being collected by a device via a sensor;
obtaining an association relation according to the historical sensor data, wherein the association relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable;
and sending the association relation to the equipment, wherein the association relation is used for searching for a dependent variable value and an independent variable value in the acquired sensor data by the equipment, and only sending the independent variable value under the condition that the dependent variable value is obtained by the independent variable value through the operation relation, wherein the dependent variable value is the sensor data which is used as the dependent variable and indicated by the association relation, and the independent variable value is the sensor data which is used as the independent variable and indicated by the association relation.
Optionally, the method further includes:
and under the condition that the independent variable value and the dependent variable value sent by the equipment are received, or under the condition that the received independent variable value and the received dependent variable value do not satisfy the association relationship, recalculating the association relationship.
Optionally, the method further includes:
and under the condition of only receiving the independent variable value sent by the equipment, calculating the dependent variable value according to the incidence relation and the independent variable value.
An apparatus, comprising:
the acquisition module is used for acquiring the incidence relation of the sensor data, wherein the incidence relation comprises the operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable;
the searching module is used for searching for a dependent variable value and an independent variable value in the acquired sensor data, wherein the dependent variable value is the sensor data which is indicated by the association relation and is used as the dependent variable, and the independent variable value is the sensor data which is indicated by the association relation and is used as the independent variable;
and the sending module is used for only sending the independent variable value under the condition that the dependent variable value is obtained by the independent variable value through the operational relation.
Optionally, the sending module is further configured to:
and transmitting the dependent variable value and the independent variable value when the dependent variable value and the independent variable value do not satisfy the association relationship.
An information processing center comprising:
a receiving module for receiving historical sensor data, the sensor data being collected by a device via a sensor;
the determining module is used for obtaining an incidence relation according to the historical sensor data, wherein the incidence relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable;
a sending module, which is used for sending the association relation to the equipment, the association relation is used for the equipment to search for the dependent variable value and the independent variable value in the collected sensor data, the dependent variable value is passed through the independent variable value under the condition that the operational relation is obtained, only the independent variable value is sent, the dependent variable value is indicated by the association relation as the sensor data of the dependent variable, and the independent variable value is indicated by the association relation as the sensor data of the independent variable.
Optionally, the determining module is further configured to:
and under the condition that the receiving module receives the independent variable value and the dependent variable value sent by the equipment, or under the condition that the received independent variable value and the received dependent variable value do not satisfy the association relationship, recalculating the association relationship.
Optionally, the method further includes:
and the calculating module is used for calculating the dependent variable value according to the association relation and the independent variable value under the condition that the receiving module only receives the independent variable value sent by the equipment.
In the application, the information processing center issues the operation relation between the sensor data serving as the independent variable and the sensor data serving as the dependent variable, which is determined according to the historical sensor data, as the association relation, and the equipment only sends the sensor data serving as the independent variable to the information processing center under the condition that the acquired sensor data meets the association relation, so that the sent data volume is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a data transmission method disclosed in an embodiment of the present application;
fig. 2 is a flowchart of a data transmission and processing method according to an embodiment of the present disclosure;
FIG. 3 is a schematic structural diagram of an apparatus disclosed in an embodiment of the present application;
fig. 4 is a schematic structural diagram of an information processing center disclosed in an embodiment of the present application.
Detailed Description
The data transmission method can be applied to the Internet of things, in the embodiment, the Internet of things comprises an information center and equipment, a sensor is arranged on the equipment, and the equipment collects sensor data through a sensor. The equipment uploads the data acquired by the sensor to the information center, and the information center processes the data.
The data transmission method aims to reduce the data volume uploaded by equipment on the premise that the data processing center does not influence the analysis of the sensor data.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a data transmission method disclosed in an embodiment of the present application, and for convenience of understanding, this embodiment is described from the perspective of interaction between a device in the internet of things and an information processing center (the information processing center is not shown in fig. 1), but the interaction does not form a limitation on steps performed by the device and the information center respectively.
Fig. 1 includes the following steps: .
The method shown in fig. 1 comprises the following steps:
s101: the device acquires an association relationship of the sensor data, the association relationship including an operational relationship of the sensor data as an independent variable and the sensor data as a dependent variable.
That is, there is an operational relationship between certain sensor data. In this embodiment, the operational relationship between sensor data is used as the association relationship. In addition to the operational relationship, in the present embodiment, the association relationship may further include sensor data as an independent variable and sensor data as a dependent variable, for example, y — 2x is an association relationship, where x is an independent variable and y is a dependent variable.
In the internet of things, the sensor data acquired by the equipment through each sensor may have an operational relationship, for example, there is a positive correlation between the wind speed data acquired by the wind speed sensor and the yaw angle data acquired by the yaw counting sensor. Namely, the association relationship includes: and positive correlation between wind speed data acquired by the wind speed sensor as an independent variable and yaw angle data acquired by the yaw counting sensor as a dependent variable.
The association relationship may be determined by the device according to the historical data obtained by each sensor (see the following embodiment for a specific determination method), or may be determined by another device, for example, an information processing center, according to the historical data obtained by each sensor sent by the device (see the following embodiment for a specific determination method), and then sent to the device described in this embodiment.
It should be noted that, in the data collected by each sensor, there may be a correlation between one sensor data and multiple sensor data, for example, the temperature data collected by the temperature transmitter is inversely correlated with the wind speed data collected by the wind speed sensor, and is positively correlated with the rotational speed data collected by the rotational speed sensor. It is also possible that certain sensor data has no operational relationship with other sensor data. For example, data collected by a brake wear sensor has no operational relationship with data collected by a temperature sensor, a wind direction sensor, and the like.
S102: the device searches for sensor data indicated by the association as a dependent variable (for convenience of description, referred to as a dependent variable value) and sensor data indicated by the association as an independent variable (for convenience of description, referred to as an independent variable value) among the collected sensor data.
In the above example, after the wind power generator determines that there is a positive correlation between the wind speed data and the yaw angle data according to the historical data acquired by the wind speed sensor and the yaw counting sensor, the wind speed data acquired by the wind speed sensor and the yaw angle data acquired by the yaw counting sensor are searched in the data (non-historical data) acquired by each sensor.
S103: the device transmits only the argument value to the information processing center when the argument value and the argument value conform to the operation relationship.
In the above example, the wind turbine verifies whether the dependent variable value, i.e., the yaw angle data, is positively correlated with the independent variable value, i.e., the wind speed data. If yes, determining that the dependent variable value and the independent variable value are in accordance with the operation relationship. In this case, only the wind speed data is sent to the information processing center.
Optionally, the information processing center calculates a dependent variable value, that is, sensor data serving as the dependent variable, according to the received independent variable value and the association relationship. The information processing center can also process the independent variable value and the dependent variable value, and the specific processing mode can be referred to the prior art and is not described herein again.
It can be seen from the method described in fig. 1 that there is an operational relationship between the dependent variable values and the independent variable values. Therefore, the device does not need to transmit the dependent variable value, but only needs to transmit the sensor data as the independent variable, and the information processing center, which is the receiving party of the data, can calculate the sensor data as the dependent variable by itself. Therefore, the data transmission amount of the device can be reduced. Further, the network load can be reduced, and in the case of transmitting data using a mobile network, since the amount of data transmitted is reduced, the use cost of the network can be reduced.
It should be noted that if the association relationship is determined by the device, for example, the wind turbine, the association relationship needs to be sent to the analyzer of the sensor data, that is, the information processing center. Since the association does not need to be repeatedly transmitted when the association is not changed, the amount of data that the device needs to transmit is still small compared to transmitting all the sensor data.
The method shown in fig. 1 will be described in more detail below, taking the plant as a wind turbine as an example.
The wind power generator is generally provided with the following sensors: the device comprises a rotating speed sensor, a yaw counting sensor, a wind speed sensor, a wind direction sensor, a vibration sensor, a temperature sensor, a brake wear sensor and the like.
Data acquired by the wind driven generator through the rotating speed sensor is recorded as X1And recording the data acquired by the yaw counting sensor as X2And recording the data acquired by the wind speed sensor as X3And recording the data acquired by the wind direction sensor as X4And recording the data acquired by the vibration sensor as X5And recording the data acquired by the temperature sensor as X6And recording the data acquired by the brake wear sensor as X7。
Fig. 2 is a diagram of another data transmission method disclosed in the embodiment of the present application, including the following steps:
s201: and the information processing center obtains the association relation of the sensor data according to the historical sensor data received from each wind driven generator.
The sensor data acquisition model may be represented as
Figure BDA0001330447840000071
Wherein m is the number of sampling cycles, X in this step1-X7Are historical data.
The method for determining the association relationship specifically comprises the following steps:
1. calculating a correlation coefficient r between different sensor dataij(i is more than or equal to 1, j is less than or equal to 7) and the formula is as follows:
Figure BDA0001330447840000072
wherein the content of the first and second substances,
Figure BDA0001330447840000073
and
Figure BDA0001330447840000074
are respectively a sensor XiAnd XjIs measured.
2. For sensor data XiIn the case of rijFind out the relation rij≥H1(H1To select a threshold valueNormal case is 0.5, which can be adjusted according to actual conditions), and determining the sensor data X by using the least square methodiIn relation to other sensor data, i.e.
Figure BDA0001330447840000075
Figure BDA0001330447840000076
I.e. an association relationship, wherein αkAnd β is the regression coefficient when least squares fit RMSE is minimal.
S202: the information processing center sends the association determined in S201 to the wind power generator.
S203: the wind driven generator is used as a data acquisition end, and the sensor data, namely the real-time data X, is acquired in real time through the sensors1-X7。
S204: the wind turbine determines the actual value of the sensor data as a dependent variable, i.e. the acquired sensor data XiAnd a calculated value calculated from sensor data and operational relations as independent variables, i.e.
Figure BDA0001330447840000081
Whether the difference between them exceeds a preset threshold, i.e. | Xi-xp|≤H2And if so, executing S205-S206, otherwise, executing S207.
Wherein the allowable error threshold value H2The value is 0.1, and can be adjusted according to the actual application condition.
S205: the wind turbine sends sensor data as arguments to an information processing center.
S206: the information processing center calculates sensor data as a dependent variable based on the sensor data as an independent variable and the association relationship.
Specifically, the information processing center is based on XkAnd
Figure BDA0001330447840000082
calculating Xi。
S207: the wind power generator sends all the collected sensor data to the information processing center, wherein the sensor data comprises sensor data serving as independent variables and sensor data serving as dependent variables.
In the case where the information processing center issues the association, if the sensor data transmitted by the wind turbine generator as the dependent variable is still received, it is possible that the association previously issued to the equipment is incorrect or changed. Therefore, optionally, after S207, the following steps may also be performed:
s208: and the information processing center re-determines the association relationship according to the historical sensor data uploaded by the wind driven generator.
In the method shown in fig. 2, the information processing center issues the operational relationship between the sensor data as the independent variable and the sensor data as the dependent variable as the association relationship, and the device transmits only the sensor data as the independent variable to the information processing center to reduce the amount of transmitted data when the acquired sensor data satisfies the association relationship.
Fig. 3 is a device disclosed in an embodiment of the present application, including: the device comprises an acquisition module, a search module and a sending module.
The acquisition module is used for acquiring the incidence relation of the sensor data, wherein the incidence relation comprises the operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable.
The searching module is used for searching for a dependent variable value and an independent variable value in the collected sensor data, the dependent variable value is indicated by the association relationship and is used as the sensor data of the dependent variable, and the independent variable value is indicated by the association relationship and is used as the sensor data of the independent variable.
The sending module is used for sending the independent variable value only under the condition that the dependent variable value is obtained by the independent variable value through the operation relation. And transmitting the dependent variable value and the independent variable value when the dependent variable value and the independent variable value do not satisfy the association relationship.
The device shown in fig. 3 can reduce the amount of data transmitted, thereby saving network usage costs.
Fig. 4 is an information processing center disclosed in an embodiment of the present application, including: the device comprises a receiving module, a determining module and a sending module.
The receiving module is used for receiving historical sensor data, and the sensor data is collected by equipment through a sensor.
The determining module is used for obtaining an association relation according to the historical sensor data, wherein the association relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable.
The sending module is used for sending the incidence relation to the equipment, the incidence relation is used for the equipment seeks dependent variable value and independent variable value in the sensor data of gathering, the dependent variable value by the independent variable value passes through under the circumstances that the operational relation obtained, only send the independent variable value, the dependent variable value is that the incidence relation is instructed the sensor data as the dependent variable, the independent variable value is that the incidence relation is instructed the sensor data as the independent variable.
Optionally, the determining module is further configured to recalculate the association relationship when the receiving module receives the argument value and the argument value sent by the device, or when the received argument value and the argument value do not satisfy the association relationship.
Optionally, a calculating module may be further included in fig. 4, configured to calculate the dependent variable value according to the association relationship and the independent variable value when the receiving module receives only the independent variable value sent by the device.
The information processing center shown in fig. 4 can determine the association relationship and issue the association relationship to the device, which can provide a basis for the device to reduce the amount of data to be sent.
The interaction process between the device shown in fig. 3 and the information processing center shown in fig. 4 can be seen from fig. 2, and is not described here again.
The functions described in the method of the embodiment of the present application, if implemented in the form of software functional units and sold or used as independent products, may be stored in a storage medium readable by a computing device. Based on such understanding, part of the contribution to the prior art of the embodiments of the present application or part of the technical solution may be embodied in the form of a software product stored in a storage medium and including several instructions for causing a computing device (which may be a personal computer, a server, a mobile computing device or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (8)

1. A data transmission method is applied to equipment in the Internet of things, and is characterized by comprising the following steps:
acquiring an incidence relation of sensor data, wherein the incidence relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable, and the incidence relation is determined according to historical data acquired by each sensor;
searching for a dependent variable value and an independent variable value in the acquired sensor data, wherein the dependent variable value is the sensor data which is indicated by the association relation and is used as the dependent variable, and the independent variable value is the sensor data which is indicated by the association relation and is used as the independent variable;
transmitting only the argument value when the argument value is obtained from the argument value by the operation relation;
and transmitting the dependent variable value and the independent variable value when the dependent variable value and the independent variable value do not satisfy the association relationship.
2. A data processing method is applied to an information processing center of the Internet of things, and is characterized by comprising the following steps:
receiving historical sensor data, the sensor data being collected by a device via a sensor;
obtaining an association relation according to the historical sensor data, wherein the association relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable;
and sending the association relation to the equipment, wherein the association relation is used for searching for a dependent variable value and an independent variable value in the collected sensor data of the equipment, the dependent variable value is obtained by passing through the independent variable value under the condition of obtaining the operation relation, only the independent variable value is sent, the dependent variable value is indicated by the association relation, the dependent variable value is indicated by the independent variable value, the dependent variable value is not satisfied by the independent variable value under the condition of the association relation, and the dependent variable value and the independent variable value are sent.
3. The method of claim 2, further comprising:
and under the condition that the independent variable value and the dependent variable value sent by the equipment are received, or under the condition that the received independent variable value and the received dependent variable value do not satisfy the association relationship, recalculating the association relationship.
4. The method of claim 2 or 3, further comprising:
and under the condition of only receiving the independent variable value sent by the equipment, calculating the dependent variable value according to the incidence relation and the independent variable value.
5. A data transmission device, comprising:
the acquisition module is used for acquiring the incidence relation of the sensor data, wherein the incidence relation comprises the operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable, and the incidence relation is determined according to historical data acquired by each sensor;
the searching module is used for searching for a dependent variable value and an independent variable value in the acquired sensor data, wherein the dependent variable value is the sensor data which is indicated by the association relation and is used as the dependent variable, and the independent variable value is the sensor data which is indicated by the association relation and is used as the independent variable;
and a transmission module for transmitting only the argument value when the argument value is obtained from the argument value through the operation relationship, and transmitting the argument value and the argument value when the argument value and the argument value do not satisfy the association relationship.
6. An information processing center, comprising:
a receiving module for receiving historical sensor data, the sensor data being collected by a device via a sensor;
the determining module is used for obtaining an incidence relation according to the historical sensor data, wherein the incidence relation comprises an operation relation between the sensor data serving as a dependent variable and the sensor data serving as an independent variable;
a sending module, is used for to the equipment sends the incidence relation, the incidence relation is used for the equipment looks for dependent variable value and argument value in the sensor data of gathering, the dependent variable value by the argument value passes through under the circumstances that the operational relation obtained, only send the argument value, the dependent variable value does the incidence relation indicates the sensor data as the dependent variable, the argument value does the incidence relation indicates the sensor data as the independent variable with the argument value does not satisfy under the circumstances of incidence relation, send the dependent variable value with the argument value.
7. The information processing center of claim 6, wherein the determination module is further configured to:
and under the condition that the receiving module receives the independent variable value and the dependent variable value sent by the equipment, or under the condition that the received independent variable value and the received dependent variable value do not satisfy the association relationship, recalculating the association relationship.
8. The information processing center according to claim 6 or 7, characterized by further comprising:
and the calculating module is used for calculating the dependent variable value according to the association relation and the independent variable value under the condition that the receiving module only receives the independent variable value sent by the equipment.
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