CN113660286A - Communication protocol fusion method combined with Kalman filtering data fusion and related equipment - Google Patents
Communication protocol fusion method combined with Kalman filtering data fusion and related equipment Download PDFInfo
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Abstract
The application relates to a communication protocol fusion method and device combined with Kalman filtering data fusion, computer equipment and a storage medium. The method comprises the following steps: acquiring first data acquired by each terminal device in the Internet of things, wherein the first data is associated with a device identifier and a type identifier; performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data; packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and the equipment identifier and the type identifier associated with the first data corresponding to the second data; and uploading the data packet to the Internet of things platform through a protocol stack. The method can improve the data precision and realize the fusion of a plurality of communication protocols.
Description
Technical Field
The application relates to the technical field of Internet of things, in particular to a communication protocol fusion method combined with Kalman filtering data fusion and related equipment.
Background
With the development of the internet of things technology and the increasing popularization of smart power grids, more and more terminal devices appear in a low-voltage distribution room, and based on different network technologies, various communication standards and transmission protocols are used, and the internet of things network system of the low-voltage distribution room gradually shows the trend of heterogeneity and closeness. The mass data transmission of multiple networks and different protocol standards cause multiple problems of low data precision, incapability of unifying multiple communication protocols, difficulty in network management and the like in the operation process of a low-voltage transformer area. The development of the low-voltage station area multi-communication protocol fusion algorithm is the key for solving the problems in order to integrate multiple communication protocols, effectively fuse collected information, timely and effectively process data, improve communication efficiency and finally greatly reduce communication cost.
In the related art, research on convergence of low-voltage station area internet-of-things communication protocols focuses on a dedicated protocol conversion chip and an embedded protocol conversion system. The special protocol conversion chip completes the conversion of data, and the system generally comprises an interface chip, a conversion chip and the like. For a client, the dedicated protocol conversion chip is a black box, the conversion algorithm is integrated only by using the dedicated chip, the system completes the conversion of data by depending on hardware, and the protocol conversion based on the dedicated chip is a specific circuit designed for a specific protocol, and has the defects of single function and lack of flexibility. The protocol conversion system built by the embedded system is a system capable of operating independently: the hardware part is formed on the basis of a microprocessor, a ROM, a RAM, a FLASH and the like; the data processing function of the protocol conversion is performed by software. The embedded system can design corresponding conversion capability and mode according to scene requirements, make up for the defects of a special protocol conversion chip, but cannot realize data fusion and communication protocol fusion of a low-voltage distribution area at the same time.
Disclosure of Invention
Therefore, in order to solve the above technical problems, it is necessary to provide a communication protocol fusion method and related device combining kalman filter data fusion, which can improve data accuracy and implement fusion of multiple communication protocols.
A communication protocol fusion method in conjunction with kalman filter data fusion, the method comprising:
acquiring first data acquired by each terminal device in the Internet of things, wherein the first data is associated with a device identifier and a type identifier;
performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data;
packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and a device identifier and a type identifier associated with first data corresponding to the second data;
and uploading the data to the Internet of things platform through a protocol stack.
In one embodiment, the performing fusion processing on each first data through kalman filtering to obtain second data corresponding to each first data includes: taking data collected by each terminal device as system state data, and predicting the state data at the current moment according to the state data at the previous moment; and optimizing the first data acquired by each terminal device according to the predicted state data at the current moment to obtain second data corresponding to each first data.
In one embodiment, optimizing first data collected by each terminal device according to predicted state data at the current time to obtain second data corresponding to each first data includes: predicting the system covariance at the current moment according to the system covariance at the previous moment; acquiring Kalman gain of the current moment according to the predicted system covariance of the current moment; optimizing first data collected by each terminal device according to Kalman gain at the current moment and predicted state data at the current moment to obtain second data corresponding to each first data.
In one embodiment, the method further comprises: and obtaining the system covariance of the current moment according to the Kalman gain of the current moment and the predicted system covariance of the current moment.
In one embodiment, encapsulating each of the second data based on a unified data packet structure to obtain a data packet includes: acquiring device identifications and type identifications corresponding to second data, wherein the device identifications corresponding to the second data are device identifications associated with first data corresponding to the second data, and the type identifications corresponding to the second data are type identifications associated with the first data corresponding to the second data; and storing the second data and the corresponding equipment identifier and type identifier thereof into a data segment for packaging to obtain a data packet.
In one embodiment, the unified data packet structure further includes: the system comprises a header, a monitoring node address, a data length, a check code and a packet tail.
In one embodiment, the terminal equipment comprises one or more of an environment security sensor, a smart meter, a low-voltage branch detection unit, a phase change switch, a distribution transformer terminal, a reactive power compensation device and switching station terminal equipment, and the environment security sensor comprises one or more of a temperature and humidity sensor, a smoke detector and a water sensor.
A communication protocol fusion apparatus in conjunction with kalman filter data fusion, the apparatus comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring first data acquired by each terminal device in the Internet of things, and the first data is associated with a device identifier and a type identifier;
the fusion module is used for performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data;
the encapsulation module is used for encapsulating each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and a device identifier and a type identifier associated with first data corresponding to the second data;
and the uploading module is used for uploading the data packet to the Internet of things platform through a protocol stack.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring first data acquired by each terminal device in the Internet of things, wherein the first data is associated with a device identifier and a type identifier;
performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data;
packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and a device identifier and a type identifier associated with first data corresponding to the second data;
and uploading the data packet to an Internet of things platform through a protocol stack.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring first data acquired by each terminal device in the Internet of things, wherein the first data is associated with a device identifier and a type identifier;
performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data;
packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and a device identifier and a type identifier associated with first data corresponding to the second data;
and uploading the data packet to an Internet of things platform through a protocol stack.
According to the communication protocol fusion method and device combined with Kalman filtering data fusion, the computer equipment and the storage medium, first data collected by each terminal equipment in the Internet of things are obtained, and the first data is associated with an equipment identifier and a type identifier; performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data; packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and the equipment identifier and the type identifier associated with the first data corresponding to the second data; and uploading the data packet to the Internet of things platform through a protocol stack. According to the data fusion processing is carried out to the data that each terminal equipment gathered in the thing networking through kalman filter, can improve the data accuracy to through unified data package structure, standardize all communication data's packaging format, make communication more high-efficient, upload the data package to the thing networking platform through the protocol stack at last, realize the integration of many communication protocols.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a communication protocol fusion method incorporating Kalman filtering data fusion in one embodiment;
FIG. 2 is a diagram of a unified data packet structure in one embodiment;
FIG. 3 is a diagram illustrating the logical structure of a protocol stack in one embodiment;
FIG. 4 is a schematic flow chart diagram illustrating a communication protocol fusion method incorporating Kalman filtering data fusion in one embodiment;
FIG. 5 is a block diagram of a communication protocol fusion device incorporating Kalman filtering data fusion in one embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The communication protocol fusion method combined with Kalman filtering data fusion can be applied to intelligent gateways, such as intelligent gateways in low-voltage transformer areas, wherein the intelligent gateways belong to edge terminal equipment and operate edge calculation programs. The intelligent gateway is downwards connected with various terminal devices to realize data conversion of different protocol contents, is upwards connected with an Internet of things platform, and can also upwards access other real-time systems through protocol conversion to realize the function of multiple purposes. The internet of things communication can be divided into local communication and remote communication, and the local communication includes but is not limited to: RS232/RS485 communication, Zigbee communication, USB communication, broadband power line carrier, Ethernet communication and the like; telecommunications include, but are not limited to: 5G communication, ethernet communication, etc.
In one embodiment, as shown in fig. 1, a communication protocol fusion method combined with kalman filter data fusion is provided, which is described as being applied to an intelligent gateway in a low-voltage platform area scenario, and includes the following steps S102 to S108.
S102, first data collected by each terminal device in the Internet of things are obtained, and the first data are associated with device identifications and type identifications.
The terminal equipment in the internet of things can be understood as equipment needing communication in the internet of things, the first data represent data actually collected by the terminal equipment, the equipment identification is used for distinguishing different terminal equipment (such as a temperature and humidity sensor, an intelligent electric meter and the like), and the type identification is used for distinguishing different data types (such as temperature data, humidity data, electric energy use data and the like). Associating the first data with the device identification and the type identification facilitates identifying a source of the collected data.
Taking the internet of things of a low-voltage distribution area as an example, the terminal devices include but are not limited to: the system comprises an environment security sensor, an intelligent electric meter, a low-voltage branch detection unit, a phase change switch, a distribution transformer terminal, a reactive compensation device and switching station terminal equipment, wherein the environment security sensor comprises but is not limited to a temperature and humidity sensor, a smoke detector and a water sensor. Thus, the first data includes, but is not limited to: temperature and humidity data of a temperature and humidity sensor, a fire alarm signal of a smoke detector, a flood alarm signal of a water sensor, electric energy use data of an intelligent ammeter, data such as voltage, current and power sent by a low-voltage branch detection unit, and operation state data of equipment such as a reactive power compensation device, a distribution transformer terminal and switching station terminal equipment.
And S104, performing fusion processing on the first data through Kalman filtering to obtain second data corresponding to the first data.
Kalman filtering can be used for fusing real-time dynamic multi-source redundant data, recursive by using statistical characteristics of a measurement model and determination of optimal fusion and data estimation in statistical significance, and the core idea is to obtain a current optimal value by calculation according to a current measurement value of terminal equipment, a predicted value at the previous moment and covariance. The second data can be understood as data obtained by optimizing the first data, so that the measurement data of the terminal equipment is more accurate.
In an embodiment, the step of performing fusion processing on each first data through kalman filtering to obtain second data corresponding to each first data may specifically include: taking data collected by each terminal device as system state data, and predicting the state data at the current moment according to the state data at the previous moment; and optimizing the first data acquired by each terminal device according to the predicted state data at the current moment to obtain second data corresponding to each first data.
Taking the internet of things of a low-voltage transformer area as an example, after data (namely measurement data) acquired by each terminal device is acquired, a system state equation of the low-voltage transformer area is formed, the acquired transformer area information and a Kalman filter algorithm are combined to perform fusion processing on the data, including calculation to obtain system covariance, and further, the covariance is continuously reduced through adjustment of a system matrix until a stable value is reached, so that an accurate state matrix of the system is obtained.
The specific formula for predicting the state data of the current time according to the state data of the previous time can be as follows:
P(k|k-1)＝T(k)P(k-1|k-1)+B(k)U(k) (1)
wherein, P (k | k-1) is the state result at the time k, which is obtained by predicting the state result at the time k-1, T (k) is a state transition matrix, P (k-1| k-1) is the state optimum result at the time k-1, B (k) is an input control item matrix, and U (k) is the current state control quantity.
In an embodiment, the step of optimizing the first data acquired by each terminal device according to the predicted state data at the current time to obtain the second data corresponding to each first data may specifically include: predicting the system covariance at the current moment according to the system covariance at the previous moment; acquiring Kalman gain of the current moment according to the predicted system covariance of the current moment; and optimizing the first data acquired by each terminal device according to the Kalman gain at the current moment and the predicted state data at the current moment to obtain second data corresponding to each first data.
The specific formula for predicting the system covariance at the current time according to the system covariance at the previous time may be as follows:
C(k|k-1)＝T(k)C(k-1|k-1)TT+N(k) (2)
where C (k | k-1) is a k-time system covariance matrix predicted using a k-1-time system covariance matrix, C (k-1| k-1) is a k-1-time system covariance matrix, and N (k) is a noise covariance matrix.
The specific calculation formula of kalman gain may be as follows:
G(k)＝C(k|k-1)M(k)T(M(k)C(k|k-1)M(k)T+E(k))-1 (3)
where G (k) is a Kalman gain matrix, M (k) is a measurement matrix, and E (k) is a measurement noise covariance matrix.
The specific formula of the filter estimation equation may be as follows:
P(k|k)＝P(k|k-1)+G(k)[Z(k)-M(k)P(k|k-1)] (4)
wherein, P (k | k) is the optimal estimated value at time k and corresponds to the second data, and z (k) is the measured value of the terminal device and corresponds to the first data.
In one embodiment, after obtaining the kalman gain at the current time and the predicted system covariance at the current time, the method further includes: and obtaining the system covariance of the current moment according to the Kalman gain of the current moment and the predicted system covariance of the current moment.
The specific formula of the covariance matrix update equation may be as follows:
C(k|k)＝[I-G(k)M(k)]C(k|k-1) (5)
where C (k | k) is the system covariance matrix at time k and I is the identity matrix.
And S106, packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and the device identifier and the type identifier associated with the first data corresponding to the second data.
Before the data are uploaded to the Internet of things platform, the data of each terminal device are packaged and uniformly converted into serial protocols, and a uniform data format is constructed for realizing integration of different types of protocols. Taking the internet of things of the low-voltage transformer area as an example, a uniform data packet structure can be designed according to the type of terminal equipment, the type of a protocol and the content of a message in the low-voltage transformer area. The unified data packet structure comprises a data segment, the data segment is used for storing effective data, and the effective data comprises second data obtained after Kalman filtering optimization and equipment identification and type identification corresponding to the second data.
In an embodiment, the step of encapsulating each second data based on a unified data packet structure to obtain a data packet may specifically include: acquiring equipment identification and type identification corresponding to each second data; and storing each second data and the corresponding equipment identifier and type identifier thereof into a data segment for packaging to obtain a data packet. The device identifier corresponding to the second data is a device identifier associated with the first data corresponding to the second data, and the type identifier corresponding to the second data is a type identifier associated with the first data corresponding to the second data.
In one embodiment, the unified data packet structure includes, in addition to the data segment: the system comprises a header, a monitoring node address, a data length, a check code and a packet tail. As shown in fig. 2, the unified data packet structure includes a header, an ID, a data length, a data segment, a check code, and a trailer. Wherein, the header indicates the beginning of a data packet, occupies one byte, and is indicated by 0x 0A; the ID represents the address of the whole embedded monitoring node, and occupies one byte, and the system can accommodate 256 monitoring nodes at most; the data length is used for representing the size of the data segment and occupies one node; the data segment comprises Id, identifiers and data of the terminal equipment nodes, wherein the Id represents the terminal equipment node addresses, the identifiers are used for identifying the data types of the terminal equipment, and the data are acquired by the terminal equipment; the check bit is used for checking data in the whole data packet and occupies one byte; the end of the packet represents the end of the data packet, and occupies one byte, represented by 0x 0F.
And S108, uploading the data packet to the Internet of things platform through a protocol stack.
The protocol stack can adopt a layered structure, and the complexity of a program can be reduced by simplifying the traditional protocol stack. In one embodiment, as shown in fig. 3, the receiving driver of each communication protocol is responsible for completing data reception of the device node at each end of the low-voltage distribution area, and each communication protocol processing part is responsible for processing the data frame and extracting valid data; the Ethernet receiving driver is responsible for packaging the extracted effective data and sending out the effective data to ensure effective transmission of a data link layer; IP processing and TCP processing respectively add an IP header and a TCP header to the data segment and send out the data frame through a network layer; the IP sending is responsible for sending the IP datagram to the next layer and is called by ICMP, TCP and SOCKET API. After the data is converted into ethernet frames and successfully transmitted, the convergence of multiple communication protocols is achieved.
In one embodiment, as shown in fig. 4, a communication protocol fusion method in combination with kalman filter data fusion is provided, which includes the following steps: initializing the system; creating a thread task; collecting data of equipment at each end of the low-voltage transformer area through a multi-communication protocol transceiving thread; performing fusion processing on data acquired from the low-voltage transformer area through a Kalman filtering algorithm to obtain more accurate data; packaging the fused data through a uniform data packet structure to obtain a data packet; and the data packet is sent out in a data frame form through a protocol stack, so that the fusion of multiple communication protocols is realized.
According to the communication protocol fusion method combining Kalman filtering data fusion, data fusion processing is carried out on data collected by each terminal device in the Internet of things through Kalman filtering, data precision can be improved, the packaging formats of all communication data are standardized through a unified data packet structure, communication is more efficient, and finally the data packets are uploaded to the Internet of things platform through a protocol stack, so that fusion of multiple communication protocols is realized.
It should be understood that, although the steps in the flowcharts related to the above embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in each flowchart related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
In one embodiment, as shown in fig. 5, there is provided a communication protocol fusion apparatus 500 in combination with kalman filter data fusion, including: an obtaining module 510, a fusing module 520, a packaging module 530, and an uploading module 540, wherein:
the obtaining module 510 is configured to obtain first data collected by each terminal device in the internet of things, where the first data is associated with a device identifier and a type identifier.
And a fusion module 520, configured to perform fusion processing on each first data through kalman filtering to obtain second data corresponding to each first data.
The encapsulating module 530 is configured to encapsulate each second data based on a unified data packet structure to obtain a data packet, where the unified data packet structure includes a data segment, and the data segment is used to store the second data and the device identifier and the type identifier associated with the first data corresponding to the second data.
And an uploading module 540, configured to upload the data packet to the internet of things platform through the protocol stack.
In an embodiment, when performing fusion processing on each first data through kalman filtering to obtain second data corresponding to each first data, the fusion module 520 is specifically configured to: taking data collected by each terminal device as system state data, and predicting the state data at the current moment according to the state data at the previous moment; and optimizing the first data acquired by each terminal device according to the predicted state data at the current moment to obtain second data corresponding to each first data.
In an embodiment, the fusion module 520 is specifically configured to, when optimizing the first data acquired by each terminal device according to the predicted state data at the current time to obtain the second data corresponding to each first data: predicting the system covariance at the current moment according to the system covariance at the previous moment; acquiring Kalman gain of the current moment according to the predicted system covariance of the current moment; and optimizing the first data acquired by each terminal device according to the Kalman gain at the current moment and the predicted state data at the current moment to obtain second data corresponding to each first data.
In one embodiment, the fusion module 520 is further configured to: and obtaining the system covariance of the current moment according to the Kalman gain of the current moment and the predicted system covariance of the current moment.
In an embodiment, the encapsulating module 530 is specifically configured to, when encapsulating each second data based on the unified data packet structure to obtain a data packet: acquiring device identifications and type identifications corresponding to the second data, wherein the device identifications corresponding to the second data are device identifications associated with first data corresponding to the second data, and the type identifications corresponding to the second data are type identifications associated with the first data corresponding to the second data; and storing each second data and the corresponding equipment identifier and type identifier thereof into a data segment for packaging to obtain a data packet.
In one embodiment, the unified data packet structure further includes: the system comprises a header, a monitoring node address, a data length, a check code and a packet tail.
In one embodiment, the terminal equipment comprises one or more of an environment security sensor, a smart meter, a low-voltage branch detection unit, a phase change switch, a distribution transformer terminal, a reactive power compensation device and a switching station terminal equipment, and the environment security sensor comprises one or more of a temperature and humidity sensor, a smoke detector and a water sensor.
In the communication protocol fusion device combining Kalman filtering data fusion, data fusion processing is performed on data collected by each terminal device in the Internet of things through Kalman filtering, data precision can be improved, the packaging formats of all communication data are standardized through a unified data packet structure, communication is more efficient, and finally the data packets are uploaded to an Internet of things platform through a protocol stack, so that fusion of multiple communication protocols is realized.
For specific limitations of the communication protocol fusion device combined with kalman filter data fusion, reference may be made to the above limitations of the communication protocol fusion method combined with kalman filter data fusion, and details are not repeated here. The modules in the communication protocol fusion device combined with kalman filter data fusion may be implemented wholly or partially by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a communication protocol fusion method in conjunction with kalman filter data fusion. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the above-described method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the respective method embodiment as described above.
In one embodiment, a computer program product or computer program is provided that includes computer instructions stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the steps in the various method embodiments described above.
It should be understood that the terms "first", "second", etc. in the above-described embodiments are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A communication protocol fusion method combined with Kalman filtering data fusion is characterized by comprising the following steps:
acquiring first data acquired by each terminal device in the Internet of things, wherein the first data is associated with a device identifier and a type identifier;
performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data;
packaging each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and a device identifier and a type identifier associated with first data corresponding to the second data;
and uploading the data packet to an Internet of things platform through a protocol stack.
2. The method according to claim 1, wherein performing a fusion process on each of the first data through kalman filtering to obtain second data corresponding to each of the first data comprises:
taking data collected by each terminal device as system state data, and predicting the state data at the current moment according to the state data at the previous moment;
and optimizing the first data acquired by each terminal device according to the predicted state data at the current moment to obtain second data corresponding to each first data.
3. The method of claim 2, wherein optimizing first data collected by each terminal device according to predicted state data at the current time to obtain second data corresponding to each first data comprises:
predicting the system covariance at the current moment according to the system covariance at the previous moment;
acquiring Kalman gain of the current moment according to the predicted system covariance of the current moment;
optimizing first data collected by each terminal device according to Kalman gain at the current moment and predicted state data at the current moment to obtain second data corresponding to each first data.
4. The method of claim 3, further comprising:
and obtaining the system covariance of the current moment according to the Kalman gain of the current moment and the predicted system covariance of the current moment.
5. The method according to any one of claims 1 to 4, wherein encapsulating each of the second data based on a unified packet structure to obtain a packet comprises:
acquiring device identifications and type identifications corresponding to second data, wherein the device identifications corresponding to the second data are device identifications associated with first data corresponding to the second data, and the type identifications corresponding to the second data are type identifications associated with the first data corresponding to the second data;
and storing the second data and the corresponding equipment identifier and type identifier thereof into a data segment for packaging to obtain a data packet.
6. The method of claim 5, wherein the unified packet structure further comprises: the system comprises a header, a monitoring node address, a data length, a check code and a packet tail.
7. The method of claim 1, wherein the terminal equipment comprises one or more of an environmental security sensor, a smart meter, a low voltage branch detection unit, a phase change switch, a distribution transformer terminal, a reactive power compensation device, and a switching station terminal equipment, and wherein the environmental security sensor comprises one or more of a temperature and humidity sensor, a smoke detector, and a water sensor.
8. A communication protocol fusion apparatus incorporating kalman filter data fusion, the apparatus comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring first data acquired by each terminal device in the Internet of things, and the first data is associated with a device identifier and a type identifier;
the fusion module is used for performing fusion processing on each first data through Kalman filtering to obtain second data corresponding to each first data;
the encapsulation module is used for encapsulating each second data based on a unified data packet structure to obtain a data packet, wherein the unified data packet structure comprises a data segment, and the data segment is used for storing the second data and a device identifier and a type identifier associated with first data corresponding to the second data;
and the uploading module is used for uploading the data packet to the Internet of things platform through a protocol stack.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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