CN114993353A - Self-adaptive filtering method, device, equipment and system for multiple disaster monitoring equipment - Google Patents
Self-adaptive filtering method, device, equipment and system for multiple disaster monitoring equipment Download PDFInfo
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Abstract
The invention relates to the technical field of data acquisition, and an implementation mode of the invention relates to a self-adaptive filtering method, device, equipment and system of multi-disaster monitoring equipment. The adaptive filtering method for the disaster monitoring equipment is applied to the disaster monitoring equipment, and comprises the following steps: responding to the received test waveform sequence, and forming a waveform file corresponding to the test waveform sequence; sending the waveform file to a calculation module, and determining a digital filter coefficient by the calculation module according to the waveform file; and receiving the digital filter coefficient determined by the calculation module, and updating the filter algorithm. The implementation method provided by the invention can be used for carrying out self-adaptive filtering on disaster monitoring equipment hardware with different qualities or different aging degrees so as to improve the reliability of the monitoring result.
Description
Technical Field
The invention relates to the technical field of data acquisition, in particular to a self-adaptive filtering method of a multi-disaster monitoring device, a self-adaptive filtering device of the multi-disaster monitoring device, a disaster monitoring device and a self-adaptive filtering system of the multi-disaster monitoring device.
Background
The disaster monitoring equipment is equipment for monitoring various indexes of natural disasters. The quality of the existing disaster monitoring equipment is different, and the quality of the equipment can directly influence the monitoring result in the process of carrying out data measurement requiring high sensitivity. Although the equipment parameters of the disaster monitoring equipment are calibrated in the factory, the accuracy and reliability of the monitoring results are gradually reduced along with the increase of the service time due to the aging of the equipment and the like.
The existing solution is to debug the monitoring device on site regularly, so as to ensure the accuracy of the detection result of the monitoring device. The installation position of the ground disaster monitoring equipment is usually at a disaster hidden danger point, and the position of the disaster hidden danger point is a position which is difficult for personnel to reach or a position with construction safety risk, so that the risk and operation and maintenance cost for field debugging of the ground disaster monitoring equipment are high.
Therefore, how to calibrate monitoring equipment with different quality at different degrees regularly without field debugging and adjust the adaptive filter coefficient at any time to ensure the accuracy of the monitoring result is a technical problem to be solved urgently in the field.
Disclosure of Invention
In view of this, the present invention aims to provide a method, an apparatus, and a system for adaptive filtering of multiple disaster monitoring devices, so as to at least solve the problem that the filtering parameters of the existing disaster monitoring devices cannot be corrected in a unified manner.
In order to achieve the above object, a first aspect of the present invention provides an adaptive filtering method for a multiple disaster monitoring device, which is applied to a disaster monitoring device, and the method includes: responding to the received test waveform sequence, and forming a waveform file corresponding to the test waveform sequence; sending the waveform file to a calculation module, and determining a digital filter coefficient by the calculation module according to the waveform file; and receiving the digital filter coefficient determined by the calculation module, and updating the filter algorithm.
Preferably, the calculation module is disposed in the disaster monitoring device, or the calculation module is disposed in a cloud and communicatively coupled with the disaster monitoring device.
Preferably, the test waveform sequence is from a monitoring instrument management platform; the sending the waveform file to a computing module includes: and sending the waveform file to the monitoring instrument management platform, and forwarding the waveform file to the computing module by the monitoring instrument management platform.
Preferably, determining digital filter coefficients from the waveform file by the calculation module comprises: the calculation module obtains an original amplitude-frequency characteristic curve of the disaster monitoring equipment according to the corresponding relation between the frequency points in the waveform file and the response waveform amplitude values; normalizing the original amplitude-frequency characteristic curve into a compensation amplitude-frequency characteristic curve; and obtaining a digital filter coefficient corresponding to the compensation amplitude-frequency characteristic curve by adopting a self-adaptive filtering method.
Preferably, the correspondence between the frequency point and the response waveform amplitude value is represented by a two-dimensional array.
Preferably, normalizing to a compensated amplitude-frequency characteristic according to the original amplitude-frequency characteristic includes: selecting a response waveform amplitude value corresponding to one frequency point in the waveform file as a reference value; and dividing the response waveform amplitude value in the original amplitude-frequency characteristic curve by the reference value to convert the original amplitude-frequency characteristic curve into the compensation amplitude-frequency characteristic curve.
In a second aspect of the present invention, there is also provided a multiple disaster monitoring device adaptive filtering apparatus, including: the waveform file generating module is used for responding to the received test waveform sequence and forming a waveform file corresponding to the test waveform sequence; the file sending module is used for sending the waveform file to the calculating module, and the calculating module determines the coefficient of the digital filter according to the waveform file; and the algorithm updating module is used for receiving the digital filter coefficient determined by the calculating module and updating the filter algorithm.
In a third aspect of the invention, there is also provided a disaster monitoring device, the device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor when executing the computer program implementing the steps of the disaster monitoring device adaptive filtering method as described above.
In a fourth aspect of the present invention, there is also provided a multi-disaster monitoring device adaptive filtering system, including: the disaster monitoring device described above, and a computing module communicatively coupled to the disaster monitoring device.
Preferably, the system further comprises a monitoring instrument management platform configured to: and transmitting execution information between the disaster monitoring equipment and the computing module, and issuing a test waveform sequence to the disaster monitoring equipment.
Preferably, the monitoring instrument management platform includes a database, and the database is used for storing the disaster monitoring device and the corresponding digital filter coefficient.
Through the technical scheme provided by the invention, the method has the following beneficial effects: and self-adaptive filtering is performed on disaster monitoring equipment hardware with different qualities or different aging degrees so as to improve the reliability of a monitoring result.
Additional features and advantages of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of an adaptive filtering method for a multiple disaster monitoring device according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an adaptive filtering apparatus for multiple disaster monitoring devices according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an adaptive filtering system for multiple disaster monitoring devices according to an embodiment of the present invention.
Detailed Description
In addition, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present invention, are given by way of illustration and explanation only, not limitation.
Fig. 1 is a schematic flow chart of an adaptive filtering method for a multiple disaster monitoring device according to an embodiment of the present invention. As shown in fig. 1, an adaptive filtering method for a multiple disaster monitoring device is applied to a disaster monitoring device, and the method includes:
s01, responding to the received test waveform sequence, and forming a waveform file corresponding to the test waveform sequence; the test waveform sequence in this embodiment is preferably a swept sine wave sequence, and each frequency point of the swept sine wave sequence includes amplitude-frequency characteristic information and duration. The sweep frequency sine wave sequence set in the step can be set in a customized manner according to different types of monitoring equipment, the sweep frequency sine wave sequence can be guaranteed to cover the monitoring range of equipment instruments, and each frequency point of the sine wave sequence comprises amplitude, frequency and duration. After the disaster monitoring equipment receives the test waveform sequence, each frequency point generates a waveform file with frequency sweep response. The format of the waveform file is not limited herein. The generated waveform file of the frequency sweep response is preferably an independent mseed file or a waveform file in other formats, and the naming of the file format can be mutually corresponding to the frequency value of the frequency point.
S02, sending the waveform file to a calculation module, and determining a digital filter coefficient by the calculation module according to the waveform file; and the calculating module calculates the response waveform amplitude value and the actual frequency of each frequency point by adopting an FFT (fast Fourier transform) method according to the received waveform file. And simultaneously, combining the calculated frequency of each frequency point and the calculated response waveform amplitude value of the frequency point to form a frequency-amplitude corresponding relation or an amplitude-frequency corresponding relation, and generating an original amplitude-frequency characteristic curve of the monitoring instrument according to the corresponding relation. Calculating to obtain an amplitude-frequency characteristic curve of the compensation digital filter according to the original amplitude-frequency characteristic curve; and calculating to obtain the optimal digital filter coefficient corresponding to the monitoring instrument according to the amplitude-frequency characteristic curve of the compensation digital filter.
And S03, receiving the digital filter coefficient determined by the calculation module, and updating the filter algorithm. And sending the digital filter coefficient to a generation end of the waveform file, namely disaster monitoring equipment, and triggering the disaster monitoring equipment to update a filter algorithm of the disaster monitoring equipment by using the digital filter coefficient, so that the correction before monitoring is realized.
Through the implementation mode, the self-adaptive filtering of different disaster monitoring devices can be realized, and the quality of monitoring results of the disaster monitoring devices is ensured.
In some embodiments of the present invention, the computing module is disposed in the disaster monitoring device, or the computing module is disposed in a cloud and communicatively coupled with the disaster monitoring device. The setting position of the computing module can be local or cloud. When the calculation module is installed in the disaster monitoring device, its function is implemented by its internal components, such as a microprocessor, e.g., a CPU, to obtain the digital filter coefficients. When the computing module is arranged at the cloud end, the function of computing the coefficient of the digital filter is realized by the cloud server or the cloud platform. The two setting modes can be selected according to different application scenes, and the flexibility of correction of the calculation module is guaranteed.
In some embodiments of the present invention, in order to conveniently and uniformly collect test waveform sequences of all monitoring devices, the test waveform sequences are all from a monitoring instrument management platform; the sending the waveform file to a computing module includes: and each monitoring device respectively sends the waveform file to the monitoring instrument management platform, and the waveform file is forwarded to the computing module by the monitoring instrument management platform. A cloud platform, namely a monitoring instrument management platform, is introduced into the embodiment. The monitoring instrument management platform triggers the disaster monitoring equipment to execute subsequent processes by sending a test waveform sequence to the disaster monitoring equipment. Correspondingly, when the disaster monitoring equipment sends the waveform file, the waveform file is sent to the monitoring instrument management platform, and the waveform file is forwarded to the local or cloud computing module by the monitoring instrument management platform. According to the embodiment, the monitoring instrument management platform is arranged, so that unified management of the disaster monitoring equipment is realized, and the consistency of different disaster monitoring equipment in parameter configuration is ensured.
In some embodiments of the invention, determining, by the computation module, digital filter coefficients from the waveform file comprises: the calculation module obtains an original amplitude-frequency characteristic curve of the disaster monitoring equipment according to the corresponding relation between the frequency point in the waveform file and the response waveform amplitude value; normalizing the original amplitude-frequency characteristic curve into a compensation amplitude-frequency characteristic curve; and obtaining the digital filter coefficient corresponding to the compensation amplitude-frequency characteristic curve by adopting a self-adaptive filtering method. The embodiment provides a method for calculating coefficients of a data filter, which comprises the following steps: and calculating the response waveform amplitude value and the actual frequency of each frequency point by adopting an FFT method. Meanwhile, a two-dimensional array of (frequency, amplitude) is formed by combining the calculated frequency of each frequency point and the calculated response waveform amplitude value of the frequency point, and the original amplitude-frequency characteristic curve of the monitoring instrument is generated through the two-dimensional array of (amplitude, frequency) certainly. Calculating the optimal digital filter coefficient refers to calculating according to the principle of the FIR filter, specifically, establishing the amplitude-frequency characteristic relationship of the n-order FIR filter, and optimizing the loss function to obtain the optimal digital filter coefficient.
In some embodiments of the present invention, normalizing to a compensated amplitude-frequency characteristic from the original amplitude-frequency characteristic comprises: selecting a response waveform amplitude value corresponding to one frequency point in the waveform file as a reference value; and dividing the response waveform amplitude value in the original amplitude-frequency characteristic curve by the reference value to convert the original amplitude-frequency characteristic curve into the compensation amplitude-frequency characteristic curve. The method for calculating the amplitude-frequency characteristic curve of the compensation digital filter is to use the amplitude of one frequency point as a reference value to divide each value in the two-dimensional array of the response amplitude-frequency characteristic curve to calculate the amplitude-frequency characteristic curve of the compensation digital filter.
Based on the same inventive concept, some embodiments of the present invention further provide an adaptive filtering apparatus for a multiple disaster monitoring device. Fig. 2 is a schematic structural diagram of an adaptive filtering apparatus for multiple disaster monitoring devices according to an embodiment of the present invention. As shown in fig. 2, the apparatus includes: the waveform file generating module is used for responding to the received test waveform sequence and forming a waveform file corresponding to the test waveform sequence; the file sending module is used for sending the waveform file to the calculating module, and the calculating module determines the coefficient of the digital filter according to the waveform file; and the algorithm updating module is used for receiving the digital filter coefficient determined by the calculating module and updating the filter algorithm.
The specific limitations of each functional module in the adaptive filtering apparatus for multiple disaster monitoring devices may refer to the limitations of the adaptive filtering method for multiple disaster monitoring devices, and are not described herein again. The various modules in the above-described apparatus may be implemented in whole or in part by software, hardware, and combinations 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 some embodiments provided by the present invention, a disaster monitoring device is further provided, where the disaster monitoring device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the foregoing steps of the adaptive filtering method for a multiple disaster monitoring device when executing the computer program. The processor herein has functions of numerical calculation and logical operation, and has at least a central processing unit CPU having data processing capability, a random access memory RAM, a read only memory ROM, various I/O ports, an interrupt system, and the like. The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be provided with one or more than one, and the method is realized by adjusting the kernel parameters. The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The disaster monitoring device is implemented by various software and hardware electronic receiving ends including but not limited to a special early warning monitoring terminal, an internet of things monitoring device, a mobile terminal with a monitoring function, a data service device at an edge side and the like.
Fig. 3 is a schematic structural diagram of an adaptive filtering system of a multiple disaster monitoring device according to an embodiment of the present invention, as shown in fig. 3. A multiple disaster monitoring device adaptive filtering system comprises: the disaster monitoring device described above, and a computing module communicatively coupled to the disaster monitoring device. In some optional embodiments, the system further comprises a monitoring instrument management platform configured to: and transmitting execution information between the disaster monitoring equipment and the computing module, and issuing a test waveform sequence to the disaster monitoring equipment. The modules are connected through wires or wirelessly to form a networking structure. In the adaptive filtering system for multiple disaster monitoring devices, other devices such as routers for data transmission may be further included.
Specifically, the monitoring instrument management platform is used for issuing a sweep frequency sine wave sequence to monitoring equipment; the disaster monitoring equipment receives a sweep frequency sine wave sequence sent by the monitoring instrument management platform, generates a sweep frequency response waveform file, and transmits the sweep frequency response waveform file back to the monitoring instrument management platform; the system comprises a calculation module, a monitor management platform and a compensation digital filter, wherein the calculation module receives a sweep frequency response waveform file sent by the monitor management platform, calculates an amplitude-frequency characteristic curve of the compensation digital filter and an optimal digital filter coefficient corresponding to disaster monitoring equipment, and simultaneously feeds back the calculation result to the monitor management platform, the monitor management platform updates algorithm parameters of the digital filters of different monitoring equipment, and the specific updating process can be that the monitor management platform sends related coefficients to the disaster monitoring equipment to be updated by the disaster monitoring equipment, or the monitoring equipment management platform remotely updates the equipment.
In some optional embodiments, the monitoring instrument management platform includes a database for storing disaster monitoring devices and corresponding digital filter coefficients. The monitoring instrument management platform adopts a database to store various information of disaster monitoring equipment, such as digital filter coefficients and the like. The database may further include device information, location information, and a timestamp of a digital filter coefficient of the disaster monitoring device, and the type of the database is not limited here.
It should be noted that the various features described in the foregoing embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the embodiments of the present invention will not be described separately for the various possible combinations.
Those skilled in the art will appreciate that all or part of the steps in the method according to the above embodiments may be implemented by a program, which is stored in a storage medium and includes instructions for causing a single chip, a chip, or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present invention. 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.
In addition, any combination of the various embodiments of the present invention is also possible, and the same should be considered as the disclosure of the present invention as long as it does not depart from the idea of the embodiments of the present invention.
Claims (11)
1. A self-adaptive filtering method of multi-disaster monitoring equipment is applied to disaster monitoring equipment and is characterized by comprising the following steps:
responding to the received test waveform sequence, and forming a waveform file corresponding to the test waveform sequence;
sending the waveform file to a calculation module, and determining a digital filter coefficient by the calculation module according to the waveform file;
and receiving the digital filter coefficient determined by the calculation module, and updating the filter algorithm.
2. The method of claim 1, wherein the computing module is disposed in the disaster monitoring device, or wherein the computing module is disposed in a cloud and communicatively coupled to the disaster monitoring device.
3. The method of claim 1, wherein the sequence of test waveforms is from a monitoring instrument management platform;
the sending the waveform file to a computing module includes:
and sending the waveform file to the monitoring instrument management platform, and forwarding the waveform file to the computing module by the monitoring instrument management platform.
4. The method of claim 1, wherein determining digital filter coefficients from the waveform file by the computation module comprises:
the calculation module obtains an original amplitude-frequency characteristic curve of the disaster monitoring equipment according to the corresponding relation between the frequency points in the waveform file and the response waveform amplitude values;
normalizing the original amplitude-frequency characteristic curve into a compensation amplitude-frequency characteristic curve;
and obtaining the digital filter coefficient corresponding to the compensation amplitude-frequency characteristic curve by adopting a self-adaptive filtering method.
5. The method of claim 4, wherein the correspondence between the frequency points and the response waveform amplitude values is represented by a two-dimensional array.
6. A method according to claim 4 or 5, wherein normalizing to a compensated amplitude-frequency characteristic from the original amplitude-frequency characteristic comprises:
selecting a response waveform amplitude value corresponding to one frequency point in the waveform file as a reference value;
and dividing the response waveform amplitude value in the original amplitude-frequency characteristic curve by the reference value to convert the original amplitude-frequency characteristic curve into the compensation amplitude-frequency characteristic curve.
7. A self-adaptive filtering device for multiple disaster monitoring equipment is characterized by comprising:
the waveform file generation module is used for responding to the received test waveform sequence and forming a waveform file corresponding to the test waveform sequence;
the file sending module is used for sending the waveform file to the calculating module, and the calculating module determines the coefficient of the digital filter according to the waveform file; and
and the algorithm updating module is used for receiving the digital filter coefficient determined by the calculating module and updating the filter algorithm.
8. Disaster monitoring device, the device comprising a memory, a processor and a computer program stored in the memory and being executable on the processor, wherein the processor, when executing the computer program, performs the steps of the disaster monitoring device adaptive filtering method as claimed in any one of the claims 1 to 6.
9. A self-adaptive filtering system of a multi-disaster monitoring device is characterized by comprising: the disaster monitoring device of claim 8, and a computing module communicatively coupled with the disaster monitoring device.
10. The system of claim 9, further comprising a monitoring instrument management platform configured to: and transmitting execution information between the disaster monitoring equipment and the computing module, and issuing a test waveform sequence to the disaster monitoring equipment.
11. The system of claim 10, wherein the monitoring instrument management platform includes a database for storing disaster monitoring devices and corresponding digital filter coefficients.
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