CN110365429B - Detection method, device and system, storage medium and processor - Google Patents
Detection method, device and system, storage medium and processor Download PDFInfo
- Publication number
- CN110365429B CN110365429B CN201910649583.3A CN201910649583A CN110365429B CN 110365429 B CN110365429 B CN 110365429B CN 201910649583 A CN201910649583 A CN 201910649583A CN 110365429 B CN110365429 B CN 110365429B
- Authority
- CN
- China
- Prior art keywords
- information
- electrical appliance
- channel state
- state information
- aging
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/309—Measuring or estimating channel quality parameters
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
- H04B7/0621—Feedback content
- H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Quality & Reliability (AREA)
- Selective Calling Equipment (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention discloses a detection method, a detection device and a detection system. Wherein, the method comprises the following steps: acquiring electrical appliance information and channel state information of an electrical appliance accessed to the wireless network equipment, wherein the channel state information is extracted from a wireless network signal of the electrical appliance by the wireless network equipment; and determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information. The invention solves the technical problem that the utilization rate of the wireless network equipment is not high because the wireless network equipment in the related technology is only used for communication interaction.
Description
Technical Field
The invention relates to the field of aging detection, in particular to a detection method, a detection device and a detection system.
Background
It is well known that wireless network devices play a crucial role in signal transmission. In recent years, as wireless communication technology has matured, more scholars have started to focus on applications other than data transmission. Therefore, a WiFi signal with a very wide coverage area attracts great attention, and besides a daily data transmission function, the WiFi signal can also inform us about information of a WiFi channel. However, in the field of smart homes in which wireless network devices are generally used to implement the internet of things, the application scenarios of the wireless network devices are limited to common communication interaction, such as APP control and fault reporting.
Aiming at the technical problem that the utilization rate of wireless network equipment is not high due to the fact that the wireless network equipment in the related technology is only used for communication interaction, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a detection method, a detection device and a detection system, which at least solve the technical problem that wireless network equipment in the related technology is only used for communication interaction, so that the utilization rate of the wireless network equipment is not high.
According to an aspect of an embodiment of the present invention, there is provided a detection method including: acquiring electrical appliance information and channel state information of an electrical appliance accessed to the wireless network equipment, wherein the channel state information is extracted from a wireless network signal of the electrical appliance by the wireless network equipment; and determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information.
Optionally, before acquiring the appliance information and the channel state information of the appliance accessing the wireless network device, the method further includes: and establishing a database of different electrical appliance information, wherein the database is prestored with aging characteristic data of each element.
Optionally, determining aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information, including: determining a target database according to the electrical appliance information; carrying out redundancy removal processing on the channel state information to obtain preprocessing information; extracting the characteristics of the preprocessed information to obtain characteristic parameters; and matching the characteristic parameters with aging characteristic data in the target database to obtain aging information.
Optionally, performing redundancy removal processing on the channel state information to obtain preprocessed information, including: performing convolution processing on data in each two channels in the channel state information through a low-pass filter to obtain de-noising data; and performing dimensionality reduction on the de-noised data through a dimensionality reduction algorithm to obtain preprocessing information.
Optionally, the feature parameters include a first feature parameter and a second feature parameter, and performing feature extraction on the preprocessed information to obtain the feature parameters includes: carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; extracting a wavelet coefficient of each frequency band in the spectrogram to serve as a first characteristic parameter; and estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as second characteristic parameters.
Optionally, after determining aging information of each element in the appliance according to the appliance information and the channel state information, the method further includes: and sending the aging information to the prompting equipment.
According to another aspect of the embodiments of the present invention, there is also provided a detection method, including: acquiring a wireless network signal of an electric appliance; extracting channel state information in wireless network signals; and uploading the channel state information and the electrical appliance information of the electrical appliance to a server, wherein the server determines the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information.
According to another aspect of the embodiments of the present invention, there is also provided a detection apparatus, including: the first acquisition module is used for acquiring the electric appliance information and the channel state information of an electric appliance accessed to the wireless network equipment, wherein the channel state information is extracted from a wireless network signal of the electric appliance by the wireless network equipment; and the determining module is used for determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information.
According to another aspect of the embodiments of the present invention, there is also provided a detection apparatus, including: the second acquisition module is used for acquiring wireless network signals of the electric appliance; the extraction module is used for extracting the channel state information in the wireless network signal; and the uploading module is used for uploading the channel state information and the electrical appliance information of the electrical appliance to the server, wherein the server determines the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information.
According to another aspect of the embodiments of the present invention, there is also provided a storage medium including a stored program, wherein when the program runs, a device on which the storage medium is located is controlled to execute the above detection method.
According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes the detection method.
According to another aspect of the embodiments of the present invention, there is also provided a detection system, including: the wireless network equipment is used for acquiring a wireless network signal of the electric appliance, extracting channel state information in the wireless network signal and uploading the channel state information and the electric appliance information of the electric appliance to the server; and the server is used for determining the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information.
In the embodiment of the invention, the electrical appliance information and the channel state information of the electrical appliance accessed to the wireless network equipment are acquired, wherein the channel state information is extracted from the wireless network signal of the electrical appliance by the wireless network equipment; and determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information. Compared with the prior art, the scheme has the advantages that the channel state information in the wireless network signal of the electric appliance is extracted, the aging degree of each component in the electric appliance is determined by using the change of the channel state information, the purpose of determining the aging information of the electric appliance is achieved, and the technical problem that the utilization rate of wireless network equipment is low because wireless network equipment in the related technology is only used for communication interaction is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a schematic flow chart of an alternative detection method according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of an alternative wireless network device sensing aging information of an air conditioner according to embodiment 1 of the present invention;
fig. 3 is a schematic flow chart of an alternative server processing channel state information according to embodiment 1 of the present invention;
FIG. 4 is a schematic flow chart of an alternative detection method according to embodiment 2 of the present invention;
FIG. 5 is a schematic view of an alternative detecting unit according to embodiment 3 of the present invention; and
fig. 6 is a schematic view of an alternative detection apparatus according to embodiment 4 of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
While embodiments of a detection method are provided from a server perspective in accordance with embodiments of the present invention, it should be noted that the steps illustrated in the flowchart of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than presented herein.
Fig. 1 is a detection method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, electric appliance information and channel state information of an electric appliance accessed to the wireless network equipment are obtained, wherein the channel state information is extracted from a wireless network signal of the electric appliance by the wireless network equipment.
In an alternative, the wireless network device may be a WiFi module, and the WiFi module may be configured in an appliance for receiving and transmitting signals; the electrical appliance can be any electrical appliance with wireless network equipment, such as an intelligent air conditioner, an intelligent sound box, an intelligent television and the like; the electrical appliance information may be a model of an electrical appliance.
Because a small change in the environment may generate a certain interference on a received waveform of the wireless network device, a radio wave transmitted by a transmitter (e.g., a router) propagates through multiple paths such as direct radiation, reflection, and scattering, and a multipath superimposed signal formed at a signal receiver (e.g., a wireless network device) may reflect a change in the environment.
The Channel State Information (CSI) belongs to fine-grained Information of a Physical Layer (PHY), and can measure the phase and amplitude of each subcarrier, so that the subcarrier Information is displayed more abundantly, and the multipath resolution capability is displayed to a certain extent, and particularly, small changes of signals are sensed in a non-line-of-sight range, and therefore, the CSI has the characteristics of high sensitivity, wide sensing area and the like. The invention just considers the factors and senses the tiny change of each component element in the electric appliance by extracting the channel state information in the wireless network signal.
In the above steps, after the wireless network device acquires the wireless network signal which is directly transmitted, reflected and scattered by the electric appliance, the wireless network device firstly extracts the channel state information therein through a software tool, namely extracts the information on the subcarrier waveform in the WIFI channel, and sends the electric appliance information and the channel state information of the electric appliance to the server.
And step S104, determining the aging information of each element in the electric appliance according to the electric appliance information and the channel state information.
In an alternative, the aging information may be the aging degree, aging speed, etc. of each component in the appliance, and the aging degree may be expressed in percentage form, for example, the aging degree of the compressor is 60%, the aging degree of the evaporator is 30%, etc.
In an optional embodiment, the server performs preprocessing on the channel state information uploaded by the wireless network device, such as filtering, removing outliers, extracting feature values, and the like, and then identifies the processed information through a preset algorithm corresponding to the electrical appliance information to determine aging information of each element.
In another optional embodiment, the server performs preprocessing on the channel state information and the electrical appliance information uploaded by the wireless network device, such as filtering, abnormal point removal, characteristic value extraction and the like, and finally identifies the processed information through algorithms such as a neural network and the like to determine the aging information of each element.
It should be noted that the server executing the method of the present embodiment may be a cloud server, and may also be a local server. In the case of a local server, may be located in the appliance.
Fig. 2 is a schematic diagram of an alternative wireless network device for sensing aging information of an air conditioner according to the embodiment. As shown in fig. 2, the air conditioning panel is affected by water leakage from the ceiling for a long time and has a fast aging rate. Radio waves emitted by the router are transmitted through multiple paths such as direct radiation, reflection and scattering of the air conditioner, and multipath superposed signals are formed at wireless network equipment of the air conditioner. After the wireless network equipment acquires the superposed wireless network signal, the channel state information in the superposed wireless network signal is extracted through a software tool, namely the information on the subcarrier waveform in the WIFI channel is extracted, and the electric appliance information and the channel state information of the electric appliance are sent to the cloud server. And the cloud server processes and identifies the channel state information according to the electric appliance information of the electric appliance, determines that the aging degree of the air conditioner panel of the electric appliance is serious and reaches 60%, and immediately informs a user to maintain.
In the embodiment of the invention, the electrical appliance information and the channel state information of the electrical appliance accessed to the wireless network equipment are acquired, wherein the channel state information is extracted from the wireless network signal of the electrical appliance by the wireless network equipment; and determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information. Compared with the prior art, the scheme adopts the wireless network equipment with the channel state information detection function, the aging degree of each component in the electric appliance is determined by extracting the channel state information in the wireless network signal of the electric appliance and utilizing the change of the channel state information, the purpose of determining the aging information of the electric appliance is achieved, and the technical problem that the utilization rate of the wireless network equipment is not high due to the fact that the wireless network equipment in the related technology is only used for communication interaction is solved.
Optionally, before the step S102 is executed to acquire the appliance information and the channel state information of the appliance accessing the wireless network device, the method of this embodiment may further include:
step S101, establishing a database of different electrical appliance information, wherein aging characteristic data of each element is prestored in the database.
Since the different types and models of electrical appliances may have different components, before implementing the method of the embodiment, the server first establishes databases of different electrical appliance information, and each database prestores aging characteristic data of the components having the same electrical appliance information.
In an alternative embodiment, fig. 3 shows a flow diagram of a server processing channel state information. As shown in fig. 3, the step S104 determines the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information, and may specifically include the following steps:
and step S1041, determining a target database according to the electric appliance information.
Step S1042, performing redundancy removal on the channel state information to obtain preprocessed information.
And step S1043, performing feature extraction on the preprocessed information to obtain feature parameters.
In an alternative, the characteristic parameter may be a characteristic parameter of a compressor, a characteristic parameter of an evaporator, a characteristic parameter of a condenser, a characteristic parameter of a panel, or the like.
And step S1044, matching the characteristic parameters with aging characteristic data in the target database to obtain aging information.
And the server matches the extracted characteristic parameters with the aging characteristic data of the corresponding elements in the database corresponding to the air conditioner model, and the aging degree of each element of the air conditioner is obtained through matching.
Optionally, the step S1042 performs redundancy removal on the channel state information to obtain the preprocessed information, which specifically includes the following steps:
step S10421, performing convolution processing on data in each pair of channels in the channel state information through a low-pass filter to obtain denoised data.
In one alternative, the low pass filter may be a hamming window low pass filter.
In the above step, a hamming window low-pass filter is used to convolute the data in the channel link between every two antennas in a series of channel state information data streams, and a preliminary denoising process is performed.
And S10422, performing dimensionality reduction on the de-noised data through a dimensionality reduction algorithm to obtain preprocessing information.
In an alternative, the dimension reduction algorithm may be a principal component analysis algorithm.
For data with more dimensions, the first thing to do is to reduce the dimensions of the data while ensuring the essence of the data as much as possible. Principal Component Analysis (PCA) algorithms synthesize high-dimensional variables that may have correlations into linearly independent low-dimensional variables, and the new low-dimensional data set preserves the variables of the original data as much as possible.
The dimensionality reduction can be carried out on the de-noised data through a principal component analysis method, and the purpose of removing redundant data is further achieved.
Optionally, the feature parameters include a first feature parameter and a second feature parameter, and the step S1043 performs feature extraction on the preprocessed information to obtain the feature parameters, which may specifically include the following steps:
step S10431, performing frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram.
Step S10432, extracting a wavelet coefficient of each frequency band in the spectrogram as a first characteristic parameter.
In the above steps, frequency analysis is performed on the preprocessed information within a period of time through discrete wavelet transform to obtain a plurality of frequency bands, and then wavelet coefficients of each frequency band are extracted to serve as first characteristic parameters.
In step S10433, the upper cut-off frequency and the center frequency at each sampling time in the spectrogram are estimated as second characteristic parameters.
In one alternative, the upper cut-off frequency and the center frequency may be estimated using a percentage algorithm.
The Percentiles algorithm operates on a spectrogram of the motion, estimating an upper (upper) cutoff frequency and a center (center) frequency at each sampling instant.
Optionally, after the step S104 is executed to determine the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information, the method of this embodiment may further include:
and step S105, sending the aging information to the prompting equipment.
In an alternative, the prompt device may be a mobile terminal of a user, or may be a display panel of an electrical appliance where the wireless network device is located.
After determining the aging information of each element in the electrical appliance, the server sends the aging information to a main controller of the electrical appliance through the wireless network equipment, and the main controller controls a display panel to display the aging information or triggers a mobile terminal of a user to inform the user of the aging information of each element.
In the above embodiment, the electrical appliance information and the channel state information of the electrical appliance accessing the wireless network device are obtained, wherein the channel state information is extracted from the wireless network signal of the electrical appliance by the wireless network device; and determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information. Compared with the prior art, the scheme adopts the wireless network equipment with the channel state information detection function, and determines the aging degree of each component in the electric appliance by extracting the channel state information in the wireless network signal of the electric appliance and utilizing the change of the channel state information; by establishing a database of different electrical appliance information, the aging information of the corresponding element can be conveniently inquired; and aging characteristic data can be conveniently inquired by performing redundancy removal processing, characteristic extraction and other operations on the channel state information. The invention not only can clarify the aging information of the electric appliance, but also can realize the self-checking of the electric appliance, avoid the abnormal work of the electric appliance, enhance the use safety of the electric appliance, and improve the user experience, thereby solving the technical problem that the utilization rate of wireless network equipment is not high because the wireless network equipment in the related technology is only used for communication interaction.
Example 2
According to an embodiment of the present invention, there is provided an embodiment of a detection method from the perspective of a wireless network device, and fig. 4 is a detection method according to an embodiment of the present invention, as shown in fig. 4, the method includes the following steps:
and step S402, acquiring wireless network signals of the electric appliance.
In an alternative, the electrical appliance may be any electrical appliance having a wireless network device, such as an intelligent air conditioner, an intelligent sound box, an intelligent television, and the like; the device for acquiring the wireless network signal may be a WiFi module, and the WiFi module may be configured in an electrical appliance and configured to receive and transmit a signal.
Step S404, extracting channel state information in the wireless network signal.
Because a small change in the environment may generate a certain interference on a received waveform of the wireless network device, a radio wave transmitted by a transmitter (e.g., a router) propagates through multiple paths such as direct radiation, reflection, and scattering, and a multipath superimposed signal formed at a signal receiver (e.g., a wireless network device) may reflect a change in the environment.
The Channel State Information (CSI) belongs to fine-grained Information of a Physical Layer (PHY), and can measure the phase and amplitude of each subcarrier, so that the subcarrier Information is displayed more abundantly, and the multipath resolution capability is displayed to a certain extent, and particularly, small changes of signals are sensed in a non-line-of-sight range, and therefore, the CSI has the characteristics of high sensitivity, wide sensing area and the like. The invention just considers the factors and senses the tiny change of each component element in the electric appliance by extracting the channel state information in the wireless network signal.
In the above steps, after the wireless network device acquires the wireless network signals which are directly transmitted, reflected and scattered by the electric appliance, the wireless network device firstly extracts the channel state information therein through a software tool, namely, extracts the information on the subcarrier waveform in the WIFI channel.
And step S406, uploading the channel state information and the electrical appliance information of the electrical appliance to a server, wherein the server determines the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information.
In an alternative, the aging information may be the aging degree, aging speed, etc. of each component in the electrical appliance, and the aging degree may be expressed in percentage form, for example, the aging degree of the compressor is 60%, the aging degree of the evaporator is 30%, etc.; the server can be a cloud server or a local server. In the case of a local server, may be located in the appliance.
In an optional embodiment, the server performs preprocessing on the channel state information uploaded by the wireless network device, such as filtering, removing outliers, extracting feature values, and the like, and then identifies the processed information through a preset algorithm corresponding to the electrical appliance information to determine aging information of each element.
In another optional embodiment, the server performs preprocessing on the channel state information and the electrical appliance information uploaded by the wireless network device, such as filtering, abnormal point removal, characteristic value extraction and the like, and finally identifies the processed information through algorithms such as a neural network and the like to determine the aging information of each element.
Optionally, before the step 402 of acquiring the wireless network signal of the electrical appliance is executed, the method of this embodiment may further include:
step S401, a database of different electrical appliance information is established through a server, wherein aging characteristic data of each element is prestored in the database.
Since the different types and models of electrical appliances may have different components, before implementing the method of the embodiment, the server first establishes databases of different electrical appliance information, and each database prestores aging characteristic data of the components having the same electrical appliance information.
Optionally, the step S406 of determining, by the server, the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information may specifically include the following steps:
step S4061, the target database is determined according to the electrical appliance information.
Step S4062, the channel state information is processed for redundancy elimination to obtain the preprocessing information.
Step S4063, extracting the characteristics of the preprocessed information to obtain characteristic parameters.
In an alternative, the characteristic parameter may be a characteristic parameter of a compressor, a characteristic parameter of an evaporator, a characteristic parameter of a condenser, a characteristic parameter of a panel, or the like.
Step S4064, the characteristic parameters are matched with aging characteristic data in the target database to obtain aging information.
And the server matches the extracted characteristic parameters with the aging characteristic data of the corresponding elements in the database corresponding to the air conditioner model, and the aging degree of each element of the air conditioner is obtained through matching.
Optionally, in step S4062, performing redundancy removal processing on the channel state information to obtain the preprocessed information, which may specifically include the following steps:
step S40621, performing convolution processing on data in each two channels in the channel state information through a low-pass filter to obtain de-noising data.
In one alternative, the low pass filter may be a hamming window low pass filter.
In the above step, a hamming window low-pass filter is used to convolute the data in the channel link between every two antennas in a series of channel state information data streams, and a preliminary denoising process is performed.
Step S40622, the denoising data is subjected to dimensionality reduction through a dimensionality reduction algorithm to obtain preprocessing information.
In an alternative, the dimension reduction algorithm may be a principal component analysis algorithm.
For data with more dimensions, the first thing to do is to reduce the dimensions of the data while ensuring the essence of the data as much as possible. Principal Component Analysis (PCA) algorithms synthesize high-dimensional variables that may have correlations into linearly independent low-dimensional variables, and the new low-dimensional data set preserves the variables of the original data as much as possible.
The dimensionality reduction can be carried out on the de-noised data through a principal component analysis method, and the purpose of removing redundant data is further achieved.
Optionally, the feature parameters include a first feature parameter and a second feature parameter, and step S4063 performs feature extraction on the preprocessed information to obtain the feature parameters, which may specifically include the following steps:
step S40631, frequency analysis is performed on the preprocessed information through discrete wavelet transform to obtain a spectrogram.
Step S40632 is performed to extract the wavelet coefficient of each frequency band in the spectrogram as the first characteristic parameter.
In the above steps, frequency analysis is performed on the preprocessed information within a period of time through discrete wavelet transform to obtain a plurality of frequency bands, and then wavelet coefficients of each frequency band are extracted to serve as first characteristic parameters.
Step S40633, estimating an upper cut-off frequency and a center frequency of each sampling time in the spectrogram, as second characteristic parameters.
In one alternative, the upper cut-off frequency and the center frequency may be estimated using a percentage algorithm.
The Percentiles algorithm operates on a spectrogram of the motion, estimating an upper (upper) cutoff frequency and a center (center) frequency at each sampling instant.
Optionally, after determining the aging information of each element in the appliance according to the appliance information and the channel state information in step S406, the method of this embodiment may further include:
step S407, the server sends the aging information to the prompting device.
In an alternative, the prompt device may be a mobile terminal of a user, or may be a display panel of an electrical appliance where the wireless network device is located.
After determining the aging information of each element in the electrical appliance, the server sends the aging information to a main controller of the electrical appliance through the wireless network equipment, and the main controller controls a display panel to display the aging information or triggers a mobile terminal of a user to inform the user of the aging information of each element.
It should be noted that, in the above example 2 of the present application, the preferred embodiment is the same as the scheme and application scenario implementation process provided in example 1, but is not limited to the scheme provided in example 1.
Example 3
According to an embodiment of the present invention, a detection apparatus is provided, and fig. 5 is a schematic diagram of the detection apparatus according to the embodiment of the present application. As shown in fig. 5, the apparatus 500 includes a first obtaining module 502 and a determining module 504.
The acquiring module 502 is configured to acquire electrical appliance information and channel state information of an electrical appliance accessed to the wireless network device, where the channel state information is extracted from a wireless network signal of the electrical appliance by the wireless network device; and the determining module 504 is configured to determine aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information.
Optionally, the apparatus may further include: the establishing module is used for establishing a database of different electrical appliance information before acquiring the electrical appliance information and the channel state information of the electrical appliance accessed to the wireless network equipment, wherein the database is prestored with aging characteristic data of each element.
Optionally, the determining module may include: the determining submodule is used for determining a target database according to the electrical appliance information; the preprocessing module is used for performing redundancy removal processing on the channel state information to obtain preprocessed information; the characteristic extraction module is used for extracting the characteristics of the preprocessed information to obtain characteristic parameters; and the matching module is used for matching the characteristic parameters with the aging characteristic data in the target database to obtain the aging information.
Optionally, the pre-processing module comprises: the convolution module is used for performing convolution processing on data in each two channels in the channel state information through the low-pass filter to obtain de-noising data; and the dimension reduction module is used for carrying out dimension reduction processing on the de-noising data through a dimension reduction algorithm to obtain preprocessing information.
Optionally, the feature parameters include a first feature parameter and a second feature parameter, and the feature extraction module includes: the analysis module is used for carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; the first extraction sub-module is used for extracting a wavelet coefficient of each frequency band in the spectrogram as a first characteristic parameter; and the second extraction module is used for estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as second characteristic parameters.
Optionally, the apparatus may further include: and the sending module is used for sending the aging information to the prompting equipment after determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information.
It should be noted that the first obtaining module 502 and the determining module 504 correspond to steps S102 to S104 in embodiment 1, and the two modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of embodiment 1.
Example 4
According to an embodiment of the present invention, a detection apparatus is provided, and fig. 6 is a schematic diagram of the detection apparatus according to the embodiment of the present application. As shown in fig. 6, the apparatus 600 includes a second obtaining module 602, an extracting module 604, and an uploading module 606.
The second obtaining module 602 is configured to obtain a wireless network signal of an electrical appliance; an extracting module 604, configured to extract channel state information in a wireless network signal; and an uploading module 606, configured to upload the channel state information and the electrical appliance information of the electrical appliance to a server, where the server determines aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information.
Optionally, the apparatus may further include: the establishing module is used for establishing a database of different electric appliance information before acquiring wireless network signals of the electric appliances, wherein the database is prestored with aging characteristic data of each element.
Optionally, the server may include: the determining submodule is used for determining a target database according to the electrical appliance information; the preprocessing module is used for performing redundancy removal processing on the channel state information to obtain preprocessed information; the characteristic extraction module is used for extracting the characteristics of the preprocessed information to obtain characteristic parameters; and the matching module is used for matching the characteristic parameters with the aging characteristic data in the target database to obtain the aging information.
Optionally, the pre-processing module comprises: the convolution module is used for performing convolution processing on data in each two channels in the channel state information through the low-pass filter to obtain de-noising data; and the dimension reduction module is used for carrying out dimension reduction processing on the de-noising data through a dimension reduction algorithm to obtain preprocessing information.
Optionally, the feature parameters include a first feature parameter and a second feature parameter, and the feature extraction module includes: the analysis module is used for carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; the first extraction sub-module is used for extracting a wavelet coefficient of each frequency band in the spectrogram as a first characteristic parameter; and the second extraction module is used for estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as second characteristic parameters.
Optionally, the server may further include: and the sending module is used for sending the aging information to the prompting equipment after determining the aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information.
It should be noted that the second obtaining module 602, the extracting module 604 and the uploading module 606 correspond to steps S402 to S406 in embodiment 2, and the three modules are the same as the corresponding steps in the implementation example and the application scenario, but are not limited to the disclosure in embodiment 2.
Example 5
According to an embodiment of the present invention, there is provided a storage medium including a stored program, wherein a device in which the storage medium is located is controlled to execute the detection method in embodiment 1 or 2 when the program runs.
Example 6
According to an embodiment of the present invention, there is provided a processor configured to run a program, wherein the detection method in embodiment 1 or 2 is performed when the program is running.
Example 7
According to an embodiment of the present invention, there is provided a detection system including:
the wireless network equipment is used for acquiring a wireless network signal of the electric appliance, extracting channel state information in the wireless network signal and uploading the channel state information and the electric appliance information of the electric appliance to the server; and the server is used for determining the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information.
Further, the server or the wireless network device may also execute the instructions of the other steps in embodiment 1 or 2, which are not described herein again.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method of detection, comprising:
acquiring electrical appliance information and channel state information of an electrical appliance accessed to wireless network equipment, wherein the electrical appliance information is the model of the electrical appliance, and the channel state information is extracted from a wireless network signal of the electrical appliance by the wireless network equipment;
determining aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information;
determining aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information, wherein the determining comprises the following steps: determining a target database according to the electrical appliance information; performing redundancy removal processing on the channel state information to obtain preprocessing information; extracting the characteristics of the preprocessed information to obtain characteristic parameters; matching the characteristic parameters with aging characteristic data in the target database to obtain the aging information;
the characteristic parameters include a first characteristic parameter and a second characteristic parameter, and the characteristic extraction is performed on the preprocessed information to obtain the characteristic parameters, which includes: carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; extracting a wavelet coefficient of each frequency band in the spectrogram to serve as the first characteristic parameter; and estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as the second characteristic parameters.
2. The method of claim 1, wherein before obtaining appliance information and channel state information of an appliance accessing a wireless network device, the method further comprises:
and establishing a database of different electrical appliance information, wherein the database is prestored with aging characteristic data of each element.
3. The method of claim 1, wherein performing de-redundancy processing on the channel state information to obtain pre-processed information comprises:
performing convolution processing on data in each two channels in the channel state information through a low-pass filter to obtain de-noising data;
and carrying out dimension reduction processing on the de-noising data through a dimension reduction algorithm to obtain the preprocessing information.
4. The method of claim 1, wherein after determining aging information of components in the appliance according to the appliance information and the channel state information, the method further comprises:
and sending the aging information to a prompt device.
5. A method of detection, comprising:
acquiring a wireless network signal of an electric appliance;
extracting channel state information in the wireless network signal;
uploading the channel state information and the electrical appliance information of the electrical appliance to a server, wherein the electrical appliance information is the model of the electrical appliance, and the server determines the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information, and the method comprises the following steps: determining a target database according to the electrical appliance information; performing redundancy removal processing on the channel state information to obtain preprocessing information; extracting the characteristics of the preprocessed information to obtain characteristic parameters; matching the characteristic parameters with aging characteristic data in the target database to obtain the aging information;
the characteristic parameters include a first characteristic parameter and a second characteristic parameter, and the characteristic extraction is performed on the preprocessed information to obtain the characteristic parameters, which includes: carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; extracting a wavelet coefficient of each frequency band in the spectrogram to serve as the first characteristic parameter; and estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as the second characteristic parameters.
6. A detection device, comprising:
the system comprises a first acquisition module, a first processing module and a second processing module, wherein the first acquisition module is used for acquiring the electric appliance information and the channel state information of an electric appliance accessed to wireless network equipment, the electric appliance information is the type of the electric appliance, and the channel state information is extracted from a wireless network signal of the electric appliance by the wireless network equipment;
a determining module for determining aging information of each element in the electrical appliance according to the electrical appliance information and the channel state information
Wherein the determining module comprises: the determining submodule is used for determining a target database according to the electrical appliance information; the preprocessing module is used for performing redundancy removal processing on the channel state information to obtain preprocessed information; the characteristic extraction module is used for extracting the characteristics of the preprocessed information to obtain characteristic parameters; the matching module is used for matching the characteristic parameters with aging characteristic data in the target database to obtain the aging information;
wherein the feature parameters include a first feature parameter and a second feature parameter, and the feature extraction module includes: the analysis module is used for carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; the first extraction sub-module is used for extracting the wavelet coefficient of each frequency band in the spectrogram to serve as the first characteristic parameter; and the second extraction module is used for estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as the second characteristic parameters.
7. A detection device, comprising:
the second acquisition module is used for acquiring wireless network signals of the electric appliance;
the extraction module is used for extracting the channel state information in the wireless network signal;
the uploading module is used for uploading the channel state information and the electrical appliance information of the electrical appliance to a server, wherein the electrical appliance information is the model of the electrical appliance, and the server determines the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information;
wherein the server comprises: the determining submodule is used for determining a target database according to the electrical appliance information; the preprocessing module is used for performing redundancy removal processing on the channel state information to obtain preprocessed information; the characteristic extraction module is used for extracting the characteristics of the preprocessed information to obtain characteristic parameters; the matching module is used for matching the characteristic parameters with aging characteristic data in the target database to obtain the aging information;
wherein the feature parameters include a first feature parameter and a second feature parameter, and the feature extraction module includes: the analysis module is used for carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; the first extraction sub-module is used for extracting the wavelet coefficient of each frequency band in the spectrogram to serve as the first characteristic parameter; and the second extraction module is used for estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as the second characteristic parameters.
8. A storage medium, characterized in that the storage medium comprises a stored program, wherein a device in which the storage medium is located is controlled to execute the detection method according to claim 1 or 5 when the program runs.
9. A processor for running a program, wherein the program is run to perform the detection method of claim 1 or 5.
10. A detection system, comprising:
the wireless network equipment is used for acquiring a wireless network signal of an electric appliance, extracting channel state information in the wireless network signal and uploading the channel state information and electric appliance information of the electric appliance to a server, wherein the electric appliance information is the model of the electric appliance;
the server is used for determining the aging information of each element in the electrical appliance according to the channel state information and the electrical appliance information;
wherein the server comprises: the determining submodule is used for determining a target database according to the electrical appliance information; the preprocessing module is used for performing redundancy removal processing on the channel state information to obtain preprocessed information; the characteristic extraction module is used for extracting the characteristics of the preprocessed information to obtain characteristic parameters; the matching module is used for matching the characteristic parameters with aging characteristic data in the target database to obtain the aging information;
wherein the feature parameters include a first feature parameter and a second feature parameter, and the feature extraction module includes: the analysis module is used for carrying out frequency analysis on the preprocessed information through discrete wavelet transform to obtain a spectrogram; the first extraction sub-module is used for extracting the wavelet coefficient of each frequency band in the spectrogram to serve as the first characteristic parameter; and the second extraction module is used for estimating the upper limit cut-off frequency and the central frequency of each sampling moment in the spectrogram as the second characteristic parameters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910649583.3A CN110365429B (en) | 2019-07-18 | 2019-07-18 | Detection method, device and system, storage medium and processor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910649583.3A CN110365429B (en) | 2019-07-18 | 2019-07-18 | Detection method, device and system, storage medium and processor |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110365429A CN110365429A (en) | 2019-10-22 |
| CN110365429B true CN110365429B (en) | 2020-09-25 |
Family
ID=68220519
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910649583.3A Active CN110365429B (en) | 2019-07-18 | 2019-07-18 | Detection method, device and system, storage medium and processor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110365429B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103596266A (en) * | 2013-11-26 | 2014-02-19 | 无锡市中安捷联科技有限公司 | Method, device and system for detecting and locating human body |
| CN106448652A (en) * | 2016-09-12 | 2017-02-22 | 珠海格力电器股份有限公司 | Control method and device for air-conditioner |
| CN107331136A (en) * | 2017-05-11 | 2017-11-07 | 深圳市斑点猫信息技术有限公司 | Indoor human body activity detection approach and system based on WiFi |
| CN108198558A (en) * | 2017-12-28 | 2018-06-22 | 电子科技大学 | A kind of audio recognition method based on CSI data |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105337718B (en) * | 2010-01-12 | 2018-09-14 | 爱立信(中国)通信有限公司 | Method and apparatus for channel estimation in mimo system and detection |
| KR101901434B1 (en) * | 2011-09-23 | 2018-09-27 | 삼성전자 주식회사 | Method and apparatus for transmitting and receiving feedback for cooperative communication system |
| CN104615244A (en) * | 2015-01-23 | 2015-05-13 | 深圳大学 | Automatic gesture recognizing method and system |
| CN106198868A (en) * | 2016-07-05 | 2016-12-07 | 深圳大学 | The method and system of Humidity Detection based on wireless aware |
-
2019
- 2019-07-18 CN CN201910649583.3A patent/CN110365429B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103596266A (en) * | 2013-11-26 | 2014-02-19 | 无锡市中安捷联科技有限公司 | Method, device and system for detecting and locating human body |
| CN106448652A (en) * | 2016-09-12 | 2017-02-22 | 珠海格力电器股份有限公司 | Control method and device for air-conditioner |
| CN107331136A (en) * | 2017-05-11 | 2017-11-07 | 深圳市斑点猫信息技术有限公司 | Indoor human body activity detection approach and system based on WiFi |
| CN108198558A (en) * | 2017-12-28 | 2018-06-22 | 电子科技大学 | A kind of audio recognition method based on CSI data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110365429A (en) | 2019-10-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107968689B (en) | Perception identification method and device based on wireless communication signals | |
| EP3340243B1 (en) | Method for performing voice control on device with microphone array, and device thereof | |
| CN107991891B (en) | Method and system for adjusting environmental parameters and user equipment | |
| US11913970B2 (en) | Wireless motion detection using multiband filters | |
| CN110647894B (en) | Fault diagnosis method and system of electrical equipment, cloud server and storage medium | |
| CN110109899B (en) | Internet of things data filling method, device and system | |
| KR20210020913A (en) | Recognition of gestures based on wireless signals | |
| CN113543010B (en) | Detection method and device for microphone equipment, storage medium and processor | |
| CN110974189A (en) | Method, device, equipment and system for detecting signal quality of pulse wave | |
| CN109298847A (en) | The adjusting method and device of volume, system | |
| CN110365429B (en) | Detection method, device and system, storage medium and processor | |
| CN112751629A (en) | Broadband specific signal detection method based on time-frequency image processing | |
| CN109951804A (en) | A kind of stream of people's amount estimation method and device | |
| CN112926555B (en) | Small sample passive behavior sensing method based on self-encoder data enhancement | |
| CN109945412A (en) | A kind of remote control equipment and its control method, device and storage medium | |
| CN111722600A (en) | Remote control method and device based on equipment space relation and remote control equipment | |
| CN110996289A (en) | Intelligent gateway, method and system for machine state monitoring diagnostic instrument | |
| US10044384B2 (en) | Data transmission terminal, data transmission/reception system and data transmission method | |
| CN109745026A (en) | A kind of method for measuring heart rate and system | |
| CN112927705B (en) | Frequency response calibration method and related product | |
| CN115687924A (en) | Model training method and device, electronic equipment and storage medium | |
| CN116266928A (en) | Sensing method, sensing device and communication equipment | |
| CN110516566B (en) | Filtering method and device based on convolutional layer | |
| CN102938823B (en) | Image processing equipment and image processing method | |
| TWI609193B (en) | Method and apparatus for space status detection based on acoustic chirp signals |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |