CN114166491A - Target equipment fault monitoring method and device, electronic equipment and medium - Google Patents
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Abstract
The application discloses a target equipment fault monitoring method, a device, electronic equipment and a medium, wherein the target equipment fault monitoring method comprises the following steps: collecting an environmental noise signal of target equipment in real time; acquiring a current unit time steady-state noise sound pressure level of target equipment based on a current unit time environment noise signal of the target equipment; judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, if so, judging that the target equipment is in an abnormal state; the method obtains the steady-state noise of the target equipment based on the environmental noise signal of the target equipment, and can effectively avoid the interference of intermittent noise in the environment on the equipment noise, thereby improving the equipment noise monitoring accuracy, improving the equipment fault identification precision and the identification real-time performance, and effectively reducing the probability of missed report and false report.
Description
Technical Field
The present disclosure relates to the field of fault monitoring technologies, and in particular, to a method and an apparatus for monitoring a fault of a target device, an electronic device, and a medium.
Background
Noise pollution and water pollution, atmospheric pollution and solid waste are recognized as four major pollutants in the world today. The noise problem becomes a serious environmental problem and seriously harms the physical and mental health of people, so that the enhancement of noise control and the reduction of noise pollution become matters which are not slow.
The transformer substation is a power transmission and distribution aggregation point and is a main heart of a power transmission system, the components mainly comprise a power transformer, a reactor, a feeder line, a bus, a switch device, a lightning rod and other devices, most of the devices generate noise during operation, the noise of the devices is superposed together to be a noise source in the high-voltage transformer substation, and the noise is likely to be increased due to abnormal operation of the internal devices. With the improvement of social laws and regulations and the continuous improvement of environmental awareness of people, the complaint events of transformer substation noise disturbing residents are increased rapidly, so that the transformer substation noise monitoring is not slow.
The environment noise signal actually acquired at the transformer substation contains relatively stable transformer substation equipment noise and intermittent noise such as automobile whistling, passerby speaking voice, bird singing and the like, and the abnormal transformer substation noise means that the abnormal transformer substation equipment noise causes continuous abnormal transformer substation noise.
The noise monitoring of the existing transformer substation is measured during manual inspection, and has the defects of poor timeliness, short observation time and the like.
The published Chinese patent CN113252165A adopts noise detection equipment to collect substation noise, and sets a threshold range according to the background noise of the substation under the condition that the substation does not work, and when the noise of the substation is within the threshold range, the noise is considered to be normal, and when the noise value exceeds the threshold range, the noise is considered to be abnormal and an alarm is given out. Although the method can detect the noise of the substation in real time, the detected noise not only comprises equipment noise, but also comprises intermittent noise such as surrounding automobile whistling, passerby speaking voice, bird singing and the like, the method has poor anti-interference capability for the intermittent noise, and the intermittent noise possibly causes abnormal false alarm of the noise caused by the fault of the substation.
Therefore, a method for accurately detecting the noise of the substation equipment is needed.
Content of application
The application aims to provide a target equipment fault monitoring method, a target equipment fault monitoring device, electronic equipment and a target equipment fault monitoring medium, which can accurately detect equipment noise in real time, so that accurate monitoring of equipment faults is realized.
In order to achieve the purpose of the application, the application provides the following technical scheme:
in one aspect, a target device fault monitoring method is provided, where the target device fault monitoring method includes:
collecting an environmental noise signal of target equipment in real time;
acquiring a current unit time steady-state noise sound pressure level of the target device based on a current unit time environment noise signal of the target device;
and judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, if so, judging that the target equipment is in an abnormal state.
In a preferred embodiment, the obtaining the current steady-state noise sound pressure level per unit time of the target device based on the current ambient noise signal per unit time of the target device includes:
obtaining a current unit time noise spectrum estimation value of the target equipment through noise spectrum estimation based on the current unit time environment noise signal of the target equipment and the noise spectrum estimation value of the target equipment in the last unit time;
and obtaining the current steady-state noise sound pressure level of the target equipment in unit time based on the current noise spectrum estimation value of the target equipment in unit time.
In a preferred embodiment, the obtaining the current time unit noise spectrum estimation value of the target device through noise spectrum estimation based on the current time unit environment noise signal of the target device and the noise spectrum estimation value of the target device at the last time unit comprises:
obtaining corresponding environmental noise power density through fast Fourier transform based on the current unit time environmental noise signal of the target device;
windowing the environmental noise power spectral density and searching the minimum value of the environmental noise power spectral density in the current unit time window length;
judging the existence probability of intermittent noise in the current unit time based on the minimum value of the power spectral density of the environmental noise in the current unit time window length;
and obtaining the current unit time noise spectrum estimated value of the target equipment based on the existence probability of the intermittent noise, the noise spectrum estimated value of the target equipment in the last unit time and the environmental noise power density.
In a preferred embodiment, the windowing the environmental noise power spectral density and searching for a minimum value of the environmental noise power spectral density within a current time unit window length includes:
performing frequency domain sliding on the environmental noise power spectral density windowing to obtain a first smooth power spectral density;
performing time domain smoothing based on the first smoothed power spectral density to obtain a noise smoothed power spectral density;
and searching the minimum power density in any window length of the noise smoothing power density as the minimum value of the environmental noise power spectral density in the corresponding current unit time window length.
In a preferred embodiment, the determining the existence probability of intermittent noise per unit time based on the power spectral density minimum value within the current time window length includes:
calculating a ratio of the first smoothed power spectral density to the minimum value of the ambient noise power spectral density;
judging whether the ratio exceeds a second preset threshold value or not, if so, determining that the existence probability of intermittent noise in the current unit time is 1; if not, the existence probability of the intermittent noise in the current unit time is 0.
In a preferred embodiment, the obtaining a current noise spectrum estimation value per unit time of the target device based on the existence probability of the intermittent noise, the noise spectrum estimation value of the target device per unit time and the environmental noise power density comprises:
smoothing the existence probability of intermittent noise in the current unit time in time and calculating a recursive average factor;
and obtaining the current unit time noise spectrum estimated value of the target equipment based on the recursive average factor, the noise spectrum estimated value of the target equipment in the last unit time and the environmental noise power density.
In a second aspect, there is also provided a target device fault monitoring apparatus, the apparatus comprising:
the acquisition module is used for acquiring an environmental noise signal of the target equipment in real time;
the processing module is used for acquiring the current steady-state noise sound pressure level of the target equipment in unit time based on the current ambient noise signal of the target equipment in unit time;
and the judging module is used for judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, and if so, the target equipment is in an abnormal state.
In a preferred embodiment, the processing module comprises:
a first processing unit, configured to obtain a current unit-time noise spectrum estimation value of the target device through noise spectrum estimation based on a current unit-time environment noise signal of the target device and a noise spectrum estimation value of a previous unit-time target device;
and the second processing unit is used for obtaining the current steady-state noise sound pressure level of the target equipment in unit time based on the current noise spectrum estimation value of the target equipment in unit time.
In a third aspect, an electronic device is provided, including:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the processors to implement the steps of the method of any of the first aspects.
In a fourth aspect, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by one or more processors, performs the steps of the method according to any one of the first aspect.
Compared with the prior art, the method has the following beneficial effects:
the application provides a target equipment fault monitoring method, a device, electronic equipment and a medium, wherein the target equipment fault monitoring method comprises the following steps: collecting an environmental noise signal of target equipment in real time; acquiring a current unit time steady-state noise sound pressure level of target equipment based on a current unit time environment noise signal of the target equipment; judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, if so, judging that the target equipment is in an abnormal state; the method obtains the steady-state noise of the target equipment based on the environmental noise signal of the target equipment, and can effectively avoid the interference of intermittent noise in the environment on the equipment noise, thereby improving the equipment noise monitoring accuracy, improving the equipment fault identification precision and the identification real-time performance, and effectively reducing the probability of missing report and false report;
further, when the steady-state noise sound pressure level of the target device in the current unit time is obtained based on the current unit time environment noise signal of the target device, the noise spectrum estimation value of the target device in the previous unit time and the current unit time environment noise signal are used for carrying out noise spectrum estimation in the current unit time, the steady-state noise sound pressure level in the current unit time is effectively improved in an iterative calculation mode to be self-adaptively adjusted so as to improve the calculation accuracy, and the device noise monitoring accuracy is further improved.
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Fig. 1 is a flowchart of a target device fault monitoring method in the present embodiment;
fig. 2 is a schematic structural diagram of a target device fault monitoring apparatus in the present embodiment;
fig. 3 is a schematic structural diagram of the computer-readable storage medium in this embodiment.
Detailed Description
In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the description of the present application, it is to be understood that the terms "first", "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present application, "a plurality" means two or more unless otherwise specified.
In view of the fact that when the fault of the substation equipment is monitored in real time by monitoring the noise of the substation, the monitoring precision of the noise of the substation equipment is always affected by the interference of intermittent noise such as surrounding automobile whistling, passerby speaking voice, bird singing and the like, and faults such as missing report, false report and the like are caused, the embodiment provides the fault monitoring method, the device, the electronic equipment and the medium for the target equipment, the problem can be effectively solved, and the accuracy rate of equipment abnormity identification is improved.
The method, apparatus, electronic device and system for monitoring the fault of the target device in this embodiment will be described in further detail with reference to fig. 1-2.
Examples
As shown in fig. 1, the present embodiment provides a target device fault monitoring method, including the following steps:
and S1, collecting the environmental noise signal of the target equipment in real time.
In this embodiment, at least one noise signal acquisition device is arranged in a preset distance range around the target device to acquire the environmental noise signal in real time. In this embodiment, the target device includes, but is not limited to, a substation related device, a factory production related device, and the like.
It should be noted that the environmental noise signal collected in step S1 includes target device noise (noise generated during operation of the target device), and intermittent noise such as car whistling, road speaker, bird song, etc. around the environment, and this embodiment is just to filter the intermittent noise in the environmental noise signal to obtain the target device noise.
And S2, acquiring the current steady-state noise sound pressure level of the target device in unit time based on the current ambient noise signal in unit time of the target device.
Note that the steady-state noise of the target device refers to the target device noise.
And when the method is executed, the unit time length depends on the monitoring precision requirement, and the unit time length is 1 frame in the embodiment, so that the current unit time is the current frame, and the last unit time is the last frame.
Specifically, the step S2 includes:
and S21, obtaining the current frame noise spectrum estimated value of the target device through noise spectrum estimation based on the current frame environment noise signal of the target device and the noise spectrum estimated value of the target device in the previous frame.
It should be noted that, in the present embodiment, a minimum control recursive average algorithm is used to perform noise spectrum estimation.
Further, step S21 includes:
s211, obtaining corresponding environment noise power density Y (k, lambda) through fast Fourier transform based on current frame environment noise signals of target equipment2。
S212, windowing the power spectral density of the environmental noise and searching the minimum value of the power spectral density of the environmental noise in the current frame window length.
Specifically, S212 includes:
performing frequency domain sliding on the environmental noise power spectral density windowing to obtain a first smooth power spectral density S of the current framef(k, λ). Smoothing the frequency domain to obtain Sf(k, λ) is specifically represented by formula (1):
wherein w (i) is a window function, and the window length is 2Lω-1, k denotes the k-th frequency bin and λ denotes the current frame.
Time domain smoothing is performed based on the first smoothed power spectral density to obtain a noise smoothed power spectral density S (k, λ).
The time domain smoothing obtains S (k, λ) as shown in formula (2):
S(k，λ)＝αsS(k，λ-1)+(1-αs)Sf(k，λ) (2)
in the formula of alphasFor the temporal smoothing factor, λ -1 represents the last frame.
Preferably, α in the present embodiment is calculated for convenience of calculations0.8 is taken.
Searching the minimum power density in any window length of the noise smooth power density as the minimum value S of the power spectrum density of the environmental noise in the corresponding current frame window lengthmin(k,λ)。
Specifically, S is found by searching within any window length according to the following formula (3)min(k,λ)：
Smin(k，λ)＝min{S(k，λ)，S(k，λ-1)，…S(k，λD+1)} (3)。
S213, judging the existence probability of intermittent noise in the current frame based on the minimum value of the power spectral density of the environmental noise in the current frame window length.
Specifically, step S213 includes:
first, a ratio S of a first smoothed power spectral density to a minimum value of an ambient noise power spectral density is calculatedr(k, λ), see in particular the following formula (4):
then, judging whether the ratio exceeds a second preset threshold value delta or not, if so, determining that the existence probability p (k, lambda) of intermittent noise in the current frame is 1; if not, the existence probability p (k, lambda) of intermittent noise in the current frame is 0. Preferably, for the convenience of calculation, the second preset threshold δ is 5.
An exemplary calculation process is shown in equation (5) below:
s214, obtaining a current frame noise spectrum estimated value of the target device based on the existence probability of the intermittent noise, the noise spectrum estimated value of the target device in the previous frame and the environmental noise power density.
Specifically, step S214 includes:
firstly, smoothing the existence probability of intermittent noise in the current frame in time and calculating a recursive average factor alphad(k, λ). Specifically, the following formulae (6) and (7) are shown below:
in the formula
For the existence probability, alpha, of intermittent noise in the smoothed current framepIs 0.2.
αd(k，λ)＝α+(1-α)p(k，λ) (7)
Wherein alpha is 0.95.
Therefore, combining equations (5) and (7), it can be seen that the difference in the determination result of the existence probability p (k, λ) of intermittent noise in the current frame leads to the calculation of the recursive average factor αdAnd the values of (k and lambda) are different, so that the signal-to-noise ratio (SNR) is adaptively adjusted, and the noise monitoring accuracy of the target equipment is improved.
Then, based on the recursive average factor αd(k, λ), noise spectrum estimate of last frame target device
And ambient noise power density Y (k, λ) converter2Obtaining the current frame noise spectrum estimated value of the target device
In particular, the method comprises the following steps of,
the calculation formula is shown in the following formula (8):
s22, estimating the noise spectrum of the current frame based on the target equipment
The current frame steady-state noise sound pressure level SPL (λ) of the target device is obtained.
The present embodiment does not limit the method for calculating the steady-state noise sound pressure level of the current frame of the target device, and for example, the method may be calculated by the following formula (9):
where nfft is the length and frame length of the fourier transform.
And S3, judging whether the steady-state noise sound pressure level of the current frame of the target equipment exceeds a first preset threshold value, if so, determining that the target equipment is in an abnormal state.
Generally, the first preset threshold is an equipment noise experience value when the target equipment fails, and illustratively, when the target equipment is substation equipment, the first preset threshold is 50dB to 70 dB.
Of course, the device noise monitoring method further includes:
and S4, when the target equipment is judged to be in an abnormal state, alarming to a background.
In summary, the present embodiment provides a target device fault monitoring method, which obtains a steady-state noise of a target device based on an environmental noise signal of the target device, and can effectively avoid interference of intermittent noise in an environment on the device noise, thereby improving device noise monitoring accuracy, improving device fault identification accuracy and identification real-time performance, and effectively reducing false alarm and false alarm probabilities;
further, when the steady-state noise sound pressure level of the target device in the current unit time is obtained based on the current unit time environment noise signal of the target device, the noise spectrum estimation value of the target device in the previous unit time and the current unit time environment noise signal are used for carrying out noise spectrum estimation in the current unit time, the steady-state noise sound pressure level in the current unit time is effectively improved in an iterative calculation mode to be self-adaptively adjusted so as to improve the calculation accuracy, and the device noise monitoring accuracy is further improved.
As shown in fig. 2, this embodiment further provides a target device fault monitoring apparatus, which includes:
the acquisition module is used for acquiring an environmental noise signal of the target equipment in real time;
the processing module is used for acquiring the current steady-state noise sound pressure level of the target equipment in unit time based on the current ambient noise signal of the target equipment in unit time;
and the judging module is used for judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, and if so, the target equipment is in an abnormal state.
Further, the processing module includes:
a first processing unit, configured to obtain a current unit-time noise spectrum estimation value of the target device through noise spectrum estimation based on a current unit-time environment noise signal of the target device and a noise spectrum estimation value of a previous unit-time target device;
and the second processing unit is used for obtaining the current steady-state noise sound pressure level of the target equipment in unit time based on the current noise spectrum estimation value of the target equipment in unit time.
Further, the first processing unit includes:
the first processing subunit is used for obtaining corresponding environmental noise power density through fast Fourier transform based on the current unit time environmental noise signal of the target device;
a second processing subunit, configured to window the ambient noise power spectral density and search for a minimum ambient noise power spectral density value within a current unit time window length;
the third processing subunit is configured to determine, based on the minimum value of the power spectral density of the environmental noise within the current unit time window length, an existence probability of intermittent noise in the current unit time;
and the fourth processing subunit is used for obtaining the current unit time noise spectrum estimated value of the target equipment based on the existence probability of the intermittent noise, the noise spectrum estimated value of the target equipment in the last unit time and the environmental noise power density.
Furthermore, the second processing subunit is specifically configured to:
performing frequency domain sliding on the environmental noise power spectral density windowing to obtain a first smooth power spectral density;
performing time domain smoothing based on the first smoothed power spectral density to obtain a noise smoothed power spectral density;
and searching the minimum power density in any window length of the noise smoothing power density as the minimum value of the environmental noise power spectral density in the corresponding current unit time window length.
Furthermore, the third processing subunit is specifically configured to:
calculating a ratio of the first smoothed power spectral density to the minimum value of the ambient noise power spectral density;
judging whether the ratio exceeds a second preset threshold value or not, if so, determining that the existence probability of intermittent noise in the current unit time is 1; if not, the existence probability of the intermittent noise in the current unit time is 0.
Furthermore, the fourth processing subunit is specifically configured to:
smoothing the existence probability of intermittent noise in the current unit time in time and calculating a recursive average factor;
and obtaining the current unit time noise spectrum estimated value of the target equipment based on the recursive average factor, the noise spectrum estimated value of the target equipment in the last unit time and the environmental noise power density.
It should be noted that: the target device fault monitoring apparatus provided in the foregoing embodiment is only illustrated by dividing the functional modules when triggering the target device fault monitoring service, and in practical applications, the function distribution may be completed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to complete all or part of the functions described above. In addition, the embodiments of the target device fault monitoring apparatus and the target device fault monitoring method provided in the above embodiments belong to the same concept, that is, the system is based on the method, and the specific implementation process thereof is detailed in the method embodiments and will not be described herein again.
In addition, the present embodiment further provides an electronic device, including:
one or more processors; and
and a memory associated with the one or more processors for storing program instructions which, when read and executed by the one or more processors, perform the aforementioned target device fault monitoring method to enable real-time, accurate monitoring of device noise, and thus, real-time, accurate monitoring of device anomalies.
With respect to the target device fault monitoring method implemented by executing the program instructions, the specific implementation details are consistent with the descriptions in the foregoing method, and will not be described herein again.
The present embodiment also provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by one or more processors, implements the steps of the device noise monitoring method, and can monitor device noise accurately in real time, so as to monitor device abnormality accurately in real time.
In particular, any combination of one or more computer-readable media may be employed. The computer readable storage medium may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing.
As shown in FIG. 3, more specific examples (a non-exhaustive list) of the computer readable storage medium include: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (Hyper Text Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of an element does not in some cases constitute a limitation on the element itself.
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the embodiments of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
It should be understood that the above-mentioned embodiments are only illustrative of the technical concepts and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All modifications made according to the spirit of the main technical scheme of the invention are covered in the protection scope of the invention.
Claims (10)
1. A target device fault monitoring method is characterized by comprising the following steps:
collecting an environmental noise signal of target equipment in real time;
acquiring a current unit time steady-state noise sound pressure level of the target device based on a current unit time environment noise signal of the target device;
and judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, if so, judging that the target equipment is in an abnormal state.
2. The method of target device fault monitoring of claim 1, wherein the obtaining the current steady state noise sound pressure level per unit time of the target device based on the current ambient noise signal per unit time of the target device comprises:
obtaining a current unit time noise spectrum estimation value of the target equipment through noise spectrum estimation based on the current unit time environment noise signal of the target equipment and the noise spectrum estimation value of the target equipment in the last unit time;
and obtaining the current steady-state noise sound pressure level of the target equipment in unit time based on the current noise spectrum estimation value of the target equipment in unit time.
3. The target device fault monitoring method of claim 2, wherein the obtaining of the current time unit noise spectrum estimate for the target device by noise spectrum estimation based on the current time unit ambient noise signal for the target device and a noise spectrum estimate for a last time unit target device comprises:
obtaining corresponding environmental noise power density through fast Fourier transform based on the current unit time environmental noise signal of the target device;
windowing the environmental noise power spectral density and searching the minimum value of the environmental noise power spectral density in the current unit time window length;
judging the existence probability of intermittent noise in the current unit time based on the minimum value of the power spectral density of the environmental noise in the current unit time window length;
and obtaining the current unit time noise spectrum estimated value of the target equipment based on the existence probability of the intermittent noise, the noise spectrum estimated value of the target equipment in the last unit time and the environmental noise power density.
4. The method of target device fault monitoring of claim 3 wherein the windowing the ambient noise power spectral density and searching for a minimum ambient noise power spectral density value within a current time unit window length comprises:
performing frequency domain sliding on the environmental noise power spectral density windowing to obtain a first smooth power spectral density;
performing time domain smoothing based on the first smoothed power spectral density to obtain a noise smoothed power spectral density;
and searching the minimum power density in any window length of the noise smoothing power density as the minimum value of the environmental noise power spectral density in the corresponding current unit time window length.
5. The method of claim 4, wherein the determining the probability of intermittent noise being present per unit time based on the power spectral density minimum over the current window length of unit time comprises:
calculating a ratio of the first smoothed power spectral density to the minimum value of the ambient noise power spectral density;
judging whether the ratio exceeds a second preset threshold value or not, if so, determining that the existence probability of intermittent noise in the current unit time is 1; if not, the existence probability of the intermittent noise in the current unit time is 0.
6. The target device fault monitoring method of claim 4, wherein the obtaining a current noise spectrum estimate per unit time for the target device based on the probability of the intermittent noise being present, the noise spectrum estimate for the target device last unit time, and the ambient noise power density comprises:
smoothing the existence probability of intermittent noise in the current unit time in time and calculating a recursive average factor;
and obtaining the current unit time noise spectrum estimated value of the target equipment based on the recursive average factor, the noise spectrum estimated value of the target equipment in the last unit time and the environmental noise power density.
7. A target device fault monitoring apparatus, the apparatus comprising:
the acquisition module is used for acquiring an environmental noise signal of the target equipment in real time;
the processing module is used for acquiring the current steady-state noise sound pressure level of the target equipment in unit time based on the current ambient noise signal of the target equipment in unit time;
and the judging module is used for judging whether the current unit time steady-state noise sound pressure level of the target equipment exceeds a first preset threshold value, and if so, the target equipment is in an abnormal state.
8. The target equipment fault monitoring device of claim 8, wherein the processing module comprises:
a first processing unit, configured to obtain a current unit-time noise spectrum estimation value of the target device through noise spectrum estimation based on a current unit-time environment noise signal of the target device and a noise spectrum estimation value of a previous unit-time target device;
and the second processing unit is used for obtaining the current steady-state noise sound pressure level of the target equipment in unit time based on the current noise spectrum estimation value of the target equipment in unit time.
9. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the processors to perform the steps of the method of any of claims 1 to 6.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by one or more processors, carries out the steps of the method according to any one of claims 1 to 6.
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