CN113378699A - Signal processing method, device, equipment and storage medium - Google Patents

Signal processing method, device, equipment and storage medium Download PDF

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CN113378699A
CN113378699A CN202110639082.4A CN202110639082A CN113378699A CN 113378699 A CN113378699 A CN 113378699A CN 202110639082 A CN202110639082 A CN 202110639082A CN 113378699 A CN113378699 A CN 113378699A
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vibration signal
period
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聂泳忠
荀兆勇
王淼清
周洪威
李亚妮
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Xilenma Shenzhen Technology Co ltd
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Xilenma Shenzhen Technology Co ltd
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Abstract

The embodiment of the application provides a signal processing method, a signal processing device, signal processing equipment and a storage medium. The method comprises the following steps: acquiring a vibration signal of target equipment; determining the duration of the vibration signal and the period of the vibration signal according to the vibration signal, wherein the duration comprises at least two periods of the vibration signal; calculating a signal effective value corresponding to each period in the duration according to the vibration signal; and calculating the periodic stability parameters of the vibration signals according to the signal effective value corresponding to each period. According to the embodiment of the application, the cyclostationary parameter of the vibration signal can be automatically calculated, the cyclostationary parameter of the vibration signal is quantitatively analyzed, and then the determining efficiency and the accuracy of the cyclostationary parameter are improved.

Description

Signal processing method, device, equipment and storage medium
Technical Field
The present application relates to the field of fault diagnosis technologies, and in particular, to a signal processing method, an apparatus, a device, and a storage medium.
Background
The fault diagnosis technology is a technology for discovering the abnormal condition of the equipment by monitoring the state parameters of the equipment and analyzing and diagnosing the fault reason after the abnormal condition is discovered, and aims to discover the potential fault of the equipment so as to prevent the equipment from accidents in the prior art.
At present, vibration signals of equipment are usually collected to analyze fault conditions, and a plurality of signal-based analysis methods exist, each method has an application range, and needs to be selected according to the periodic stability of the signals, so that the periodic stability analysis of the signals is very important for fault diagnosis. However, the periodic stationarity of the signal is usually determined by the experience of the plant management personnel, which is inefficient and less accurate.
Disclosure of Invention
The embodiment of the application provides a signal processing method, a signal processing device, signal processing equipment and a signal processing storage medium, which can automatically calculate the cyclostationary parameter of a vibration signal and quantitatively analyze the cyclostationary parameter of the vibration signal.
In a first aspect, an embodiment of the present application provides a signal processing method, where the method includes:
acquiring a vibration signal of target equipment;
determining the duration of the vibration signal and the period of the vibration signal according to the vibration signal, wherein the duration comprises at least two periods of the vibration signal;
calculating a signal effective value corresponding to each period in the duration according to the vibration signal;
and calculating the periodic stability parameters of the vibration signals according to the signal effective value corresponding to each period.
In some implementations of the first aspect, the vibration signal is collected by a sampling device, the vibration signal includes a plurality of sampling points, and determining a period of the vibration signal according to the vibration signal includes:
determining a plurality of periodic sampling points according to the sampling points of the vibration signal;
calculating a signal autocorrelation coefficient corresponding to the number of sampling points in each period according to the instantaneous value of the sampling point of the vibration signal;
and under the condition that the at least two signal autocorrelation coefficients meet a preset proportion condition, calculating the period of the vibration signal according to the sampling frequency of the sampling equipment and the number of periodic sampling points corresponding to the minimum autocorrelation parameter in the at least two signal autocorrelation coefficients.
In some implementations of the first aspect, calculating a period of the vibration signal according to a sampling frequency of the sampling device and a number of periodic sampling points corresponding to a minimum autocorrelation parameter of the at least two signal autocorrelation coefficients includes:
and calculating the quotient of the number of periodic sampling points corresponding to the minimum autocorrelation parameter divided by the sampling frequency, and taking the quotient as the period of the vibration signal.
In some implementations of the first aspect, calculating, from the vibration signal, an effective value of the signal corresponding to each period of the duration includes:
and calculating a signal effective value corresponding to each period in the duration according to the instantaneous value of the sampling point of the vibration signal in each period in the duration.
In some implementations of the first aspect, calculating the cyclostationary parameter of the vibration signal according to the effective value of the signal corresponding to each period includes:
calculating the average value of the signal effective values according to the signal effective value corresponding to each period;
and calculating the variance according to the effective value and the average value of the signal corresponding to each period, and taking the variance as the cyclostationary parameter of the vibration signal.
In some implementations of the first aspect, the method further comprises:
determining an analysis algorithm corresponding to the vibration signal according to the cyclostationary parameter;
the vibration signal is analyzed according to an analysis algorithm.
In some implementations of the first aspect, determining an analysis algorithm corresponding to the vibration signal according to the cyclostationary parameter includes:
determining a frequency domain analysis algorithm as an analysis algorithm corresponding to the vibration signal under the condition that the cyclostationary parameter is greater than or equal to a preset parameter threshold;
and under the condition that the cyclostationary parameter is smaller than the preset parameter threshold, determining the time domain analysis algorithm and/or the time-frequency domain analysis algorithm as the analysis algorithm corresponding to the vibration signal.
In a second aspect, an embodiment of the present application provides a signal processing apparatus, including:
the acquisition module is used for acquiring a vibration signal of the target equipment;
the determining module is used for determining the duration of the vibration signal and the period of the vibration signal according to the vibration signal, wherein the duration comprises at least two periods of the vibration signal;
the calculation module is used for calculating a signal effective value corresponding to each period in the duration according to the vibration signal;
and the calculation module is also used for calculating the periodic stability parameter of the vibration signal according to the signal effective value corresponding to each period.
In some implementations of the second aspect, the vibration signal is collected by a sampling device, the vibration signal includes a plurality of sampling points, and the determining module includes:
the determining unit is used for determining a plurality of periodic sampling points according to the sampling points of the vibration signal;
the first calculating unit is used for calculating a signal autocorrelation coefficient corresponding to the number of sampling points in each period according to the instantaneous value of the sampling point of the vibration signal;
the first calculating unit is further configured to calculate a period of the vibration signal according to the sampling frequency of the sampling device and the number of periodic sampling points corresponding to the minimum autocorrelation parameter of the at least two signal autocorrelation coefficients, when the at least two signal autocorrelation coefficients satisfy a preset proportion condition.
In some implementations of the second aspect, the first computing unit is specifically configured to:
and calculating the quotient of the number of periodic sampling points corresponding to the minimum autocorrelation parameter divided by the sampling frequency, and taking the quotient as the period of the vibration signal.
In some implementations of the second aspect, the computing module includes:
and the second calculating unit is used for calculating the signal effective value corresponding to each period in the duration according to the instantaneous value of the sampling point of the vibration signal in each period in the duration.
In some implementations of the second aspect, the computing module includes:
the third calculating unit is used for calculating the average value of the signal effective values according to the signal effective values corresponding to each period;
and the third calculating unit is also used for calculating the variance according to the effective value and the average value of the signal corresponding to each period, and taking the variance as the cyclostationary parameter of the vibration signal.
In some realizations of the second aspect, the determining module is further configured to determine an analysis algorithm corresponding to the vibration signal according to the cyclostationary parameter;
the device still includes: and the analysis module is used for analyzing the vibration signal according to an analysis algorithm.
In some implementations of the second aspect, the determining module includes:
the fourth determining unit is used for determining the frequency domain analysis algorithm as the analysis algorithm corresponding to the vibration signal under the condition that the cyclostationary parameter is greater than or equal to the preset parameter threshold;
the fourth determining unit is further configured to determine that the time domain analysis algorithm and/or the time-frequency domain analysis algorithm is/are an analysis algorithm corresponding to the vibration signal under the condition that the cyclostationary parameter is smaller than the preset parameter threshold.
In a third aspect, an embodiment of the present application provides a signal processing apparatus, including: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements the signal processing method described in the first aspect or any of its realizations.
In a fourth aspect, the present application provides a computer-readable storage medium, on which computer program instructions are stored, and the computer program instructions, when executed by a processor, implement the signal processing method in the first aspect or any of the implementable manners of the first aspect.
According to the signal processing method, the signal processing device, the signal processing equipment and the signal processing storage medium, the duration of the vibration signal and the period of the vibration signal can be determined according to the vibration signal of the target equipment, then the signal effective value corresponding to each period in the duration is calculated according to the vibration signal, and then the cyclostationary parameter of the vibration signal is calculated according to the signal effective value corresponding to each period, so that the cyclostationary parameter is used for quantitatively analyzing the cyclostationary of the vibration signal, and the determining efficiency and the accuracy of the cyclostationary parameter are improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic block diagram of a signal processing system according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of a signal processing method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a vibration signal provided by an embodiment of the present application;
FIG. 4 is a schematic diagram of a signal autocorrelation coefficient provided by an embodiment of the present application;
FIG. 5 is a schematic diagram of an effective value of a signal provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of another vibration signal provided by an embodiment of the present application;
FIG. 7 is a schematic diagram of another signal autocorrelation coefficient provided by an embodiment of the present application;
fig. 8 is a schematic diagram of another signal effective value provided by the embodiment of the present application;
fig. 9 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present application.
Detailed Description
Features and exemplary embodiments of various aspects of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the application and do not limit the application. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In view of the problems in the background art, embodiments of the present application provide a signal processing method, an apparatus, a device, and a storage medium, which may first determine a duration of a vibration signal and a period of the vibration signal according to a vibration signal of a target device, then calculate a signal effective value corresponding to each period within the duration according to the vibration signal, and then calculate a cyclostationary parameter of the vibration signal according to the signal effective value corresponding to each period, so as to quantitatively analyze cyclostationarity of the vibration signal through the cyclostationary parameter, and improve determination efficiency and accuracy of cyclostationarity.
The signal processing method, apparatus, device and storage medium provided in the embodiments of the present application are described in detail with reference to the accompanying drawings through specific embodiments and application scenarios thereof.
Fig. 1 is a schematic architecture diagram of a signal processing system provided in an embodiment of the present application, and as shown in fig. 1, the signal processing system may include an electronic device 110 and a target device 120, which is not limited herein.
The electronic device 110 may be a mobile electronic device or a non-mobile electronic device. For example, the Mobile electronic device may be a Mobile phone, a tablet Computer, a notebook Computer, a palmtop Computer, an Ultra-Mobile Personal Computer (UMPC), or the like, and the non-Mobile electronic device may be a server, a Network Attached Storage (NAS), a Personal Computer (PC), or the like. The target device 120 may be a rotating device such as a speed reducer, a generator, or a motor.
As an example, the signal processing system may be applied to equipment failure diagnosis scenarios in the fields of energy, electricity, traffic, manufacturing, and the like. As shown in fig. 1, the electronic device 110 may obtain a vibration signal of the target device 120, such as a voltage signal or a current signal, and then determine a duration of the vibration signal and a period of the vibration signal according to the vibration signal, then calculate an effective value of the signal corresponding to each period in the duration, that is, an effective value of an instantaneous value of the signal in each period according to the vibration signal, and calculate a cyclostationarity parameter of the vibration signal according to the effective value of the signal corresponding to each period, so as to characterize cyclostationarity of the vibration signal.
The signal processing method provided by the embodiment of the present application will be described below. The main body of the signal processing method may be the electronic device 110 in the signal processing system shown in fig. 1.
Fig. 2 is a schematic flowchart of a signal processing method provided in an embodiment of the present application, and as shown in fig. 2, the signal processing method may include the following steps:
s210, acquiring a vibration signal of the target device.
Specifically, in a state where the target device is operating, a vibration signal of the target device collected by the sampling device may be acquired. The sampling device may be a sensor, and the vibration signal may be a voltage signal or a current signal, which includes a plurality of sampling points.
And S220, determining the duration of the vibration signal and the period of the vibration signal according to the vibration signal.
In one embodiment, the duration of the vibration signal may be calculated from the number of sampling points of the vibration signal and the sampling frequency of the sampling device. For example, the duration is obtained by dividing the number of sampling points by the sampling frequency.
Meanwhile, the number of sampling points in a plurality of periods can be determined according to the number of sampling points of the vibration signal. The number of periodic sampling points represents the number of sampling points in one candidate period, and the number of periodic sampling points represents the number of sampling points in a plurality of different candidate periods.
And calculating a signal autocorrelation coefficient corresponding to the number of sampling points in each period according to the instantaneous value of the sampling point of the vibration signal. Wherein the signal autocorrelation coefficient represents the degree of autocorrelation of the vibration signal.
In the case where the at least two signal autocorrelation coefficients satisfy a preset scaling condition, for example, the at least two signal autocorrelation coefficients satisfy an increasing scaling. The period of the vibration signal can be rapidly and accurately calculated according to the sampling frequency of the sampling device and the number of periodic sampling points corresponding to the minimum autocorrelation parameter in the autocorrelation coefficients of at least two signals. For example, a quotient obtained by dividing the number of periodic sampling points corresponding to the minimum autocorrelation parameter by the sampling frequency may be calculated as the period of the vibration signal.
As an example, the sampling frequency of the sampling device is m, the sampling length of the vibration signal is n, that is, the vibration signal includes n equally spaced sampling points, the number of instantaneous values defining the sampling points is x (n), and n is 0, 1, 2, …, n. The number of periodic sampling points is k equal to 1, 2, …, n/2. And calculating the signal autocorrelation coefficient corresponding to the number of sampling points in each period according to the instantaneous value of the sampling point and a signal autocorrelation formula. Illustratively, the signal autocorrelation formula may be as follows:
Figure BDA0003106414030000071
if the ratio of the autocorrelation coefficients of the signals corresponding to k-k 1, k2, k3, and k4 is 1:2:3:4, the quotient of k1 divided by m, i.e., m/k1, can be calculated, and the period of the vibration signal is m/k 1.
And S230, calculating a signal effective value corresponding to each period in the duration according to the vibration signal.
In one embodiment, the effective value of the signal corresponding to each period in the duration, that is, the effective value of the instantaneous value of the signal in each period, can be quickly and accurately calculated according to the instantaneous values of the sampling points of the vibration signal in each period in the duration.
As an example, the signal effective value for each period may be calculated from the instantaneous value of the sampling point within each period and the signal effective value formula. Illustratively, the signal effective value formula may be as follows:
Figure BDA0003106414030000072
wherein rms (T) represents the effective value of the signal of the Tth period in the duration, N1Indicating the number of the last sample point in the T-th period of the duration, N0Indicating the number, N, of the first sample point in the T-th period of the duration1-N0Representing the number of sample points in the T-th period of the duration, and T represents the number of periods in the duration.
And S240, calculating the periodic stability parameter of the vibration signal according to the signal effective value corresponding to each period.
In one embodiment, the average value of the effective signal values may be calculated according to the effective signal value corresponding to each period, and the variance may be calculated according to the effective signal value and the average value corresponding to each period, and the variance may be used as the cyclostationary parameter of the vibration signal. Therefore, the difference of the sampling points in each period can be accurately represented through the variance, and the periodic stationarity of the vibration signal can be intuitively reflected.
As an example, the variance may be calculated from the signal significance and mean values corresponding to each period, and a variance formula. Illustratively, the variance formula may be as follows:
Figure BDA0003106414030000081
wherein, Stability represents a cyclostationary parameter, rms (T) represents a signal effective value of the Tth period in the duration, and mu represents an average value of the signal effective values of the T periods.
In the embodiment of the application, the duration of the vibration signal and the period of the vibration signal can be determined according to the vibration signal of the target device, then the signal effective value corresponding to each period in the duration is calculated according to the vibration signal, and then the cyclostationary parameter of the vibration signal is calculated according to the signal effective value corresponding to each period, so that the cyclostationary parameter is used for quantitatively analyzing the cyclostationary of the vibration signal, and the determination efficiency and accuracy of the cyclostationary are improved.
In one embodiment, an analysis algorithm corresponding to the vibration signal may be determined based on the cyclostationary parameter, and the vibration signal may be analyzed based on the analysis algorithm. For example, in the case that the cyclostationary parameter is greater than or equal to the preset parameter threshold, the frequency domain analysis algorithm may be determined to be the analysis algorithm corresponding to the vibration signal; and under the condition that the cyclostationary parameter is smaller than the preset parameter threshold, determining that the time domain analysis algorithm and/or the time-frequency domain analysis algorithm is an analysis algorithm corresponding to the vibration signal. The frequency domain analysis algorithm may be a cepstrum analysis algorithm or a refined spectrum analysis algorithm, the time domain analysis algorithm may be a classical time domain analysis algorithm, and the time-frequency domain analysis algorithm may be a wavelet transform analysis algorithm. Therefore, an analysis algorithm suitable for the vibration signal can be determined based on the cyclostationary parameter, and the analysis effect is further improved.
The following describes a signal processing method provided in the embodiment of the present application with reference to a simulation example, which includes the following specific steps:
as shown in fig. 3, the vibration signal is x (n) sin (0.125 pi n), the sampling frequency is 4, the period of the vibration signal is 4s, and the number of sampling points in the period is 16.
And (2) simulating the vibration signal, determining the duration of the vibration signal and a plurality of periodic sampling points, and calculating a signal autocorrelation coefficient corresponding to each periodic sampling point according to the instantaneous value of the sampling point and the formula (1). The autocorrelation coefficient of the signal corresponding to the number of sampling points in each period can be as shown in fig. 4. In fig. 4, when the number of periodic sampling points is 16, the autocorrelation coefficient of the signal is 8; when the number of periodic sampling points is 32, the autocorrelation coefficient of the signal is 16; when the number of periodic sampling points is 48, the autocorrelation coefficient of the signal is 24; when the number of periodic sampling points is 64, the signal autocorrelation coefficient is 32, and the ratio of the signal autocorrelation coefficient is an increasing ratio of 1:2:3: 4. Therefore, it is determined that 16, which is the smallest number of periodic sampling points, is the number of target periodic sampling points of the vibration signal, and 4, which is obtained by dividing 16 by 4, is the period of the vibration signal, that is, the period of the vibration signal is 4 s.
Then, the effective value of the signal in each period in the duration is calculated according to the instantaneous value of the sampling point in each period and the formula (2). Wherein, the effective value of the signal corresponding to each period can be as shown in fig. 5. It can be seen that the effective values of the signals of 4 periods of the vibration signal are equal, and the variance calculated according to equation (3) is 0, i.e., the cyclostationary parameter is 0. Therefore, the validity of the signal processing method provided by the embodiment of the application can be verified through the simulation signal.
The following describes a signal processing method provided in an embodiment of the present application with reference to a specific example, which specifically includes:
the target equipment is a speed reducer, a speed sensor is installed on a shell of the speed reducer, the sampling frequency of the speed sensor is 2048Hz, and the collected vibration signals of the speed reducer are shown in figure 6, so that a lot of burrs exist in the sampling signals.
And processing the vibration signal, determining the duration of the vibration signal and a plurality of periodic sampling points, and calculating a signal autocorrelation coefficient corresponding to each periodic sampling point according to the instantaneous value of the sampling point and a formula (1). The autocorrelation coefficient of the signal corresponding to the number of sampling points in each period can be as shown in fig. 7. In fig. 7, when the number of periodic sampling points is 408, the autocorrelation coefficient of the signal is 3539; when the number of periodic sampling points is 814, the signal autocorrelation coefficient is 7135; when the number of periodic sampling points is 1222, the autocorrelation coefficient of the signal is 10280; when the number of periodic sampling points is 1630, the signal autocorrelation coefficient is 12560; when the number of periodic sampling points is 2038, the signal autocorrelation coefficient is 16970, and the ratio of the signal autocorrelation coefficients is about the increasing ratio of 1:2:3:4: 5. Therefore, 408 with the smallest number of periodic sampling points can be determined as the number of target periodic sampling points of the vibration signal, and 0.2 obtained by dividing 408 by 2048 is taken as the period of the vibration signal, that is, the period of the vibration signal is 0.2 s.
Then, the effective value of the signal in each period in the duration is calculated according to the instantaneous value of the sampling point in each period and the formula (2). Wherein, the effective value of the signal corresponding to each period can be as shown in fig. 8. It can be seen that the effective values of the signals of the 1 st to 5 th periods of the vibration signal are 0.1133, 0.1416, 0.2761, 0.1798 and 0.2244, respectively, and the variance calculated according to the formula (3) is 0.0034, i.e., the cyclostationary parameter is 0.0034. Therefore, the validity of the signal processing method provided by the embodiment of the application can be verified through specific examples.
Based on the signal processing method provided in the embodiment of the present application, an embodiment of the present application further provides a signal processing apparatus, as shown in fig. 9, the signal processing apparatus 900 may include:
an obtaining module 910, configured to obtain a vibration signal of a target device.
A determining module 920, configured to determine a duration of the vibration signal and a period of the vibration signal according to the vibration signal, where the duration includes at least two periods of the vibration signal.
A calculating module 930, configured to calculate, according to the vibration signal, a signal effective value corresponding to each period in the duration.
The calculating module 930 is further configured to calculate a cyclostationary parameter of the vibration signal according to the effective value of the signal corresponding to each period.
In some embodiments, the vibration signal is collected by a sampling device, the vibration signal includes a plurality of sampling points, and the determining module 920 includes:
and the determining unit is used for determining the number of sampling points in a plurality of periods according to the number of the sampling points of the vibration signal.
And the first calculating unit is used for calculating a signal autocorrelation coefficient corresponding to the number of sampling points in each period according to the instantaneous value of the sampling point of the vibration signal.
The first calculating unit is further configured to calculate a period of the vibration signal according to the sampling frequency of the sampling device and the number of periodic sampling points corresponding to the minimum autocorrelation parameter of the at least two signal autocorrelation coefficients, when the at least two signal autocorrelation coefficients satisfy a preset proportion condition.
In some embodiments, the first computing unit is specifically configured to:
and calculating the quotient of the number of periodic sampling points corresponding to the minimum autocorrelation parameter divided by the sampling frequency, and taking the quotient as the period of the vibration signal.
In some embodiments, the calculation module 930 includes:
and the second calculating unit is used for calculating the signal effective value corresponding to each period in the duration according to the instantaneous value of the sampling point of the vibration signal in each period in the duration.
In some embodiments, the calculation module 930 includes:
and the third calculating unit is used for calculating the average value of the signal effective values according to the signal effective values corresponding to each period.
And the third calculating unit is also used for calculating the variance according to the effective value and the average value of the signal corresponding to each period, and taking the variance as the cyclostationary parameter of the vibration signal.
In some embodiments, the determining module 920 is further configured to determine an analysis algorithm corresponding to the vibration signal according to the cyclostationary parameter.
The signal processing apparatus 900 further includes: and the analysis module is used for analyzing the vibration signal according to an analysis algorithm.
In some embodiments, the determining module 920 includes:
and the fourth determining unit is used for determining the frequency domain analysis algorithm as the analysis algorithm corresponding to the vibration signal under the condition that the cyclostationary parameter is greater than or equal to the preset parameter threshold.
The fourth determining unit is further configured to determine that the time domain analysis algorithm and/or the time-frequency domain analysis algorithm is/are an analysis algorithm corresponding to the vibration signal under the condition that the cyclostationary parameter is smaller than the preset parameter threshold.
It can be understood that, for brevity, details of each module/unit in the signal processing apparatus 900 shown in fig. 9 are not described herein again, and the functions of each step in the signal processing method provided in the embodiment of the present application can be realized and the corresponding technical effects can be achieved.
Fig. 10 is a schematic structural diagram of a signal processing apparatus according to an embodiment of the present application. As shown in fig. 10, the signal processing device may include a processor 1001 and a memory 1002 storing computer program instructions.
Specifically, the processor 1001 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement the embodiments of the present Application.
Memory 1002 may include mass storage for data or instructions. By way of example, and not limitation, memory 1002 may include a Hard Disk Drive (HDD), a floppy Disk Drive, flash memory, an optical Disk, a magneto-optical Disk, magnetic tape, or a Universal Serial Bus (USB) Drive or a combination of two or more of these. Memory 1002 may include removable or non-removable (or fixed) media, where appropriate. The memory 1002 may be internal or external to the signal processing apparatus, where appropriate. In a particular embodiment, the memory 1002 is non-volatile solid-state memory. In a particular embodiment, the memory 1002 includes Read Only Memory (ROM). Where appropriate, the ROM may be mask-programmed ROM, Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), electrically rewritable ROM (EAROM), or flash memory or a combination of two or more of these.
The processor 1001 can implement the signal processing method provided in the embodiment of the present application by reading and executing the computer program instructions stored in the memory 1002, and achieve the corresponding technical effects achieved by executing the method in the embodiment of the present application, which are not described herein again for brevity.
In one example, the signal processing device may also include a communication interface 1003 and a bus 1010. As shown in fig. 10, the processor 1001, the memory 1002, and the communication interface 1003 are connected to each other via a bus 1010 to complete communication therebetween.
The communication interface 1003 is mainly used for implementing communication between modules, apparatuses, units and/or devices in this embodiment.
The bus 1010 includes hardware, software, or both to couple the components of the signal processing device to each other. By way of example, and not limitation, a Bus may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (Front Side Bus, FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) Bus, an infiniband interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a Micro Channel Architecture (MCA) Bus, a Peripheral Component Interconnect (PCI) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a video electronics standards association local (VLB) Bus, or other suitable Bus or a combination of two or more of these. Bus 1010 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.
The signal processing device can execute the signal processing method in the embodiment of the application, so that the corresponding technical effects of the signal processing method provided by the embodiment of the application are realized.
In addition, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores computer program instructions; the computer program instructions realize the signal processing method provided by the embodiment of the application when being executed by the processor.
It should be clear that each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments may be referred to each other, and for brevity, the description is omitted. The present application is not limited to the specific configurations and processes described above and shown in the figures. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications, and additions or change the order between the steps after comprehending the spirit of the present application.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic Circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of machine-readable media include electronic circuits, semiconductor Memory devices, Read-Only memories (ROMs), flash memories, erasable ROMs (eroms), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood 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 for performing the specified functions or acts, or combinations of special purpose hardware and computer instructions.
As described above, only the specific embodiments of the present application are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application.

Claims (10)

1. A method of signal processing, the method comprising:
acquiring a vibration signal of target equipment;
determining a duration of the vibration signal and a period of the vibration signal according to the vibration signal, wherein the duration comprises at least two periods of the vibration signal;
calculating a signal effective value corresponding to each period in the duration according to the vibration signal;
and calculating the cyclostationary parameter of the vibration signal according to the signal effective value corresponding to each period.
2. The method of claim 1, wherein the vibration signal is collected by a sampling device, the vibration signal includes a plurality of sampling points, and determining a period of the vibration signal from the vibration signal includes:
determining a plurality of periodic sampling points according to the sampling points of the vibration signal;
calculating a signal autocorrelation coefficient corresponding to the number of sampling points in each period according to the instantaneous value of the sampling point of the vibration signal;
and under the condition that at least two signal autocorrelation coefficients meet a preset proportion condition, calculating the period of the vibration signal according to the sampling frequency of the sampling equipment and the number of periodic sampling points corresponding to the minimum autocorrelation parameter in the at least two signal autocorrelation coefficients.
3. The method of claim 2, wherein the calculating the period of the vibration signal according to the sampling frequency of the sampling device and the number of periodic sampling points corresponding to the minimum autocorrelation parameter of the autocorrelation coefficients of the at least two signals comprises:
and calculating a quotient obtained by dividing the number of periodic sampling points corresponding to the minimum autocorrelation parameter by the sampling frequency, and taking the quotient as the period of the vibration signal.
4. The method of claim 2, wherein said calculating a signal effective value for each period of said duration based on said vibration signal comprises:
and calculating a signal effective value corresponding to each period in the duration according to the instantaneous value of the sampling point of the vibration signal in each period in the duration.
5. The method according to any one of claims 1 to 4, wherein said calculating a cyclostationary parameter of the vibration signal according to the signal effective value corresponding to each period comprises:
calculating the average value of the signal effective values according to the signal effective value corresponding to each period;
and calculating a variance according to the signal effective value corresponding to each period and the average value, and taking the variance as a cyclostationary parameter of the vibration signal.
6. The method of claim 1, further comprising:
determining an analysis algorithm corresponding to the vibration signal according to the cyclostationary parameter;
analyzing the vibration signal according to the analysis algorithm.
7. The method of claim 6, wherein determining an analysis algorithm corresponding to the vibration signal based on the cyclostationary parameter comprises:
determining a frequency domain analysis algorithm as an analysis algorithm corresponding to the vibration signal under the condition that the cyclostationary parameter is greater than or equal to a preset parameter threshold;
and under the condition that the cyclostationary parameter is smaller than a preset parameter threshold value, determining a time domain analysis algorithm and/or a time-frequency domain analysis algorithm as an analysis algorithm corresponding to the vibration signal.
8. A signal processing apparatus, characterized in that the apparatus comprises:
the acquisition module is used for acquiring a vibration signal of the target equipment;
the determining module is used for determining the duration of the vibration signal and the period of the vibration signal according to the vibration signal, wherein the duration comprises at least two periods of the vibration signal;
the calculation module is used for calculating a signal effective value corresponding to each period in the duration according to the vibration signal;
and the calculation module is also used for calculating the cyclostationary parameter of the vibration signal according to the signal effective value corresponding to each period.
9. A signal processing apparatus, characterized in that the apparatus comprises: a processor and a memory storing computer program instructions; the processor, when executing the computer program instructions, implements a signal processing method as claimed in any one of claims 1-7.
10. A computer-readable storage medium, having stored thereon computer program instructions, which, when executed by a processor, implement the signal processing method of any one of claims 1 to 7.
CN202110639082.4A 2021-06-08 2021-06-08 Signal processing method, device, equipment and storage medium Pending CN113378699A (en)

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Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110639082.4A CN113378699A (en) 2021-06-08 2021-06-08 Signal processing method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
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