CN114416459B - Hard disk performance loss prediction method, device, equipment and storage medium - Google Patents
Hard disk performance loss prediction method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a method, a device, equipment and a storage medium for predicting performance loss of a hard disk. Relating to the technical field of hard disk test, the method comprises the following steps: carrying out noise sensitivity test on a hard disk to be predicted to obtain target power spectral density corresponding to the hard disk to be predicted under loss criticality of different frequency bands and sensitivity of the hard disk to be predicted under different frequency bands; acquiring a power spectral density curve corresponding to the measured noise in the case to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise; and predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band. The performance loss prediction of the hard disk under the complex condition in the case can be realized, and the real object test in the case is replaced.
Description
Technical Field
The invention relates to the technical field of hard disk testing, in particular to a method, a device, equipment and a storage medium for predicting the performance loss of a hard disk.
Background
At present, a high-speed fan used for system heat dissipation needs radiates strong noise, and performance loss of a mechanical hard disk is often caused. Research and development personnel usually need to analyze the principle and frequency (Hz) of the performance degradation of the hard disk caused by noise, but at present, only PES (position Error Signal) analysis tools of hard disk manufacturers can display the influence degree of each frequency and the performance degradation of the hard disk in a case caused by the noise of which frequencies, but the PES analysis tools are exclusive tools of the hard disk manufacturers, and other companies have no application permission, so that the analysis work of the research and development personnel does not have convenient and available tools. Therefore, how to predict the performance loss of the hard disk is a problem which needs to be solved urgently at present.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, a device and a medium for predicting performance loss of a hard disk, which can predict performance loss of the hard disk under a complex condition in a chassis. The specific scheme is as follows:
in a first aspect, the present application discloses a method for predicting a performance loss of a hard disk, comprising:
carrying out noise sensitivity test on a hard disk to be predicted to obtain target power spectral density corresponding to the hard disk to be predicted under loss criticality of different frequency bands and sensitivity of the hard disk to be predicted under different frequency bands; the loss critical is the edge state from the loss of the hard disk performance to the loss;
acquiring a power spectral density curve corresponding to the measured noise in the case to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise;
and predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band.
Optionally, the performing a noise sensitivity test on the hard disk to be predicted to obtain target power spectral densities corresponding to the hard disk to be predicted under loss criticalities of different frequency bands and sensitivities of the hard disk to be predicted under different frequency bands includes:
carrying out noise sensitivity tests of different frequency segments on the hard disk to be predicted to obtain the power spectral density of each frequency segment under different preset sound pressure levels, the target power spectral density corresponding to the loss critical of each frequency segment and the hard disk performance loss of each frequency segment under different preset sound pressure levels;
and obtaining the sensitivity of the corresponding frequency band based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency band.
Optionally, the performing noise sensitivity tests on different frequency bands on the hard disk to be predicted to obtain the power spectral density of each frequency band at different preset sound pressure levels, the target power spectral density corresponding to the loss threshold of each frequency band, and the hard disk performance loss of each frequency band at different preset sound pressure levels includes:
dividing a target frequency range according to a preset bandwidth to obtain upper and lower frequency limits and a center frequency of a plurality of frequency segments;
calculating the power spectral density of the frequency segment under different preset sound pressure levels, and determining the hard disk performance loss of the hard disk to be predicted under different preset sound pressure levels corresponding to the frequency segment;
and determining the loss critical of the hard disk to be predicted in the frequency band and the target power spectral density corresponding to the loss critical according to the hard disk performance loss corresponding to different preset sound pressure levels.
Optionally, the obtaining the sensitivity of the corresponding frequency segment based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency segment includes:
respectively calculating the square difference between the power spectral density of the frequency segment under different preset sound pressure levels and the target power spectral density corresponding to the loss critical of the frequency segment to obtain the overrun noise intensity corresponding to the frequency segment under different preset sound pressure levels;
constructing a linear regression model by taking the overrun noise intensity as a first coordinate and taking the performance loss of the hard disk of the frequency segment under different preset sound pressure levels as a second coordinate;
and taking the slope of the linear regression model as the sensitivity of the hard disk to be predicted under the frequency band.
Optionally, the predicting, according to the sensitivity, the target power spectral density, and the power spectral density curve segment corresponding to each frequency segment, the local performance loss of the hard disk to be predicted in different frequency segments, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss in each frequency segment includes:
extracting target characteristic parameters of the power spectral density curve segment; the target feature parameters include a saliency ratio and a frequency duty cycle;
determining a rule according to the target characteristic parameters and a preset integration method, and determining a target integration method for the frequency segments corresponding to the power spectral density curve segments so as to determine a target integration method corresponding to each frequency segment;
predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density, the power spectral density curve segment and the target integration method corresponding to each frequency band;
and summing the local performance losses corresponding to all the frequency sections to obtain the overall performance loss of the hard disk to be predicted.
Optionally, the predicting, according to the sensitivity, the target power spectral density, the power spectral density curve segment, and the target integration method corresponding to each frequency band, the local performance loss of the hard disk to be predicted in different frequency bands includes:
calculating the actual overrun noise intensity of the hard disk to be predicted in the frequency band by using the target integration method based on the target power spectral density and the power spectral density curve segment;
and taking the product of the actual overrun noise intensity and the sensitivity of the corresponding frequency band as the local performance loss of the frequency band so as to predict and obtain the local performance loss of the hard disk to be predicted under different frequency bands.
Optionally, the calculating, based on the target power spectral density and the power spectral density curve segment, the actual overrun noise strength of the hard disk to be predicted in the frequency segment by using the target integration method includes:
if the target integration method is a first target integration method, integrating the region of the power spectral density curve segment in the frequency band, which exceeds the target power spectral density, so as to obtain the actual overrun noise intensity of the hard disk to be predicted in the frequency band;
if the target integration method is a second target integration method, determining a frequency width value of an area where the power spectral density curve segment exceeds the target power spectral density in the frequency segment and a power spectral density maximum value of the power spectral density curve in the frequency segment, and calculating a product of the frequency width value and the power spectral density maximum value to obtain an actual overrun noise intensity of the hard disk to be predicted in the frequency segment.
In a second aspect, the present application discloses a hard disk performance loss prediction apparatus, including:
the system comprises a sensitivity testing module, a data processing module and a data processing module, wherein the sensitivity testing module is used for testing the noise sensitivity of a hard disk to be predicted so as to obtain the corresponding target power spectral density of the hard disk to be predicted under the loss criticality of different frequency bands and the sensitivity of the hard disk to be predicted under different frequency bands; the loss critical is the edge state from the loss of the hard disk performance to the loss;
the power spectral density curve acquisition module is used for acquiring a power spectral density curve corresponding to the measured noise in the chassis so as to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise;
and the performance loss prediction module is used for predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band.
In a third aspect, the present application discloses an electronic device, comprising:
a memory for storing a computer program;
and the processor is used for executing the computer program to realize the hard disk performance loss prediction method.
In a fourth aspect, the present application discloses a computer readable storage medium for storing a computer program; wherein the computer program when executed by the processor implements the aforementioned hard disk performance loss prediction method.
In the method, a hard disk to be predicted is subjected to noise sensitivity test to obtain target power spectral density corresponding to the hard disk to be predicted under loss criticality of different frequency bands and sensitivity of the hard disk to be predicted under different frequency bands; the loss critical is the edge state from the loss of the hard disk performance to the loss; acquiring a power spectral density curve corresponding to the measured noise in the case to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise; and predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band. Therefore, the performance loss of the hard disk in the case is predicted by performing the noise sensitivity test on the hard disk to be predicted and combining the hard disk sensitivity test result and the actual noise condition of the case, so that the performance loss prediction of the hard disk in the case under the complex condition is realized, the actual test in the case can be replaced, a PES analysis tool is replaced, and the influence degree of the noise of each frequency on the performance reduction of the hard disk can be analyzed according to the predicted local performance loss.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a hard disk performance loss prediction method provided in the present application;
FIG. 2 is a chart of a power spectral density spectrum of a random signal with a predetermined bandwidth according to the present application;
FIG. 3 is a linear regression model of hard disk performance loss and overrun noise strength provided herein;
FIG. 4 is a graph of sensitivity versus frequency provided herein;
FIG. 5 is a plot of a measured noise power spectral density curve versus a target power spectral density curve within a chassis according to the present application;
fig. 6 is a graph of a measured noise power spectral density curve and a target power spectral density curve in a local frequency next chassis according to the present application;
FIG. 7 is a table of rules determined by the integral method provided herein;
FIG. 8 is a flowchart illustrating a method for predicting performance loss of a hard disk according to an embodiment of the present disclosure;
fig. 9 is a schematic structural diagram of a hard disk performance loss prediction apparatus according to the present application;
fig. 10 is a block diagram of an electronic device provided in the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the prior art, only a PES analysis tool of a hard disk manufacturer can display the influence degree of each frequency and the performance degradation of a hard disk in a case caused by noise of which frequencies, but the PES analysis tool is a special tool of the hard disk manufacturer, and other companies do not have application permission, so that the analysis work of research and development personnel does not have a convenient and available tool. In order to overcome the technical problem, the application provides a method for predicting the performance loss of a hard disk, which can predict the performance loss of the hard disk under the complex condition in a case.
The embodiment of the application discloses a method for predicting the performance loss of a hard disk, which can comprise the following steps as shown in figure 1:
step S11: and carrying out noise sensitivity test on the hard disk to be predicted to obtain the corresponding target power spectral density of the hard disk to be predicted under the loss criticality of different frequency bands and the sensitivity of the hard disk to be predicted under different frequency bands, wherein the loss criticality is the marginal state from the loss of the hard disk performance to the loss of the hard disk.
In this embodiment, by performing a noise sensitivity test on the hard disk to be predicted, the target power spectral density corresponding to the hard disk to be predicted under the loss criticality of different frequency bands and the sensitivity of the hard disk to be predicted under different frequency bands are determined. The noise sensitivity test is to perform an audio frequency sweep test or a random noise test on the hard disk in order to study the problem of the sensitivity of the hard disk to noise, so as to observe the performance degradation phenomenon of the hard disk under the noise interference of different frequencies and different sound pressure levels, and specifically, the test can be performed by editing an audio signal by using a computer, playing the audio signal by using a sound system, applying sound pressure excitation to the hard disk and the like; accordingly, the hard disk sensitivity test result is generally a two-dimensional matrix, and the performance loss of the hard disk under different frequencies and different sound pressures can be revealed and expressed by percentage. The noise signal can be converted into FFT (Fast Fourier Transform) or PSD (power spectral density) to reveal its energy distribution at each frequency. By testing the noise sensitivity of the hard disk to be predicted, the target power spectral density corresponding to the hard disk to be tested under the loss critical of different frequency segments of the hard disk in the single body test and the sensitivity of the hard disk to be tested under different frequency segments can be obtained, wherein the loss critical is the marginal state from the performance loss of the hard disk from the non-existence loss to the loss.
In this embodiment, the performing a noise sensitivity test on the hard disk to be predicted to obtain a target power spectral density corresponding to the hard disk to be predicted under loss criticalities of different frequency bands and sensitivities of the hard disk to be predicted under different frequency bands may include: carrying out noise sensitivity tests of different frequency segments on the hard disk to be predicted to obtain the power spectral density of each frequency segment under different preset sound pressure levels, the target power spectral density corresponding to the loss critical of each frequency segment and the hard disk performance loss of each frequency segment under different preset sound pressure levels; and obtaining the sensitivity of the corresponding frequency band based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency band. The method comprises the steps of conducting noise sensitivity tests of different frequency bands on a hard disk to be predicted, obtaining power spectral density of each frequency band under different preset sound pressure levels, target power spectral density corresponding to loss criticality of each frequency band and hard disk performance loss of each frequency band under different preset sound pressure levels, and then determining the sensitivity of the hard disk to be predicted under the frequency band based on the power spectral density of a certain frequency band under different preset sound pressure levels, the target power spectral density corresponding to the loss criticality of the frequency band and the hard disk performance loss of the frequency band under different preset sound pressure levels, so that the sensitivity of the hard disk to be predicted under different frequency bands is obtained.
In this embodiment, the performing noise sensitivity tests on different frequency segments on the hard disk to be predicted to obtain a power spectral density of each frequency segment under different preset sound pressure levels, a target power spectral density corresponding to a loss threshold of each frequency segment, and a hard disk performance loss of each frequency segment under different preset sound pressure levels may include: dividing a target frequency range according to a preset bandwidth to obtain upper and lower frequency limits and a center frequency of a plurality of frequency segments; calculating the power spectral density of the frequency segment under different preset sound pressure levels, and determining the hard disk performance loss of the hard disk to be predicted under different preset sound pressure levels corresponding to the frequency segment; and determining the loss critical of the hard disk to be predicted in the frequency band and the target power spectral density corresponding to the loss critical according to the hard disk performance loss corresponding to different preset sound pressure levels.
It can be understood that, the target frequency range is divided according to the preset bandwidth to obtain a plurality of frequency segments and determine the upper and lower frequency limits and the central frequency of each frequency segment; for example, the hard disk noise sensitivity test signal used in this embodiment is a random signal with 1/9 octave bandwidth, that is, the preset bandwidth is 1/9 octave bandwidth, its PSD spectral line is shown in fig. 2, and the energy of the noise signal is at the frequency
Are uniformly distributed but in
The other frequencies do not output energy. So that its sound pressure P (Pa) is
；
Is the power spectral density;
sound pressure P (Pa) converted to sound pressure level of
；
The power spectral density can be known according to the formula
And sound pressure level
In a relationship of
(ii) a From this, the power spectral density corresponding to the sound pressure level is calculated.
As shown in table 1 below, the test results of the center frequency f =3428Hz at different preset sound pressure levels are shown, wherein the third row of data is the power spectral density:
TABLE 1
Meanwhile, determining the performance loss of the hard disk to be predicted under different preset sound pressure levels corresponding to the frequency segments, and specifically applying a formula according to the ratio of the actual measurement performance (namely, the hard disk performance measured under the noise interference) of the hard disk to the standard performance value (namely, the hard disk performance measured under the noise interference-free condition): δ =100% -actual measurement performance/performance benchmark, and hard disk performance loss is calculated. Further, according to the performance loss of the hard disk corresponding to different preset sound pressure levels, determining the loss critical of the hard disk to be predicted in the current frequency band and the target power spectral density corresponding to the loss critical, namely analyzing the PSD value of the hard disk when the loss is close to but the loss is not generated; taking the test result of the central frequency f =3428Hz in each test step in table 1 as an example, the upper and lower boundaries of the 1/9 octave are respectively f1=3299Hz and f2=3563Hz, the sound pressure level in each test step is gradually increased, the corresponding sound pressure level is the second line in table 1, the corresponding PSD spectral line height p is the third line in table 1, and the performance trend of the hard disk in the fifth line is observedLoss of critically corresponding target power spectral density, in p0Denotes that at this frequency p0=0.060（Pa2/Hz）。
In this embodiment, the obtaining the sensitivity of the corresponding frequency segment based on the power spectral density, the target power spectral density, and the performance loss of the hard disk corresponding to the same frequency segment may include: respectively calculating the square difference between the power spectral density of the frequency segment under different preset sound pressure levels and the target power spectral density corresponding to the loss critical of the frequency segment to obtain the overrun noise intensity corresponding to the frequency segment under different preset sound pressure levels; constructing a linear regression model by taking the overrun noise intensity as a first coordinate and taking the performance loss of the hard disk of the frequency segment under different preset sound pressure levels as a second coordinate; and taking the slope of the linear regression model as the sensitivity of the hard disk to be predicted under the frequency band.
It can be understood that, after the target power spectral density of the frequency segment is determined, the out-of-limit noise intensity corresponding to the frequency segment at different preset sound pressure levels is obtained according to the square difference between the power spectral density of the frequency segment at different preset sound pressure levels and the target power spectral density corresponding to the loss criticality of the frequency segment, and the out-of-limit noise intensity corresponding to the frequency segment at different preset sound pressure levels is used
Is expressed in unit of
In particular, using formulae
Calculating the mean square value of the random noise signal of each test step, representing the intensity of the random signal with the unit of
. For each test step of the hard disk performance degradation, applying a formula
Computing the overrun noise levelDegrees, as in the fourth row of table 1. Then, the performance of the hard disk is lost
And the intensity of the overrun noise
A linear regression model was established and the slope K was calculated, as shown in fig. 3, which shows the performance loss of this hard disk under the excitation of 1/9 octave bandwidth noise with center frequency f =3428Hz
And the intensity of the overrun noise
In a relationship of
Where K =0.0087, thereby yielding sensitivity at this frequency. Similarly, for all frequencies, the sensitivity is calculated by the same method to obtain the sensitivities of different frequency bands, and a sensitivity curve as shown in fig. 4 is formed.
Step S12: and acquiring a power spectral density curve corresponding to the measured noise in the case to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise.
In this embodiment, a power spectral density curve corresponding to noise measured in the chassis is collected to obtain power spectral density curve segments corresponding to different frequency segments under the noise measured in the chassis, and it can be understood that the noise in the chassis is formed by multiple complex factors, as shown in fig. 5, a solid line is the power spectral density curve corresponding to the noise measured in the chassis, and a dotted line is a target power spectral density corresponding to each frequency segment.
Step S13: and predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band.
In this embodiment, according to the sensitivity, the target power spectral density, and the power spectral density curve segment corresponding to the same frequency segment, the local performance loss of the hard disk to be predicted in the frequency segment is predicted to obtain the local performance loss of the hard disk to be predicted in different frequency segments, and the overall performance loss of the hard disk to be predicted is obtained according to the local performance loss in each frequency segment.
In this embodiment, the predicting, according to the sensitivity, the target power spectral density, and the power spectral density curve segment corresponding to each frequency segment, the local performance loss of the hard disk to be predicted in different frequency segments, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss in each frequency segment may include: extracting target characteristic parameters of the power spectral density curve segment; the target characteristic parameters comprise a protrusion ratio and a frequency duty ratio; determining a rule according to the target characteristic parameters and a preset integration method, and determining a target integration method for the frequency segments corresponding to the power spectral density curve segments so as to determine a target integration method corresponding to each frequency segment; predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density, the power spectral density curve segment and the target integration method corresponding to each frequency band; and summing the local performance losses corresponding to all the frequency sections to obtain the overall performance loss of the hard disk to be predicted. It can be understood that, according to a great deal of practical experience, in order to improve the prediction accuracy, different integration models should be adopted FOR different PSD spectral line characteristics during calculation, and in this embodiment, a target integration method FOR a Frequency band corresponding to each power spectral density curve segment is determined specifically according to a Projecting Ratio (PR) and a Frequency duty Ratio (FOR) corresponding to the power spectral density curve segment;
taking the local frequency next-time in-chassis measurement noise power spectral density curve and the target power spectral density curve shown in fig. 6 as an example, for a frequency band
To
The curve is a power spectral density curve segment, the transverse line is the target power spectral density, and the calculation method of the frequency duty ratio of the power spectral density curve segment is as follows:
the method for calculating the saliency ratio of the power spectral density curve segments is as follows:
In this embodiment, the predicting, according to the sensitivity, the target power spectral density, the power spectral density curve segment, and the target integration method corresponding to each frequency band, the local performance loss of the hard disk to be predicted in different frequency bands may include: calculating the actual overrun noise intensity of the hard disk to be predicted in the frequency band by using the target integration method based on the target power spectral density and the power spectral density curve segment; and taking the product of the actual overrun noise intensity and the sensitivity of the corresponding frequency band as the local performance loss of the frequency band so as to predict and obtain the local performance loss of the hard disk to be predicted under different frequency bands. The actual out-of-limit noise intensity of the noise in the chassis on each frequency is multiplied by the sensitivity to obtain the local performance loss on each frequency, and finally the local performance loss and the sensitivity are summed to obtain the overall performance loss. The power spectral density curve of the noise in the chassis is set as
Spectral line of critical target power spectral density of hard disk is
Sensitivity at each frequency of
. As shown in fig. 5, the PSD spectral line in the chassis is formed by combining a large number of frequency components, and the performance loss caused by the influence of the PSD spectral line on the hard disk is calculated by the following formula:
wherein i is the serial number of the frequency segment tested by the hard disk single body, N is the total number of the frequency segments,
and with
The sensitivity of the hard disk under each frequency and the actual overrun noise intensity are respectively obtained by integral calculation of PSD spectral lines of the actual overrun noise part.
In this embodiment, the calculating, based on the target power spectral density and the power spectral density curve segment, the actual overrun noise strength of the hard disk to be predicted in the frequency segment by using the target integration method may include: if the target integration method is a first target integration method, integrating the region of the power spectral density curve segment in the frequency band, which exceeds the target power spectral density, so as to obtain the actual overrun noise intensity of the hard disk to be predicted in the frequency band; if the target integration method is a second target integration method, determining a frequency width value of an area where the power spectral density curve segment exceeds the target power spectral density in the frequency segment and a power spectral density maximum value of the power spectral density curve in the frequency segment, and calculating a product of the frequency width value and the power spectral density maximum value to obtain an actual overrun noise intensity of the hard disk to be predicted in the frequency segment. Specifically, how to determine the target integration method of the frequency segment corresponding to each power spectral density curve segment according to the saliency ratio and the frequency duty ratio may be determined according to a preset integration method shown in fig. 7, where a number 1 represents a first target integration method, and a number 2 represents a second target integration method. Taking FIG. 6 as an example, for a frequency bin
To
Calculating the overrun intensity using a first target integration method, i.e. direct integration
I.e. directly calculating the area of the shaded portion in fig. 6, the calculation formula can be simply expressed as:
wherein the content of the first and second substances,
is a power spectral density curve
To
The curve on the upper side of the graph,
for the frequency resolution of the spectral line of the power spectral density, in this embodiment
；
Second target integration, i.e. peak flare integration, i.e. calculation, with
Calculated for the rectangular area of height by this method
Larger than the direct integration method, the calculation formula can be simply expressed as:
。
that is, in this embodiment, the flow of the method for calculating the actual performance loss of the hard disk in the chassis and the distribution condition of the hard disk in the frequency domain may be as shown in fig. 8, according to the protrusion ratio and the frequency duty ratio of the power spectral density curve corresponding to the frequency segment, determining the target integration method corresponding to the frequency segment, then performing integration calculation on the frequency segment by using the target integration method to obtain the actual over-limit noise intensity, obtaining the local performance loss by combining the sensitivities corresponding to the frequency segments, determining whether to traverse each frequency segment by cycling, and when all the frequency segments are traversed, summing to predict the overall performance loss of the hard disk to be predicted in the chassis. It can be seen that, in this embodiment, the sensitivity of the hard disk performance to noise and the critical target power spectral density in the unit test are first calculated, and then the performance loss of the hard disk under the interference of the complex noise in the chassis is predicted; the problem of a hard disk single body can be revealed through a sensitivity test, and mathematical correlation is established between the performance of the hard disk and the noise in the case according to the power spectral density difference between the target power spectral density with critical loss and the actually measured noise, so that the problem of noise signals in the case is directly pointed out, and the loss of related research and development personnel on an analysis method is made up. Moreover, each frequency band corresponds to a local performance loss, so that the performance loss can be decomposed according to the frequency bands, and research and development personnel can clearly know what frequency band noise is the fundamental factor of the problem and how many decibels the noise sound pressure should be improved in each frequency band to solve the problem.
As can be seen from the above, in this embodiment, a noise sensitivity test is performed on a hard disk to be predicted, so as to obtain target power spectral densities corresponding to the hard disk to be predicted under loss criticalities of different frequency bands and sensitivities of the hard disk to be predicted under different frequency bands; acquiring a power spectral density curve corresponding to the measured noise in the case to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise; and predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band. Therefore, the performance loss of the hard disk in the case is predicted by performing the noise sensitivity test on the hard disk to be predicted and combining the hard disk sensitivity test result and the actual noise condition of the case, so that the performance loss prediction of the hard disk in the case under the complex condition is realized, the actual test in the case can be replaced, a PES analysis tool is replaced, and the influence degree of the noise of each frequency on the performance reduction of the hard disk can be analyzed according to the predicted local performance loss.
Correspondingly, the embodiment of the present application further discloses a device for predicting performance loss of a hard disk, as shown in fig. 9, the device includes:
the sensitivity testing module 11 is configured to perform noise sensitivity testing on a hard disk to be predicted to obtain target power spectral densities corresponding to the hard disk to be predicted under loss criticalities of different frequency bands and sensitivities of the hard disk to be predicted under different frequency bands; the loss critical is the edge state from the loss of the hard disk performance to the loss;
a power spectral density curve obtaining module 12, configured to obtain a power spectral density curve corresponding to the measured noise in the chassis, so as to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise;
and the performance loss prediction module 13 is configured to predict local performance losses of the hard disk to be predicted in different frequency bands according to the sensitivity, the target power spectral density, and the power spectral density curve segment corresponding to each frequency band, and obtain an overall performance loss of the hard disk to be predicted according to the local performance loss in each frequency band.
As can be seen from the above, in this embodiment, a noise sensitivity test is performed on a hard disk to be predicted, so as to obtain target power spectral densities corresponding to the hard disk to be predicted under loss criticalities of different frequency bands and sensitivities of the hard disk to be predicted under different frequency bands; acquiring a power spectral density curve corresponding to the measured noise in the chassis to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise; and predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band. Therefore, the performance loss of the hard disk in the case is predicted by performing the noise sensitivity test on the hard disk to be predicted and combining the hard disk sensitivity test result and the actual noise condition of the case, so that the performance loss prediction of the hard disk in the case under the complex condition is realized, the actual test in the case can be replaced, a PES analysis tool is replaced, and the influence degree of the noise of each frequency on the performance reduction of the hard disk can be analyzed according to the predicted local performance loss.
In some embodiments, the sensitivity testing module 11 may specifically include:
the test unit is used for testing the noise sensitivity of the hard disk to be predicted in different frequency bands to obtain the power spectral density of each frequency band under different preset sound pressure levels, the target power spectral density corresponding to the loss critical of each frequency band and the hard disk performance loss of each frequency band under different preset sound pressure levels;
and the sensitivity determining unit is used for obtaining the sensitivity of the corresponding frequency band based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency band.
In some specific embodiments, the test unit may specifically include:
the frequency segment dividing unit is used for dividing a target frequency range according to a preset bandwidth to obtain upper and lower frequency limits and central frequencies of a plurality of frequency segments;
a hard disk performance loss determining unit, configured to calculate power spectral densities of the frequency segments at different preset sound pressure levels, and determine hard disk performance losses of the hard disk to be predicted at different preset sound pressure levels corresponding to the frequency segments;
and the target power spectral density determining unit is used for determining the loss critical of the hard disk to be predicted in the frequency band and the target power spectral density corresponding to the loss critical according to the hard disk performance loss corresponding to different preset sound pressure levels.
In some embodiments, the sensitivity determining unit may specifically include:
the overrun noise intensity determination unit is used for respectively calculating the square differences of the power spectral densities of the frequency segments under different preset sound pressure levels and target power spectral densities corresponding to the loss criticality of the frequency segments to obtain overrun noise intensities corresponding to the frequency segments under different preset sound pressure levels;
the linear regression model building unit is used for building a linear regression model by taking the overrun noise intensity as a first coordinate and taking the performance loss of the hard disk of the frequency band under different preset sound pressure levels as a second coordinate;
and the sensitivity determining unit is used for taking the slope of the linear regression model as the sensitivity of the hard disk to be predicted in the frequency band.
In some embodiments, the performance loss prediction module 13 may specifically include:
a characteristic parameter extraction unit, configured to extract a target characteristic parameter of the power spectral density curve segment; the target characteristic parameters comprise a protrusion ratio and a frequency duty ratio;
the target integration method determining unit is used for determining a target integration method for the frequency segments corresponding to the power spectral density curve segments according to the target characteristic parameters and a preset integration method determining rule so as to determine a target integration method corresponding to each frequency segment;
the local performance loss determining unit is used for predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density, the power spectral density curve segment and the target integration method corresponding to each frequency band;
and the overall performance loss determining unit is used for summing the local performance losses corresponding to all the frequency sections to obtain the overall performance loss of the hard disk to be predicted.
In some specific embodiments, the local performance loss determining unit may specifically include:
the actual overrun noise intensity determination unit is used for calculating the actual overrun noise intensity of the hard disk to be predicted in the frequency band by using the target integration method based on the target power spectral density and the power spectral density curve segment;
and the local performance loss determining unit is used for taking the product of the actual overrun noise intensity and the sensitivity of the corresponding frequency band as the local performance loss of the frequency band so as to predict and obtain the local performance loss of the hard disk to be predicted under different frequency bands.
In some specific embodiments, the actual overrun noise strength determination unit may specifically include:
the first integration unit is used for integrating an area, exceeding the target power spectral density, of the power spectral density curve segment in the frequency band if the target integration method is the first target integration method, so as to obtain the actual out-of-limit noise intensity of the hard disk to be predicted in the frequency band;
and the second integrating unit is configured to determine a frequency width value of an area where the power spectral density curve segment exceeds the target power spectral density in the frequency segment and a power spectral density maximum value of the power spectral density curve in the frequency segment, and calculate a product of the frequency width value and the power spectral density maximum value to obtain an actual overrun noise intensity of the hard disk to be predicted in the frequency segment if the target integration method is a second target integration method.
Further, the embodiment of the present application also discloses an electronic device, which is shown in fig. 10, and the content in the drawing cannot be considered as any limitation to the application scope.
Fig. 10 is a schematic structural diagram of an electronic device 20 according to an embodiment of the present disclosure. The electronic device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input output interface 25, and a communication bus 26. The memory 22 is used for storing a computer program, and the computer program is loaded and executed by the processor 21 to implement the relevant steps in the hard disk performance loss prediction method disclosed in any of the foregoing embodiments.
In this embodiment, the power supply 23 is configured to provide a working voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and an external device, and a communication protocol followed by the communication interface is any communication protocol applicable to the technical solution of the present application, and is not specifically limited herein; the input/output interface 25 is configured to obtain external input data or output data to the outside, and a specific interface type thereof may be selected according to specific application requirements, which is not specifically limited herein.
In addition, the storage 22 is used as a carrier for resource storage, and may be a read-only memory, a random access memory, a magnetic disk or an optical disk, etc., and the resources stored thereon include an operating system 221, a computer program 222, data 223 including sensitivity, etc., and the storage may be a transient storage or a permanent storage.
The operating system 221 is used for managing and controlling each hardware device and the computer program 222 on the electronic device 20, so as to realize the operation and processing of the mass data 223 in the memory 22 by the processor 21, and may be Windows Server, Netware, Unix, Linux, and the like. The computer program 222 may further include a computer program that can be used to perform other specific tasks in addition to the computer program that can be used to perform the hard disk performance loss prediction method performed by the electronic device 20 disclosed in any of the foregoing embodiments.
Further, an embodiment of the present application further discloses a computer storage medium, where computer-executable instructions are stored in the computer storage medium, and when the computer-executable instructions are loaded and executed by a processor, the steps of the hard disk performance loss prediction method disclosed in any of the foregoing embodiments are implemented.
The embodiments are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same or similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should also be 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 an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The method, the device, the equipment and the medium for predicting the performance loss of the hard disk provided by the invention are described in detail, a specific example is applied in the text to explain the principle and the implementation mode of the invention, and the description of the embodiment is only used for helping to understand the method and the core idea of the invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (8)
1. A method for predicting performance loss of a hard disk is characterized by comprising the following steps:
carrying out noise sensitivity test on a hard disk to be predicted to obtain target power spectral density corresponding to the hard disk to be predicted under loss criticality of different frequency bands and sensitivity of the hard disk to be predicted under different frequency bands; the loss critical is the edge state from the loss of the hard disk performance to the loss; the noise sensitivity test is used for testing the performance loss of the hard disk under the noise interference of different frequencies and different sound pressure levels;
acquiring a power spectral density curve corresponding to the measured noise in the case to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise;
predicting local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band;
the method for testing the noise sensitivity of the hard disk to be predicted to obtain the target power spectral density corresponding to the hard disk to be predicted under the loss criticality of different frequency bands and the sensitivity of the hard disk to be predicted under different frequency bands comprises the following steps:
carrying out noise sensitivity tests of different frequency segments on the hard disk to be predicted to obtain the power spectral density of each frequency segment under different preset sound pressure levels, the target power spectral density corresponding to the loss critical of each frequency segment and the hard disk performance loss of each frequency segment under different preset sound pressure levels;
obtaining the sensitivity of the corresponding frequency band based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency band;
the predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band includes:
extracting target characteristic parameters of the power spectral density curve segment; the target characteristic parameters comprise a protrusion ratio and a frequency duty ratio;
determining a rule according to the target characteristic parameters and a preset integration method, and determining a target integration method for the frequency segments corresponding to the power spectral density curve segments so as to determine a target integration method corresponding to each frequency segment;
predicting local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity corresponding to each frequency band, the target power spectral density, the power spectral density curve segment and the target integration method;
and summing the local performance losses corresponding to all the frequency sections to obtain the overall performance loss of the hard disk to be predicted.
2. The method for predicting the performance loss of the hard disk according to claim 1, wherein the testing the noise sensitivity of the hard disk to be predicted in different frequency bands to obtain the power spectral density of each frequency band under different preset sound pressure levels, the target power spectral density corresponding to the loss threshold of each frequency band, and the performance loss of the hard disk of each frequency band under different preset sound pressure levels comprises:
dividing a target frequency range according to a preset bandwidth to obtain upper and lower frequency limits and a center frequency of a plurality of frequency segments;
calculating the power spectral density of the frequency segment under different preset sound pressure levels, and determining the hard disk performance loss of the hard disk to be predicted under different preset sound pressure levels corresponding to the frequency segment;
and determining the loss critical of the hard disk to be predicted in the frequency band and the target power spectral density corresponding to the loss critical according to the hard disk performance loss corresponding to different preset sound pressure levels.
3. The method of claim 1, wherein the obtaining the sensitivity of the corresponding frequency segment based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency segment comprises:
respectively calculating the square difference between the power spectral density of the frequency band under different preset sound pressure levels and the target power spectral density corresponding to the loss criticality of the frequency band to obtain the overrun noise intensity corresponding to the frequency band under different preset sound pressure levels;
constructing a linear regression model by taking the overrun noise intensity as a first coordinate and taking the performance loss of the hard disk of the frequency segment under different preset sound pressure levels as a second coordinate;
and taking the slope of the linear regression model as the sensitivity of the hard disk to be predicted under the frequency band.
4. The method for predicting the performance loss of the hard disk according to claim 1, wherein the predicting the local performance loss of the hard disk to be predicted in different frequency bands according to the sensitivity, the target power spectral density, the power spectral density curve segment and the target integration method corresponding to each frequency band comprises:
calculating the actual overrun noise intensity of the hard disk to be predicted in the frequency band by using the target integration method based on the target power spectral density and the power spectral density curve segment;
and taking the product of the actual overrun noise intensity and the sensitivity of the corresponding frequency band as the local performance loss of the frequency band so as to predict and obtain the local performance loss of the hard disk to be predicted under different frequency bands.
5. The method for predicting the performance loss of the hard disk according to claim 4, wherein the calculating the actual overrun noise strength of the hard disk to be predicted in the frequency band by using the target integration method based on the target power spectral density and the power spectral density curve segment comprises:
if the target integration method is a first target integration method, integrating the region of the power spectral density curve segment in the frequency band, which exceeds the target power spectral density, so as to obtain the actual overrun noise intensity of the hard disk to be predicted in the frequency band;
if the target integration method is a second target integration method, determining a frequency width value of an area where the power spectral density curve segment exceeds the target power spectral density in the frequency segment and a power spectral density maximum value of the power spectral density curve in the frequency segment, and calculating a product of the frequency width value and the power spectral density maximum value to obtain an actual overrun noise intensity of the hard disk to be predicted in the frequency segment.
6. A hard disk performance loss prediction apparatus, comprising:
the system comprises a sensitivity testing module, a data processing module and a data processing module, wherein the sensitivity testing module is used for testing the noise sensitivity of a hard disk to be predicted so as to obtain the corresponding target power spectral density of the hard disk to be predicted under the loss criticality of different frequency bands and the sensitivity of the hard disk to be predicted under different frequency bands; the loss critical is the edge state from the loss of the hard disk performance to the loss; the noise sensitivity test is used for testing the performance loss of the hard disk under the noise interference of different frequencies and different sound pressure levels;
the power spectral density curve acquisition module is used for acquiring a power spectral density curve corresponding to the measured noise in the chassis so as to obtain power spectral density curve segments corresponding to different frequency segments under the measured noise;
the performance loss prediction module is used for predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density and the power spectral density curve segment corresponding to each frequency band, and obtaining the overall performance loss of the hard disk to be predicted according to the local performance loss under each frequency band;
the sensitivity testing module is further used for testing the noise sensitivity of the hard disk to be predicted in different frequency bands to obtain the power spectral density of each frequency band under different preset sound pressure levels, the target power spectral density corresponding to the loss critical of each frequency band and the performance loss of the hard disk of each frequency band under different preset sound pressure levels; obtaining the sensitivity of the corresponding frequency band based on the power spectral density, the target power spectral density and the performance loss of the hard disk corresponding to the same frequency band;
wherein the performance loss prediction module point is further configured to extract target characteristic parameters of the power spectral density curve segment; the target characteristic parameters comprise a protrusion ratio and a frequency duty ratio; determining a rule according to the target characteristic parameters and a preset integration method, and determining a target integration method for the frequency segments corresponding to the power spectral density curve segments so as to determine a target integration method corresponding to each frequency segment; predicting the local performance loss of the hard disk to be predicted under different frequency bands according to the sensitivity, the target power spectral density, the power spectral density curve segment and the target integration method corresponding to each frequency band; and summing the local performance losses corresponding to all the frequency sections to obtain the overall performance loss of the hard disk to be predicted.
7. An electronic device, comprising:
a memory for storing a computer program;
a processor for executing the computer program to implement the hard disk performance loss prediction method according to any of claims 1 to 5.
8. A computer-readable storage medium for storing a computer program; wherein the computer program when executed by the processor implements the hard disk performance loss prediction method of any of claims 1 to 5.
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