CN117591383B - Method for judging working state of server based on server sound - Google Patents

Method for judging working state of server based on server sound Download PDF

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CN117591383B
CN117591383B CN202410080229.4A CN202410080229A CN117591383B CN 117591383 B CN117591383 B CN 117591383B CN 202410080229 A CN202410080229 A CN 202410080229A CN 117591383 B CN117591383 B CN 117591383B
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server
sound
sound signals
decoding
microphone
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CN117591383A (en
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左超
蒋敏
唐琪
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Cetc Shentai Information Technology Co ltd
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Cetc Shentai Information Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/30—Monitoring
    • G06F11/3055—Monitoring arrangements for monitoring the status of the computing system or of the computing system component, e.g. monitoring if the computing system is on, off, available, not available
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/10—Pre-processing; Data cleansing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G06F18/2132—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on discrimination criteria, e.g. discriminant analysis
    • G06F18/21322—Rendering the within-class scatter matrix non-singular
    • G06F18/21324—Rendering the within-class scatter matrix non-singular involving projections, e.g. Fisherface techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
    • G06F18/2134—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods based on separation criteria, e.g. independent component analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/29—Graphical models, e.g. Bayesian networks
    • G06F18/295—Markov models or related models, e.g. semi-Markov models; Markov random fields; Networks embedding Markov models
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G10L21/0216—Noise filtering characterised by the method used for estimating noise
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0272—Voice signal separating
    • G10L21/028—Voice signal separating using properties of sound source
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
    • G10L25/48—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use
    • G10L25/51—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 specially adapted for particular use for comparison or discrimination
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/02—Preprocessing
    • G06F2218/04—Denoising
    • G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/08—Feature extraction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12—Classification; Matching
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention relates to the technical field of server state detection, in particular to a method for judging the working state of a server based on server sound. The method comprises the following steps: step 1: collecting sound signals generated by the server during operation through a microphone; step 2: noise reduction processing is carried out on the sound signal by utilizing a wavelet transformation method; step 3: decoding and classifying the server sound signals by using a decoding method of the motion unit action potential sequence; step 4: different server operating states are matched according to the classified sound signals. The invention provides powerful support for daily work of operation and maintenance personnel, shortens the time of fault discovery and problem positioning treatment, and ensures safe and stable operation of servers in a machine room. The invention greatly reduces the workload of operation and maintenance personnel, saves the operation and maintenance cost of the system and has wide market popularization value.

Description

Method for judging working state of server based on server sound
Technical Field
The invention relates to the technical field of server state detection, in particular to a method for judging the working state of a server based on server sound.
Background
For a company, a machine room can be said to be one of the most important supporting infrastructures. The operation and maintenance of the machine room are very critical, so how to optimize the operation and maintenance of the machine room becomes a non-negligible problem. The server is one of the core devices of the machine room, so that the server needs to be periodically inspected, maintained and upgraded, and the stability and the safety of the server are ensured.
At present, the traditional server inspection mode is completed through manual operation. This approach is not only inefficient, but also wasteful of human resources, as there is also a potential safety hazard if improperly operated. There is a need to develop a method for determining the operating state of a server according to the sound generated by the operation of the server.
Disclosure of Invention
The invention aims to provide a method for judging the working state of a server based on server sound, which solves the problems that the prior art only can adopt manual inspection and cannot realize timely and effective processing.
In order to solve the technical problems, the invention provides a method for judging the working state of a server based on server sound, which comprises the following steps:
step 1: collecting sound signals generated by the server during operation through a microphone;
step 2: noise reduction processing is carried out on the sound signal by utilizing a wavelet transformation method;
step 3: decoding and classifying the server sound signals by using a decoding method of the motion unit action potential sequence;
step 4: different server operating states are matched according to the classified sound signals.
Preferably, the microphone in the step 1 is an embedded microphone, and the microphone is a device for converting sound waves into electric signals, and the working principle of the microphone is that the electric signals are generated through vibration diaphragms or vibration signals, the sound wave signals are converted into the electric signals, then the electric signals are subjected to analog-to-digital conversion through an internal or external sound card of a computer, and finally the analog signals are converted into digital signals and transmitted to the computer, so that the functions of voice recording, voice recognition and the like are realized.
Preferably, the step 2 specifically includes: selecting a process and a threshold value by utilizing a wavelet noise reduction criterion, and carrying out 4-layer decomposition on an original signal by adopting a sym8 wavelet basis; and the method for selecting the threshold value adopts the principle of maximum and minimum.
Preferably, the step 3 specifically includes: the method comprises the steps of extracting hidden information in server sound signals by a rapid independent component analysis method based on negative entropy in a blind source separation algorithm, extracting features by a local retention projection algorithm, classifying by a hidden Markov model, and finally decoding and classifying several different server sound signals.
Preferably, the step 4 specifically includes: the server sound signals classified according to decoding can be matched with different working states of the server, wherein the working states comprise but are not limited to: boot, self-test, normal operation, cpu overload, insufficient memory, suspend and crash, etc.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a method for judging the working state of a server based on server sound, which is similar to a doctor with experience, and can judge the physical state of a patient according to different sounds emitted by internal organs of the patient by means of a stethoscope. The invention provides powerful support for daily work of operation and maintenance personnel, shortens the time of fault discovery and problem positioning treatment, and ensures safe and stable operation of servers in a machine room. The invention greatly reduces the workload of operation and maintenance personnel, saves the operation and maintenance cost of the system and has wide market popularization value.
Drawings
Fig. 1 is a flowchart of a method for determining a working state of a server based on server sound provided by the invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and the specific examples. The advantages and features of the present invention will become more apparent from the following description. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the invention.
As shown in fig. 1, the embodiment of the invention specifically discloses a method for judging the working state of a server based on the sound of the server. The present embodiment collects sound information of the server through the microphone. The microphone is a device for converting sound waves into electric signals, and the working principle is that the electric signals are generated through vibration diaphragms or vibration signals, the sound wave signals are converted into the electric signals, analog-digital conversion is carried out through an internal or external sound card of a computer, and finally, the analog signals are converted into digital signals to be transmitted to the computer, so that the functions of voice recording, voice recognition and the like are realized. Depending on the type of microphone and the application scenario, it may be classified into a pointing microphone, a stereo microphone, an embedded microphone, etc. The use of microphones to collect audio information is the basis and premise for computers to perform various speech applications. The present embodiment is preferably an embedded microphone.
The method specifically comprises the following steps: firstly, the sound of the server is collected through an embedded microphone, and the sound signal of the server is converted into an electrical signal which can be conveniently processed. And then noise reduction processing is carried out on the obtained signal by utilizing the wavelet transformation principle. And 4 layers of decomposition is carried out on an original signal by adopting a sym8 wavelet basis, and finally experiments show that the noise reduction effect is better by a method of selecting a threshold value by using a principle of maximum and minimum. Moreover, the embodiment provides a decoding method using the motion unit action potential sequence. The method adopts a rapid independent component analysis method based on negative entropy in a blind source separation algorithm to extract hidden information in signals, uses a local reservation projection algorithm to extract characteristics, classifies the extracted characteristics through a hidden Markov model, and finally decodes working states of a server such as startup, self-checking, normal operation, cpu overload, insufficient memory, suspension, dead halt and the like.
The above description is only illustrative of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention, and any alterations and modifications made by those skilled in the art based on the above disclosure shall fall within the scope of the appended claims.

Claims (3)

1. The method for judging the working state of the server based on the server sound is characterized by comprising the following steps:
step 1: collecting sound signals generated by the server during operation through a microphone;
step 2: noise reduction processing is carried out on the sound signal by utilizing a wavelet transformation method;
the step 2 specifically comprises the following steps: selecting a process and a threshold value by utilizing a wavelet noise reduction criterion, and carrying out 4-layer decomposition on an original signal by adopting a sym8 wavelet basis; and the method for selecting the threshold value adopts the principle of maximum and minimum;
step 3: decoding and classifying the server sound signals by using a decoding method of the motion unit action potential sequence;
the step 3 specifically comprises the following steps: extracting hidden information in the server sound signals by adopting a rapid independent component analysis method based on negative entropy in a blind source separation algorithm, extracting features by using a local retention projection algorithm, classifying by using a hidden Markov model, and finally decoding and classifying several different server sound signals;
step 4: different server operating states are matched according to the classified sound signals.
2. The method of claim 1, wherein the microphone in step 1 is an embedded microphone.
3. The method for determining the operating state of the server based on the server sound according to claim 1, wherein the step 4 is specifically: the server sound signals classified according to decoding can be matched with different working states of the server, wherein the working states comprise but are not limited to: boot, self-test, normal operation, cpu overload, memory starvation, suspend, and crash.
CN202410080229.4A 2024-01-19 2024-01-19 Method for judging working state of server based on server sound Active CN117591383B (en)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103443649A (en) * 2011-03-03 2013-12-11 高通股份有限公司 Systems, methods, apparatus, and computer-readable media for source localization using audible sound and ultrasound
KR101864388B1 (en) * 2018-03-29 2018-06-04 주식회사 경림이앤지 Peculiar sound detection system and method to be cancelled out the noise by using array microphone in CCTV camera system
CN112648220A (en) * 2019-10-10 2021-04-13 天津科技大学 Fan fault diagnosis method based on wavelet-approximate entropy
CN115376526A (en) * 2022-08-23 2022-11-22 国网江苏省电力有限公司泰州供电分公司 Power equipment fault detection method and system based on voiceprint recognition
CN115932561A (en) * 2022-07-29 2023-04-07 东南大学 High-voltage circuit breaker mechanical fault online diagnosis method based on voiceprint recognition
KR20230064011A (en) * 2021-11-01 2023-05-10 정익중 Analysis system of circumstantial judgement based on voice with image pattern and operating method thereof

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103443649A (en) * 2011-03-03 2013-12-11 高通股份有限公司 Systems, methods, apparatus, and computer-readable media for source localization using audible sound and ultrasound
KR101864388B1 (en) * 2018-03-29 2018-06-04 주식회사 경림이앤지 Peculiar sound detection system and method to be cancelled out the noise by using array microphone in CCTV camera system
CN112648220A (en) * 2019-10-10 2021-04-13 天津科技大学 Fan fault diagnosis method based on wavelet-approximate entropy
KR20230064011A (en) * 2021-11-01 2023-05-10 정익중 Analysis system of circumstantial judgement based on voice with image pattern and operating method thereof
CN115932561A (en) * 2022-07-29 2023-04-07 东南大学 High-voltage circuit breaker mechanical fault online diagnosis method based on voiceprint recognition
CN115376526A (en) * 2022-08-23 2022-11-22 国网江苏省电力有限公司泰州供电分公司 Power equipment fault detection method and system based on voiceprint recognition

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