CN105021276A - Electric appliance fault diagnosis method and apparatus and electric appliance - Google Patents
Electric appliance fault diagnosis method and apparatus and electric appliance Download PDFInfo
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- CN105021276A CN105021276A CN201510465912.0A CN201510465912A CN105021276A CN 105021276 A CN105021276 A CN 105021276A CN 201510465912 A CN201510465912 A CN 201510465912A CN 105021276 A CN105021276 A CN 105021276A
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Abstract
The invention discloses an electric appliance fault diagnosis method and an apparatus and an electric appliance. The electric appliance of the present invention comprises a part that vibrates in work process; the electric appliance fault diagnosis method comprises the steps of detecting the vibration signal of the electric appliance; extracting vibration characteristics of the vibration signal; and determining the part that has a fault based on the vibration characteristics of the vibration signal. According to the invention, the fault diagnosis efficiency of the electric appliance is raised.
Description
Technical field
The present invention relates to detection field, in particular to a kind of Fault Diagnosis of Electrical Appliance and device and electrical equipment.
Background technology
Along with growth in the living standard, various household electrical appliance constantly incorporate the life of people, bring great convenience to life.Such as, range hood has become popular household electrical appliance, gets rid of oil smoke when being convenient for people to cook.But for the cooking method of big fire quick-fried, easily produce the flue gas of a large amount of oil smoke, water vapor and burning during the cooking in kitchen, people are more and more concerned about the quality of range hood suction effect.
Range hood comprises motor and blower fan, improve the suction effect of range hood, in fact the motor speed of range hood and the exhaust air rate of blower fan is namely improved, but, while the raising motor speed of range hood and the exhaust air rate of blower fan, inevitably considerably increase noise signal.The noise signal part that range hood increases derives from the mechanical vibration noise of the moving components (there are the parts of vibration in work) such as the wind wheel of rotor and blower fan, and the vibration signal formed by mechanical vibration noise contains the failure message of potential range hood.
For being similar to this electrical equipment that there is vibrating mass at work of range hood, the mechanical vibration noise of vibrating mass contains potential apparatus failure information, but, that which parts there occurs fault actually, need to search one by one numerous parts of electrical equipment, sometimes even need dismounting complete machine to search the parts broken down, this method for diagnosing faults not only bothers, and need the cost plenty of time to go checking, affect detection efficiency.
For the inefficient problem of the fault diagnosis of electrical equipment in correlation technique, at present effective solution is not yet proposed.
Summary of the invention
Fundamental purpose of the present invention is to provide a kind of Fault Diagnosis of Electrical Appliance and device and electrical equipment, with the inefficient problem of the fault diagnosis solving electrical equipment.
To achieve these goals, according to an aspect of the present invention, provide a kind of Fault Diagnosis of Electrical Appliance, wherein, electrical equipment comprises the parts that there is vibration in the course of the work, and the method comprises: the vibration signal detecting electrical equipment; Extract the vibration performance of vibration signal; And according to there are the parts of fault in the vibration performance determination electrical equipment of vibration signal.
Further, the vibration performance extracting vibration signal comprises: the time-frequency spectrum picture being obtained vibration signal by the vibration performance extracting vibration signal, parts according to there is fault in the vibration performance determination electrical equipment of vibration signal comprise: by amplitude and the frequency of time-frequency spectrum graphical analysis vibration signal, obtain the time-frequency characteristics of vibration signal; By there are the parts of fault in the time-frequency characteristics determination electrical equipment of vibration signal.
Further, the vibration signal detecting electrical equipment comprises: carry out noise reduction process to vibration signal, obtain the vibration signal after noise reduction process, and the vibration performance extracting vibration signal comprises: the vibration performance extracting the vibration signal after noise reduction process.
Further, the vibration signal detecting electrical equipment comprises; Detect the vibration signal of electrical equipment, obtain the first vibration signal, wherein, the first vibration signal is non-stationary signal; Carry out data sectional process to the first vibration signal, obtain the second vibration signal, wherein, the second vibration signal is stationary signal, and the vibration performance extracting vibration signal comprises: the vibration performance extracting the second vibration signal.
Further, data sectional process is carried out to the first vibration signal and comprises: by the rectangular window adding predetermined width, data sectional process is carried out to the first vibration signal, obtain multiple signal segment, wherein, there is between multiple signal segment the lap of preset ratio; To the overlapped signal between the adjacent signals section in multiple signal segment through repeatedly noise reduction, obtain multiple noise reduction process result; And process is averaging to multiple noise reduction process result, obtain the second vibration signal.
Further, electrical equipment is range hood, range hood comprises motor, the vibration signal detecting electrical equipment comprises: utilize displacement transducer to gather the radial vibration signal of the rotor of motor, the vibration performance extracting vibration signal comprises: the vibration performance extracting radial vibration signal, the parts according to there is fault in the vibration performance determination electrical equipment of vibration signal comprise: judge whether motor exists fault according to the vibration performance of radial vibration signal.
To achieve these goals, according to a further aspect in the invention, additionally provide a kind of electric equipment fault diagnosis device, wherein, electrical equipment comprises the parts that there is vibration in the course of the work, and this device comprises: detecting unit, for detecting the vibration signal of electrical equipment; Extraction unit, for extracting the vibration performance of vibration signal; And determining unit, for according to the parts that there is fault in the vibration performance determination electrical equipment of vibration signal.
Further, the extraction unit vibration performance be used for by extracting vibration signal obtains the time-frequency spectrum picture of vibration signal, determining unit comprises: analysis module, for passing through amplitude and the frequency of time-frequency spectrum graphical analysis vibration signal, obtains the time-frequency characteristics of vibration signal; And determination module, for the parts by there is fault in the time-frequency characteristics determination electrical equipment of vibration signal.
Further, electric equipment fault diagnosis device also comprises: noise reduction processing unit, for carrying out noise reduction process to vibration signal, obtains the vibration signal after noise reduction process, and wherein, extraction unit is for extracting the vibration performance of the vibration signal after noise reduction process.
Further, detecting unit comprises: detection module, for detecting the vibration signal of electrical equipment, obtains the first vibration signal, and wherein, the first vibration signal is non-stationary signal; And staging treating module, for carrying out data sectional process to the first vibration signal, obtain the second vibration signal, wherein, the second vibration signal is stationary signal, and wherein, extraction unit is for extracting the vibration performance of the second vibration signal.
Further, staging treating module comprises: staging treating submodule, carries out data sectional process for the rectangular window by adding predetermined width to the first vibration signal, obtains multiple signal segment, wherein, has the lap of preset ratio between multiple signal segment; Noise reduction module, for the overlapped signal between the adjacent signals section in multiple signal segment through repeatedly noise reduction, obtain multiple noise reduction process result; And computing module, for being averaging process to multiple noise reduction process result, obtain the second vibration signal.
Further, electrical equipment is range hood, range hood comprises motor, the radial vibration signal of detecting unit for utilizing displacement transducer to gather the rotor of motor, extraction unit is for extracting the vibration performance of radial vibration signal, according to the vibration performance of radial vibration signal, determining unit judges whether motor exists fault.
To achieve these goals, according to a further aspect in the invention, additionally provide a kind of electrical equipment, this electrical equipment comprises any one electric equipment fault diagnosis device provided by the invention.
Further, this electrical equipment is range hood.
Pass through the present invention, adopt the vibration signal detecting electrical equipment, then the vibration performance of vibration signal is extracted, again according to the parts that there is fault in the vibration performance determination electrical equipment of vibration signal, solve the inefficient problem of the fault diagnosis of electrical equipment in prior art, and then reach the effect of the fault diagnosis efficiency improving electrical equipment.
Accompanying drawing explanation
The accompanying drawing forming a application's part is used to provide a further understanding of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:
Fig. 1 is the process flow diagram of the Fault Diagnosis of Electrical Appliance according to the embodiment of the present invention;
Fig. 2 is the process flow diagram of the denoise processing method according to the embodiment of the present invention;
Fig. 3 is the process flow diagram of the method for diagnosing faults of range hood according to the embodiment of the present invention;
Fig. 4 is the schematic diagram of electric equipment fault diagnosis device according to a first embodiment of the present invention;
Fig. 5 is the schematic diagram of electric equipment fault diagnosis device according to a second embodiment of the present invention;
Fig. 6 is the schematic diagram of electric equipment fault diagnosis device according to a third embodiment of the present invention;
Fig. 7 is the schematic diagram of electric equipment fault diagnosis device according to a fourth embodiment of the present invention;
Fig. 8 is the schematic diagram of electric equipment fault diagnosis device according to a fifth embodiment of the present invention;
Fig. 9 is the schematic diagram of the range hood according to the embodiment of the present invention; And
Figure 10 is the schematic diagram of the displacement transducer according to the embodiment of the present invention.
Embodiment
It should be noted that, when not conflicting, the embodiment in the application and the feature in embodiment can combine mutually.Below with reference to the accompanying drawings and describe the present invention in detail in conjunction with the embodiments.
The application's scheme is understood better in order to make those skilled in the art person, below in conjunction with the accompanying drawing in the embodiment of the present application, technical scheme in the embodiment of the present application is clearly and completely described, obviously, described embodiment is only the embodiment of the application's part, instead of whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not making the every other embodiment obtained under creative work prerequisite, all should belong to the scope of the application's protection.
It should be noted that, term " first ", " second " etc. in the instructions of the application and claims and above-mentioned accompanying drawing are for distinguishing similar object, and need not be used for describing specific order or precedence.Should be appreciated that the data used like this can be exchanged, in the appropriate case so that the embodiment of the application described herein.In addition, term " comprises " and " having " and their any distortion, intention is to cover not exclusive comprising, such as, contain those steps or unit that the process of series of steps or unit, method, system, product or equipment is not necessarily limited to clearly list, but can comprise clearly do not list or for intrinsic other step of these processes, method, product or equipment or unit.
Fig. 1 is the process flow diagram of the Fault Diagnosis of Electrical Appliance according to the embodiment of the present invention, and the method is used for carrying out fault diagnosis to electrical equipment, and it should be noted that, this electrical equipment comprises the parts that there is vibration in the course of the work.As shown in Figure 1, this Fault Diagnosis of Electrical Appliance comprises the following steps:
Step S11, detects the vibration signal of electrical equipment.
Electrical equipment containing vibrating mass, in the course of work, especially can produce noise signal in start-up course, and such as, for the electrical equipment comprising rotor, wherein the noise signal of a part derives from the mechanical vibration noise of the vibrating mass such as rotor.In order to monitor the duty of electrical equipment more accurately and rapidly, thus to potential diagnosing malfunction, in this embodiment, the vibration signal of electrical equipment is gathered.
The detection of the vibration signal of electrical equipment can utilize signal detection device, and such as, utilizes displacement transducer to detect.Detected the vibration signal of electrical equipment by signal detection device, obtain analog detection signal, now signal is the signal of non-stationary.After obtaining analog detection signal, sample quantization process is carried out to analog detection signal, obtains digital detection signal, digital detection signal is input to signal processing system, signal processing system carries out noise reduction process to the vibration signal of electrical equipment, obtains the vibration signal after noise reduction process.Perform follow-up electric equipment fault diagnosis by the vibration signal after noise reduction process, be conducive to the accuracy improving fault diagnosis.
Can be obtained the vibration signal of noise reduction process by the method shown in Fig. 2, as shown in Figure 2, the method comprises the following steps:
Step S111, obtains the digital signal of the first vibration signal.
Simulating signal, for reflecting the Vibration Condition of electrical equipment, if the signal of the electrical equipment detected is simulating signal, is then converted into digital signal by the first vibration signal.The first vibration signal detected is generally the signal of non-stationary, comprises noise signal, in this step, obtains the digital signal x (n) detecting the non-stationary obtained, wherein, and n=1,2 ..., N.
Step S112, Overlapping Fragment first vibration signal.
Staging treating is carried out to the first vibration signal, such as, by the rectangular window adding predetermined width, data sectional process is carried out to the first vibration signal, obtain multiple signal segment.In order to reduce the noise reduction error of the first vibration signal contiguous segmentation, have the lap of preset ratio between multiple signal segment, then Overlapping Fragment first vibration signal can be expressed as:
Q＝[ceil(N-L)*(1-α)/L]+1
Wherein, Q is total segments of signal, and N is the total length of the signal data recorded, initialization null matrix S (Q, N), and the length of setting segment data is L, make α=max (1, k-n+1), wherein, k=1,2,, L, n=1,2 ..., N.
Step S113, performs svd inverse operation process to multiple signal segment.
After Overlapping Fragment is carried out to the first vibration signal, adopt svd (SingularValue Decomposition, referred to as SVD) inverse calculation to process to multiple signal segment, obtain the restructuring matrix of the stationary signal based on SVD.Particularly, with the i-th segment signal structure Hankel type matrix A (i), first according to formula ∑=U
ta (i) V carries out SVD to A (i), obtain the singular value of A (i), wherein, U and V is the singular vector of A (i) respectively, ∑ is the diagonal matrix of A (i), value on its diagonal matrix is the singular value of A (i), determines the number of effective singular value of A (i); Again according to formula A
m(i)=U ∑ V
t, SVD inverse operation is carried out to A (i), obtains restructuring matrix A
mi (), to A
mi the anti-diagonal element in () is averaging and then obtains de-noising signal.
Step S114, obtains the signal after process.
After svd inverse operation process is adopted to the corresponding signal section of the first vibration signal, obtain the first vibration signal of the corresponding signal section after noise reduction, can be expressed as:
Wherein, k=1,2 ..., L, α=max (1, k-n+1), β=min (m, k).
By x
1k () assignment is in i-th row of S (Q, N).
Step S115, judges whether multiple signal segment is disposed.
SVD inverse operation process is carried out to multiple signal segment circulations of the first vibration signal, now, SVD inverse operation process is carried out once to each signal segment of the first vibration signal, whether SVD inverse operation is disposed to judge multiple signal segments of the first vibration signal, particularly, if the i-th segment signal has exceeded total segments Q of signal, then signal segment SVD inverse operation has been disposed, perform step S116, obtain the signal after noise reduction.If the i-th segment signal is less than total segments Q of signal, then multiple signal segments of the first vibration signal do not have SVD inverse operation to be disposed, i=i+1, perform step S113, proceed SVD inverse operation restructuring matrix A to matrix A (i)
m(i), and to A
mi the anti-diagonal element of () is averaging, according to the block signal that this determination methods circular treatment is all, until multiple signal segments of vibration signal all SVD inverse operation be disposed, namely i > Q sets up, thus the overlapped signal between the adjacent signals section of repeatedly noise reduction first vibration signal, obtain the first vibration signal of the correspondent section after noise reduction, obtain multiple noise reduction process result.
Step S116, is averaging the noise reduction process result of multiple signal segment.
At all block signals of complete first vibration signal of circular treatment, after multiple noise reduction process results of the overlapped signal between the adjacent signals section obtaining the first vibration signal, nonzero element is carried out to each section of multiple noise reduction process result and is averaging calculating, obtain the second vibration signal.Specifically all nonzero elements that S (Q, N) respectively arranges are averaging, the second vibration signal x'(n can be obtained), n=1,2 ..., N.Second vibration signal is the stationary signal after noise reduction, the vibration signal ripple under elimination impulse disturbances, retains the real vibration performance of mechanical oscillation signal.
Step S12, extracts the vibration performance of vibration signal.
After detecting and collect the vibration signal of electrical equipment, obtained the time-frequency spectrum picture of vibration signal by the vibration performance extracting vibration signal, the vibration performance extracting vibration signal comprises: the vibration performance extracting the vibration signal after noise reduction process.Preferably, obtained the time-frequency spectrum picture of the second vibration signal by the vibration performance extracting the second vibration signal, the vibration performance extracting the second vibration signal comprises: the vibration performance extracting the second vibration signal after noise reduction process.
Step S13, according to the parts that there is fault in the vibration performance determination electrical equipment of vibration signal.
By amplitude and the frequency of time-frequency spectrum graphical analysis vibration signal, obtain the time-frequency characteristics of vibration signal, by there are the parts of fault in the time-frequency characteristics determination electrical equipment of vibration signal.Preferably, by amplitude and the frequency of time-frequency spectrum graphical analysis second vibration signal, obtain the time-frequency characteristics of the second vibration signal, then pass through the time-frequency characteristics of the second vibration signal, extract the time-frequency characteristics of fault-signal, thus determine the parts that there is fault in electrical equipment.
The Fault Diagnosis of Electrical Appliance of this embodiment adopts the vibration signal detecting electrical equipment, then the vibration performance of vibration signal is extracted, again according to the parts that there is fault in the vibration performance determination electrical equipment of vibration signal, and then reach the effect of the fault diagnosis efficiency improving electrical equipment.
Electrical equipment in the embodiment of the present invention can be range hood, and range hood comprises the parts such as motor, wind wheel, spiral case and centrifugation blade.For range hood, Fault Diagnosis of Electrical Appliance is described below.
Fig. 3 is the process flow diagram of the method for diagnosing faults of range hood according to the embodiment of the present invention, and as shown in Figure 3, the method for diagnosing faults of this range hood comprises the following steps:
Step S21, gathers vibration signal.
In the operational process of range hood, signal acquisition device is utilized to gather the vibration signal at the motor place of range hood.Such as, by the radial vibration signal utilizing displacement transducer to gather rotor in the process that operates at range hood, obtain the first vibration signal, the first vibration signal is now non-stationary signal.
Step S22, inputted vibration signal is to disposal system.
Synchronously be input to by the radial vibration signal of rotor in the disposal system be connected with the other end of displacement transducer, disposal system can be computer.The vibration signal of non-stationary is converted into digital signal by computer expert's over-sampling quantification treatment, is set to the function with certain data length.
Step S23, SVD noise reduction process.
Obtain the digital signal being input to the non-stationary of signal processing system.By the rectangular window adding predetermined width, data sectional process is carried out to the first vibration signal, obtain multiple signal segment.In order to reduce the noise reduction error of the first vibration signal contiguous segmentation, there is between multiple signal segment the lap of preset ratio.After Overlapping Fragment is carried out to the first vibration signal, the first vibration signal is processed.Preferably, SVD inverse calculation is adopted to process to multiple signal segments of the first vibration signal.After SVD inverse operation is adopted to multiple signal segments of the first vibration signal, obtain the first vibration signal of the respective signal section after noise reduction.Whether noise reduction process is complete to judge multiple signal segments of the first vibration signal, if judge that multiple signal segments of the first vibration signal do not have noise reduction process complete, continue first vibration signal corresponding to arbitrary signal segment and carry out SVD inverse operation, until multiple signal segments of vibration signal are all disposed.Thus to the overlapped signal between the adjacent signals section in multiple signal segments of the first vibration signal through repeatedly noise reduction, obtain multiple noise reduction process result.After the multiple noise reduction process result of acquisition, then nonzero element is carried out to each section of multiple noise reduction process result be averaging process.
Consider that range hood is in utilization process, especially the vibration signal in unloading phase contains noise signal, along with the rising of rotating speed, noise is also more and more obvious, and there is irregular impulse disturbances, corresponding noise-reduction method can be utilized to carry out Reduction Analysis, filter the vibration signal ripple under impulse disturbances, retain the real vibration performance of mechanical oscillation signal, by amplitude and the frequency of electric motor rotor vibration signal in the time-frequency spectrum image feedback range hood start-up course that obtains, extract the time-frequency characteristics of fault-signal, thus the malfunction of rotor is analyzed on quicklook ground, thus be beneficial to and diagnose out motor whether to occur dependent failure problem with the wind wheel be connected therewith in early days rapidly, and complete machine need not be dismantled, solve the inefficient problem of fault diagnosis of electrical equipment,
Step S24, obtains the signal after noise reduction process.
Nonzero element is carried out to each section of multiple noise reduction process result and is averaging process, obtain the vibration signal after noise reduction.Preferably, the vibration signal after noise reduction is the radial vibration signal at the rotor place of range hood, belongs to the second vibration signal, be stationary signal, the vibration signal ripple under elimination impulse disturbances, retains the real vibration performance of mechanical oscillation signal.
Step S25, analyzes time-frequency spectrum picture.
Extract the vibration performance of the radial vibration signal at the rotor place of range hood, by amplitude and the frequency of time-frequency spectrum graphical analysis radial vibration signal, obtain the time-frequency characteristics of radial vibration signal.
Step S26, extracts the time-frequency characteristics of fault-signal.
The time-frequency characteristics of fault-signal is extracted from the time-frequency characteristics of radial vibration signal.
Step S27, obtains fault diagnosis conclusion.
Judge whether the vibrating mass such as motor exist fault according to the vibration performance of radial vibration signal, from the time-frequency characteristics determination electrical equipment of the fault-signal extracted, there are the parts of fault.
The method for diagnosing faults of the range hood of this embodiment is by gathering vibration signal, then the radial vibration signal at range hood motor place is gathered by signal acquisition device, radial vibration signal is input to disposal system, recycling SVD noise reduction process radial vibration signal, obtain the signal after noise reduction process, analyze the time-frequency spectrum picture of radial vibration signal again and extract the time-frequency characteristics of fault-signal, finally obtain the fault diagnosis conclusion of range hood, what save fault generating unit searches the proving time, early diagnosis for vibrating mass faults such as motors provides reliable technical support, and then reach the effect of the fault diagnosis efficiency improving electrical equipment.
It should be noted that, can perform in the computer system of such as one group of computer executable instructions in the step shown in the process flow diagram of accompanying drawing, and, although show logical order in flow charts, but in some cases, can be different from the step shown or described by order execution herein.
The embodiment of the present invention additionally provides a kind of electric equipment fault diagnosis device, it should be noted that, the electric equipment fault diagnosis device of this embodiment may be used for the Fault Diagnosis of Electrical Appliance performing the embodiment of the present invention, and electrical equipment comprises the parts that there is vibration in the course of the work.
Fig. 4 is the schematic diagram of electric equipment fault diagnosis device according to a first embodiment of the present invention, and as shown in Figure 4, this device comprises detecting unit 30, judging unit 40 and determining unit 50.
Detecting unit 30, for detecting the vibration signal of electrical equipment.Detecting unit 30 gathers the vibration signal of electrical equipment by the detection of the vibration signal to electrical equipment.The detection of the vibration signal of electrical equipment can utilize signal detection device, and such as, utilizes displacement transducer to detect.Detected the vibration signal of electrical equipment by signal detection device, obtain analog detection signal, now signal is the signal of non-stationary.After obtaining analog detection signal, sample quantization process is carried out to analog detection signal, obtains digital detection signal, digital detection signal is input to signal processing system, signal processing system carries out noise reduction process to the vibration signal of electrical equipment, obtains the vibration signal after noise reduction process.Perform follow-up electric equipment fault diagnosis by the vibration signal after noise reduction process, be conducive to the accuracy improving fault diagnosis.
Extraction unit 40, for extracting the vibration performance of vibration signal.After detecting unit 30 detects and collects the vibration signal of electrical equipment, the vibration performance that extraction unit 40 extracts vibration signal comprises the time-frequency spectrum picture being obtained vibration signal by the vibration performance of extraction vibration signal.The vibration performance that extraction unit 40 extracts vibration signal can also comprise the vibration performance of the vibration signal after extracting noise reduction process.Preferably, after detecting unit 30 detects and collects the vibration signal of electrical equipment, the vibration performance vibration performance comprised by extracting the second vibration signal that extraction unit 40 extracts vibration signal obtains the time-frequency spectrum picture of the second vibration signal, and the vibration performance extracting the second vibration signal comprises: the vibration performance extracting the second vibration signal after noise reduction process.
Determining unit 50, for according to the parts that there is fault in the vibration performance determination electrical equipment of vibration signal.After the time-frequency characteristics obtaining vibration signal, by there are the parts of fault in determining unit 50 in the time-frequency characteristics determination electrical equipment of vibration signal.Preferably, amplitude and the frequency of time-frequency spectrum graphical analysis second vibration signal is obtained by extraction unit 40, obtain the time-frequency characteristics of the second vibration signal, again by the time-frequency characteristics of the second vibration signal, extract the time-frequency characteristics of fault-signal, thus determining unit 50 can determine the parts that there is fault in electrical equipment.
Fig. 5 is the schematic diagram of electric equipment fault diagnosis device according to a second embodiment of the present invention, and in one embodiment of the invention, determining unit 50 comprises analysis module 51, determination module 52.As shown in Figure 5, the device of this embodiment comprises detecting unit 30, extraction unit 40 and determining unit 50, and wherein, determining unit 50 also comprises analysis module 51 and determination module 52.
Extraction unit 40, obtains the time-frequency spectrum picture of vibration signal for the vibration performance by extracting vibration signal.
Analysis module 51, for passing through amplitude and the frequency of time-frequency spectrum graphical analysis vibration signal, obtains the time-frequency characteristics of vibration signal.
Determination module 52, for the parts by there is fault in the time-frequency characteristics determination electrical equipment of vibration signal.
Fig. 6 is the schematic diagram of electric equipment fault diagnosis device according to a third embodiment of the present invention, and as shown in Figure 6, this device comprises detecting unit 30, extraction unit 40, determining unit 50 and noise reduction processing unit 60, wherein, determining unit 50 also comprises analysis module 51 and determination module 52.
Noise reduction processing unit 60, for carrying out noise reduction process to vibration signal, obtains the vibration signal after noise reduction process, and wherein, extraction unit 40 is also for extracting the vibration performance of the vibration signal after noise reduction process.
Fig. 7 is the schematic diagram of electric equipment fault diagnosis device according to a fourth embodiment of the present invention, and in one embodiment of the invention, detecting unit 30 comprises detection module 31 and staging treating module 32.As shown in Figure 7, this device comprises detecting unit 30, extraction unit 40, determining unit 50 and noise reduction processing unit 60, and wherein, determining unit 50 also comprises analysis module 51 and determination module 52, and detecting unit 30 also comprises detection module 31 and staging treating module 32.
Detection module 31, for detecting the vibration signal of electrical equipment, obtains the first vibration signal, and wherein, the first vibration signal is non-stationary signal.
Staging treating module 32, for carrying out data sectional process to the first vibration signal, obtains the second vibration signal, and the second vibration signal is stationary signal.Extraction unit 40 is also for extracting the vibration performance of the second vibration signal.
Fig. 8 is the schematic diagram of electric equipment fault diagnosis device according to a fifth embodiment of the present invention, and in one embodiment of the invention, staging treating module 32 comprises staging treating submodule 321, noise reduction module 322 and computing module 323.As shown in Figure 8, this device comprises detecting unit 30, extraction unit 40, determining unit 50 and noise reduction processing unit 60, wherein, determining unit 50 also comprises analysis module 51 and determination module 52, and detecting unit 30 also comprises detection module 31 and staging treating module 32, staging treating module 32 also comprises staging treating submodule 321, noise reduction module 322 and computing module 323.
Staging treating submodule 321, carries out data sectional process for the rectangular window by adding predetermined width to the first vibration signal, obtains multiple signal segment, has the lap of preset ratio between multiple signal segment.
Noise reduction module 322, for the overlapped signal between the adjacent signals section in multiple signal segment through repeatedly noise reduction, obtain multiple noise reduction process result.
Computing module 323, for being averaging process to multiple noise reduction process result, obtains the second vibration signal.
The embodiment of the present invention additionally provides a kind of range hood, it should be noted that, this range hood may be used for the electric equipment fault diagnosis device of the embodiment of the present invention.
Fig. 9 is the schematic diagram of the range hood according to the embodiment of the present invention.Preferably, the vibration signal of range hood can be gathered by displacement transducer 10 as shown in Figure 10.Range hood comprises motor, detecting unit 30 utilizes displacement transducer 10 to gather the radial vibration signal of the rotor of motor, extracted the vibration performance of radial vibration signal by extraction unit 40, according to the vibration performance of radial vibration signal, determining unit 50 judges whether motor exists fault again.
This embodiment utilizes the attractive force of the magnet of displacement transducer 10 end its one end to be arranged on the bonnet direction of range hood, also, and the position at motor and wind wheel place.When displacement transducer 10 pairs of range hoods carry out signals collecting, can accurate acquisition to the vibration signal at motor place, and then obtain the radial vibration signal of rotor.Now the radial vibration signal of rotor is non-stationary signal, it is synchronously input in the computer that is connected with the other end of displacement transducer 10, the vibration signal of non-stationary is converted into digital signal by computer expert's over-sampling quantification treatment, then carries out noise reduction process to the digital signal after conversion.The digital signal transforming rear Noise is set to the function of data length, Overlapping Fragment is carried out to non-stationary signal, alternatively, svd inverse operation process is carried out to arbitrary segment signal, obtain the signal of corresponding section after noise reduction, and carry out all block signals of circular treatment, until all block signals are disposed, the nonzero element of all block signals is averaging, just can obtains the stationary signal after noise reduction.Through noise reduction process, vibration signal ripple under elimination impulse disturbances, remain the real vibration performance of mechanical oscillation signal, from the rotor of the signal waveform collected and time-frequency spectrum image feedback range hood at the amplitude of start-up course vibration signal and warbled physical features, can by the time-frequency characteristics of time-frequency spectrum image zooming-out fault-signal, determine whether the vibrating mass such as motor exist fault, save the proving time of looking up the fault generating unit, thus provide reliable technical support for the early diagnosis of the vibrating mass faults such as motor, improve the development efficiency of project.
The embodiment of the present invention additionally provides a kind of electrical equipment, and this electrical equipment exists the parts of vibration in the course of the work, and this electrical equipment may be used for the electric equipment fault diagnosis device of the embodiment of the present invention, and preferably, this electrical equipment is range hood.
The Fault Diagnosis of Electrical Appliance that the embodiment of the present invention provides and device, by detecting the vibration signal of electrical equipment, then the vibration performance of vibration signal is extracted, and according to there are the parts of fault in the vibration performance determination electrical equipment of vibration signal, achieve the condition monitoring and fault diagnosis to electrical equipment, improve the fault diagnosis efficiency of electrical equipment.
Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on network that multiple calculation element forms, alternatively, they can realize with the executable program code of calculation element, thus, they can be stored and be performed by calculation element in the storage device, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the present invention is not restricted to any specific hardware and software combination.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (14)
1. a Fault Diagnosis of Electrical Appliance, is characterized in that, described electrical equipment comprises the parts that there is vibration in the course of the work, and described Fault Diagnosis of Electrical Appliance comprises:
Detect the vibration signal of described electrical equipment;
Extract the vibration performance of described vibration signal; And
The parts that there is fault in described electrical equipment are determined according to the vibration performance of described vibration signal.
2. Fault Diagnosis of Electrical Appliance according to claim 1, is characterized in that,
The vibration performance extracting described vibration signal comprises: the time-frequency spectrum picture being obtained described vibration signal by the vibration performance extracting described vibration signal,
Determine that the parts that there is fault in described electrical equipment comprise according to the vibration performance of described vibration signal: by amplitude and the frequency of vibration signal described in described time-frequency spectrum graphical analysis, obtain the time-frequency characteristics of described vibration signal; The parts that there is fault in described electrical equipment are determined by the time-frequency characteristics of described vibration signal.
3. Fault Diagnosis of Electrical Appliance according to claim 1, is characterized in that,
The vibration signal detecting described electrical equipment comprises: carry out noise reduction process to described vibration signal, obtains the vibration signal after noise reduction process,
The vibration performance extracting described vibration signal comprises: the vibration performance extracting the vibration signal after described noise reduction process.
4. Fault Diagnosis of Electrical Appliance according to claim 1, is characterized in that,
The vibration signal detecting described electrical equipment comprises: the vibration signal detecting described electrical equipment, obtains the first vibration signal, and wherein, described first vibration signal is non-stationary signal; Carry out data sectional process to described first vibration signal, obtain the second vibration signal, wherein, described second vibration signal is stationary signal,
The vibration performance extracting described vibration signal comprises: the vibration performance extracting described second vibration signal.
5. Fault Diagnosis of Electrical Appliance according to claim 4, is characterized in that, carries out data sectional process comprise described first vibration signal:
By the rectangular window adding predetermined width, data sectional process is carried out to described first vibration signal, obtain multiple signal segment, wherein, there is between described multiple signal segment the lap of preset ratio;
To the overlapped signal between the adjacent signals section in described multiple signal segment through repeatedly noise reduction, obtain multiple noise reduction process result; And
Process is averaging to described multiple noise reduction process result, obtains described second vibration signal.
6. Fault Diagnosis of Electrical Appliance according to any one of claim 1 to 5, is characterized in that, described electrical equipment is range hood, and described range hood comprises motor,
The vibration signal detecting described electrical equipment comprises: utilize displacement transducer to gather the radial vibration signal of the rotor of described motor,
The vibration performance extracting described vibration signal comprises: the vibration performance extracting described radial vibration signal,
Determine that the parts that there is fault in described electrical equipment comprise according to the vibration performance of described vibration signal: judge whether described motor exists fault according to the vibration performance of described radial vibration signal.
7. an electric equipment fault diagnosis device, is characterized in that, described electrical equipment comprises the parts that there is vibration in the course of the work, and described electric equipment fault diagnosis device comprises:
Detecting unit, for detecting the vibration signal of described electrical equipment;
Extraction unit, for extracting the vibration performance of described vibration signal; And
Determining unit, for determining according to the vibration performance of described vibration signal the parts that there is fault in described electrical equipment.
8. electric equipment fault diagnosis device according to claim 7, is characterized in that, described extraction unit is used for the time-frequency spectrum picture being obtained described vibration signal by the vibration performance extracting described vibration signal, and described determining unit comprises:
Analysis module, for by the amplitude of vibration signal described in described time-frequency spectrum graphical analysis and frequency, obtains the time-frequency characteristics of described vibration signal; And
Determination module, for determining by the time-frequency characteristics of described vibration signal the parts that there is fault in described electrical equipment.
9. electric equipment fault diagnosis device according to claim 7, is characterized in that, described electric equipment fault diagnosis device also comprises:
Noise reduction processing unit, for carrying out noise reduction process to described vibration signal, obtains the vibration signal after noise reduction process,
Wherein, described extraction unit is for extracting the vibration performance of the vibration signal after described noise reduction process.
10. electric equipment fault diagnosis device according to claim 7, is characterized in that, described detecting unit comprises;
Detection module, for detecting the vibration signal of described electrical equipment, obtains the first vibration signal, and wherein, described first vibration signal is non-stationary signal; And
Staging treating module, for carrying out data sectional process to described first vibration signal, obtains the second vibration signal, and wherein, described second vibration signal is stationary signal,
Wherein, described extraction unit is for extracting the vibration performance of described second vibration signal.
11. electric equipment fault diagnosis devices according to claim 10, is characterized in that, described staging treating module comprises:
Staging treating submodule, carrying out data sectional process for the rectangular window by adding predetermined width to described first vibration signal, obtaining multiple signal segment, wherein, has the lap of preset ratio between described multiple signal segment;
Noise reduction module, for the overlapped signal between the adjacent signals section in described multiple signal segment through repeatedly noise reduction, obtain multiple noise reduction process result; And
Computing module, for being averaging process to described multiple noise reduction process result, obtains described second vibration signal.
12. electric equipment fault diagnosis devices according to any one of claim 7 to 11, it is characterized in that, described electrical equipment is range hood, and described range hood comprises motor,
The radial vibration signal of described detecting unit for utilizing displacement transducer to gather the rotor of described motor,
Described extraction unit for extracting the vibration performance of described radial vibration signal,
According to the vibration performance of described radial vibration signal, described determining unit judges whether described motor exists fault.
13. 1 kinds of electrical equipment, is characterized in that, comprise the electric equipment fault diagnosis device according to any one of parts and claim 7 to 12 that there is vibration in the course of the work.
14. electrical equipment according to claim 13, is characterized in that, described electrical equipment is range hood.
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