CN107948251A - A kind of remote mechanical fault diagnosis system based on Android - Google Patents

A kind of remote mechanical fault diagnosis system based on Android Download PDF

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Publication number
CN107948251A
CN107948251A CN201711078434.3A CN201711078434A CN107948251A CN 107948251 A CN107948251 A CN 107948251A CN 201711078434 A CN201711078434 A CN 201711078434A CN 107948251 A CN107948251 A CN 107948251A
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signal
module
judging result
mobile terminal
frequency
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CN107948251B (en
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周凤星
毛海波
沈春鹏
严保康
卢少武
马娅婕
但峰
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Wuhan University of Science and Engineering WUSE
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Wuhan University of Science and Engineering WUSE
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/02—Gearings; Transmission mechanisms
    • G01M13/021—Gearings
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/02—Gearings; Transmission mechanisms
    • G01M13/028—Acoustic or vibration analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/04—Bearings
    • G01M13/045—Acoustic or vibration analysis
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network

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  • Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Acoustics & Sound (AREA)
  • Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

The present invention provides a kind of remote failure diagnosis system based on Android, it is characterised in that：Including collection terminal and mobile terminal；The collection terminal and mobile terminal are equipped with communication module, for the data interaction between equipment；The collection terminal, further includes digital signal acquiring module；The mobile terminal, further includes digital signal processing module；Wherein, all kinds of detection data of the digital signal acquiring module collection Devices to test, and it is transferred to mobile terminal；After the digital signal processing module is handled and analyzed to detection data, result diagnosis report is generated.The system can be used in the problems such as mechanical breakdown of quick, efficient, accurate detection bearing and gear-box.

Description

A kind of remote mechanical fault diagnosis system based on Android
Technical field
The invention belongs to technology for mechanical fault diagnosis field, and in particular, to a kind of remote mechanical failure based on Android Diagnostic system.
Background technology
Mechanical fault diagnosis is a kind of state for understanding and grasping machine in operational process, determines that it is overall or local normal Or abnormal, early detection failure and its reason, and can forecast the technology of fault progression trend.With automating skill in modern industry A large amount of popularizations of art, requirement of the people to safety and stability in production process are more and more stringenter.Currently on the market it is various just The formula failure diagnostic apparatus of taking respectively has the characteristics of respective, and different instruments meets different requirements, but exists to varying degrees Shortcoming, these portable fault diagnosis testers are controlled using microcontroller more, and cumbersome or function is single, intelligence degree It is low, it can not be connected with smart mobile phone.
The content of the invention
It is contemplated that overcome the above problem, there is provided it is a kind of it is easy to operate, price is low, feature-rich, versatility is good and just In carrying mechanical breakdown (such as：Bearing and gear-box etc.) diagnostic system.
A kind of remote failure diagnosis system based on Android provided by the invention, it is characterised in that：Including collection terminal and shifting Moved end；
Above-mentioned collection terminal and mobile terminal are equipped with communication module, for the data interaction between equipment；
Above-mentioned collection terminal, further includes digital signal acquiring module；
Above-mentioned mobile terminal, further includes digital signal processing module；
Wherein, all kinds of detection data of above-mentioned digital signal acquiring module collection Devices to test, and it is transferred to movement End；
After above-mentioned digital signal processing module is handled and analyzed to detection data, result diagnosis report is generated.
Further, a kind of remote failure diagnosis system based on Android provided by the invention, also has the characteristics that such： I.e., process is handled as follows to detection data in above-mentioned digital signal acquiring module respectively：
S1, auto-correlation transformation and wavelet transformation；
S2, the transformation results obtained to process one carry out Hilbert conversion, and ask for signal Hilbert envelope spectrums；
S3, by envelope spectrum carry out FFT transform ask for signal low-frequency spectra；
S4, pass through low-frequency spectra acquisition characteristics of low-frequency frequency；
S5, the characteristic frequency being calculated is compared with the characteristic frequency that S4 is analyzed, generation result diagnosis report Accuse；
Wherein, the above-mentioned characteristic frequency being calculated is the spy of the failure mode of the rolling bearing obtained by theoretical calculation Levy frequency；The theoretical calculation mode is as follows：
(1) inner ring fault characteristic frequency：
(2) outer ring fault characteristic frequency：
(3) rolling element fault characteristic frequency：
Wherein, Z is rolling element number, and D is pitch diameter, and d is rolling element diameter, and ɑ is contact angle, and f i turn frequency for inner ring.
The above results diagnosis report includes whether that there are the concrete form of failure, and failure.
Further, a kind of remote failure diagnosis system based on Android provided by the invention, also has the characteristics that such： I.e., remote service end is further included；
Above-mentioned remote service end includes memory module, for storing the Various types of data from each equipment；
Above-mentioned remote service end further includes communication module, is realized by communication module and other data interactions between setting.
In the present invention, the function of cloud server mainly saves historical data, and judges bearing by historical data Fault progression form, so as to determine whether need shutdown maintenance.
Further, a kind of remote failure diagnosis system based on Android provided by the invention, also has the characteristics that such： I.e., the operational process of above-mentioned mobile terminal is as follows：
S2-1, system initialization；
S2-2, judge whether to connect collection terminal；
If judging result is "Yes", then step 2-3 is carried out；
If judging result is "No", then step 2-6 is carried out；
The judgement whether connected on two equipment, in the concrete scheme of the present invention, can pass through collection terminal A flag bit whether transmitted is provided with working procedure or software, automatically will mark when mobile terminal connects upper collection terminal Will position position, when disconnection, reset, and whether SM set mode are in by judgement symbol position, to determine whether can be transmitted.
S2-3, to collection terminal send acquisition parameter and bearing parameter；
Such parameter can include acquisition channel, sample frequency, sampling number, amplification factor, show Digital Signal Processing Signal processing results of device etc., the relevant parameter of bearing, has embodiment in above-mentioned fault characteristic frequency calculation formula.
S2-4, the collection vibration signal for waiting collection terminal, after collection, are collected original by communication module The data of signal；
S2-5, after original signal is handled and analyzed by signal processing module, extract characteristic frequency, and generate knot Fruit diagnosis report；
The content of the diagnosis report mainly includes whether that there are inner ring failure, outer ring failure, rolling element failure and mixing Failure.
S2-6, judge whether to connect remote service end；
If judging result is "Yes", then step 2-7 is carried out；
If judging result is "No", then step 2-2 is carried out；
S2-7, by original signal data and dependent diagnostic report be uploaded to remote service end；
S2-8, download historical signal data and dependent diagnostic report from remote service end.
In the present invention, remote service end is (such as：Cloud server) function mainly save historical data, pass through history Data judge the fault progression form of bearing to observe, and judge whether to need shutdown maintenance.Bearing can be with the minor failure stage It is continuing with, shutdown maintenance is necessarily required when failure becomes serious.And when Site Detection personnel because lack experience or its More professional testing staff can be asked to download detection data from high in the clouds when he can not judge and complete diagnosis.
The process whether diagnosis needs to shut down can also realize by way of software diagnoses automatically, in the present invention The remote failure diagnosis system based on Android, also have the characteristics that such：I.e., diagnostic module is further included；
Above-mentioned diagnostic module, according to the content of current result diagnosis report, is made whether to need the judgement of shutdown maintenance；
When judging result is " needs ", it will determine that user interface of the result in mobile terminal is shown；
When judging result is " being not required ", above-mentioned diagnostic module, carries out historical signal data and historical diagnostic report After analysis, fault progression situation trend report is generated.
Further, a kind of remote failure diagnosis system based on Android provided by the invention, also has the characteristics that such： I.e., above-mentioned collection terminal, further includes digital signal primary treatment module；
All kinds of detection data are carried out time-domain analysis and frequency-domain analysis by above-mentioned digital signal primary treatment module.
In the present invention, the primary treatment module on collection terminal and mobile terminal be (such as：Cell phone application) on data processing module It is two systems independent of each other, realizes and communicate by communication modules such as wifi between two, complete each independent work(mutually Can, collection terminal mainly completes signal acquisition, also can be by carrying in the case of carrying out processing analysis to signal in no mobile terminal Primary treatment module complete the work of simple signal processing, if mobile terminal, then signal data can be preferably sent to shifting Moved end, the function of ensuing processing and analysis is completed by mobile terminal.
It is specific as follows：A kind of remote failure diagnosis system based on Android provided by the invention, also has the characteristics that such： I.e., the operational process of above-mentioned collection terminal is as follows：
S1-1, system initialization；
S1-2, confirm acquisition parameter and bearing parameter；
S1-3, start to gather vibration signal and preserve；
S1-4, the signal for judging whether to need to collect are transmitted to mobile terminal；
If judging result is "Yes", then step 1-7 is carried out；
If judging result is "No", then step 1-5 is carried out；
S1-5, extraction original signal, and time-domain analysis and/or frequency-domain analysis are carried out to original signal to obtain statistical indicator And/or characteristic frequency；And/or extraction resonance and demodulation signal, and frequency-domain analysis is carried out to resonance and demodulation signal to obtain feature frequency Rate；
S1-6, according to statistical indicator and/or characteristic frequency judge bearing state；
S1-7, judge whether to need to transmit the signal that collect and/or the judging result of S1-6 to mobile terminal；
If judging result is "Yes", then step 1-8 is carried out；
If judging result is "No", then into holding state；
The holding state is that, when data acquisition finishes, whether wait has the operation of next step.For example operating personnel pass through Touch-screen directly controls digital signal processor and carries out new data acquisition, or receive that mobile terminal sends over to collection End carries out the order of next step operation.
S1-8, system initialization communication module；
S1-9, establish the link with mobile terminal；
S1-10, by communication module be transferred to mobile terminal by the judging result of the signal collected and/or S1-6.
Further, a kind of remote failure diagnosis system based on Android provided by the invention, also has the characteristics that such： I.e., the step of operational process of above-mentioned collection terminal can also play S1-7 is replaced as follows：
S1-7, judge whether to need to transmit the signal that collect and/or the judging result of S1-6 to mobile terminal；
If judging result is "Yes", then step 1-8 is carried out；
If judging result is "No", then step 1-11 is carried out；
S1-8, system initialization communication module；
S1-9, establish the link with mobile terminal；
S1-10, by communication module be transferred to mobile terminal by the judging result of the signal collected and/or S1-6；
S1-11, judge whether to connect remote service end；
If judging result is "Yes", then step 1-12 is carried out；
If judging result is "No", then into holding state；
S1-12, by various types of signal data and dependent diagnostic report be uploaded to remote service end.
Further, present invention also offers a kind of hardware configuration of the remote failure diagnosis system based on Android, it is special Sign is：Including collecting device, smart mobile phone and high in the clouds；
Above-mentioned collecting device, for gathering the detection signal data of Devices to test；
Above-mentioned smart mobile phone, for carrying out statistics and analysis to detection data；
Above-mentioned high in the clouds, for storing history detection signal data and historical signal diagnosis report；
Data transfer is realized in above-mentioned collecting device, smart mobile phone and high in the clouds by communication module；
Wherein, above-mentioned collecting device includes the screen with operation interface, control panel, collection plate and the power supply installed successively System；
Above-mentioned collection plate includes signal acquisition module, is connected with sensor；
Above-mentioned control panel includes signal processing module；
Connected between above-mentioned collection plate, control panel, screen by socket.
In addition, a kind of above-mentioned remote failure diagnosis system based on Android, also has the characteristics that such：I.e., above-mentioned biography Sensor is piezoelectric acceleration transducer, and being attached to test surfaces using magnet fixation carries out signal acquisition；
Above-mentioned signal acquisition module includes original signal Acquisition Circuit and resonance and demodulation signal acquisition circuit.
In addition, a kind of above-mentioned remote failure diagnosis system based on Android, also has the characteristics that such：I.e., above-mentioned letter Number acquisition module includes two road signal acquisition circuits：Original signal Acquisition Circuit and resonance and demodulation signal acquisition circuit.
The function and effect of the present invention：
The system of the present invention has small, easy to carry, and easy to operate, signal processing function is powerful, and testing result is accurate Really, the characteristics of cloud database amount of storage is big, can realize that live quick diagnosis and Remote diagnose work(using cell phone application Energy, can effectively improve the work efficiency of check staff's Site Detection.
In the present invention, it is to cooperate by mobile phone (mobile terminal) and digital signal processor (collection terminal)：Numeral Signal processor mainly completes the collecting work of signal, and mobile phone mainly completes the complicated algorithm processing of signal.Traditional is portable Its data processing of failure diagnostic apparatus and data storage capacities are limited, therefore we are mainly completed to detection data by mobile phone Processing and storage, improve data processing and data storage capacities.Digital signal acquiring device device, can only in the case where lacking mobile phone Simple signal processing function is enough completed, diagnostic function is limited.Obvious this volume is sufficiently small, is carried easy to scene and operation is set It is standby, and possess enough computing capabilitys, the algorithm process of complexity can be completed；And the low cost of product, currently on the market just The cost for taking formula failure diagnostic apparatus is very high.
Brief description of the drawings
The structure diagram of Fig. 1, the present embodiment system；
The structure diagram of Fig. 2, the present embodiment babinet；
Fig. 3, dsp system flow scheme design schematic diagram；
Fig. 4, cell phone application flow scheme design schematic diagram；
Fig. 5, example envelope spectrogram；
Fig. 6, the Fourier space of periodic signal are decomposed；
FFT calculation flow charts when Fig. 7, N=8；
Fig. 8, the result obtained after Hilbert is converted.
Embodiment
Such as Fig. 1 and as shown in Fig. 2, a kind of remote failure diagnosis system based on Android provided in this embodiment, including case Body, smart mobile phone and cloud database；Switch, fan, sensor, touch-screen are equipped with outside above-mentioned babinet；Above-mentioned babinet Inside is three-decker, and bottom is lithium battery, and intermediate layer is collection plate, top layer plate in order to control；Above-mentioned collection plate includes MicroUSB interfaces, power module, signal acquisition module；Above-mentioned control panel includes signal processing module, wireless network module； Connected between above-mentioned collection plate, control panel, touch-screen by socket；Above-mentioned digital signal processor and smart mobile phone are each Equipped with special fault diagnosis software；Above-mentioned cloud database is stored with history detection signal data and historical signal diagnosis report Accuse.
The sensor is piezoelectric acceleration transducer, and being attached to test surfaces progress signal using magnet fixation adopts Collection.
Above-mentioned touch-screen can set sampling parameter, including acquisition channel, sample frequency, sampling number, amplification factor, show The signal processing results of registration word signal processor.
Above-mentioned lithium battery is that double 12V power, and 12V voltage conversions are that 3.3V, 5V voltage are whole by above-mentioned power module System power supply.
Above-mentioned signal acquisition module includes two road signal acquisition circuits, and original signal Acquisition Circuit and resonance and demodulation signal are adopted Collector.
Above-mentioned wireless network module is Wi-Fi module, chip model ESP8266, for communicating with smart mobile phone.
The mode of carrying out practically is：All kinds of detection data of mobile terminal Devices to test are gathered by babinet, and are transmitted To smart mobile phone；After smart mobile phone is handled and analyzed to detection data, result diagnosis report is generated, and shown in front end Show.
The chip model of above-mentioned signal processing module is TMS320F28335, can be directly by touching equipped with special software Screen is touched to be operated, while can be by smart mobile phone remote control, as shown in figure 3, the dsp system running software flow is：
Step 1：System initialization；
Step 2：Acquisition parameter and bearing parameter are inputted, including：Sampling channel, sample frequency, sampling number, times magnification Number, the relevant parameter of bearing etc.；
Step 3：Start to gather vibration signal and preserve；
Step 4：Judge whether to need to transmit；
If it is, enter step nine；
If it is not, then enter step five；
Step 5：Original signal is extracted, time-domain analysis and frequency-domain analysis are carried out to original signal；
Step 6：Resonance and demodulation signal is extracted, frequency-domain analysis is carried out to resonance and demodulation signal；
Step 7：Bearing state is judged according to characteristic frequency；
Step 8：Judge whether to need to transmit, if it is, entering step nine；If it is not, then system, which enters, waits mould Formula；
Step 9：System initialization Wi-Fi module；
Step 10：Established the link with cell phone application；
Step 11：Cell phone application is transferred data to by Wi-Fi module.
Above-mentioned smart mobile phone is equipped with special fault diagnosis software, can complete remote control babinet collection signal, can The characteristic frequency of signal and the characteristic frequency of signal envelope spectrum are extracted, can upload and download history detection letter from cloud database Number and historical signal diagnosis report.As shown in figure 4, the operational process of the cell phone application is：
Step 1：Software initialization；
Step 2：Judge whether to connect DSP；
If it is, enter step three；
If it is not, then enter step seven；
Step 3：Acquisition parameter and bearing parameter are inputted, including：Sampling channel, sample frequency, sampling number, times magnification Number and bearing parameter etc.；
Step 4：DSP collection vibration signals are waited, data are received by Wi-F i modules after collection；
Step 5：Auto-correlation transformation and wavelet transformation to original signal carry out envelope spectrum analysis, extract characteristic frequency；
Step 6：Fault diagnosis report is checked, by characteristic frequency and the fault signature frequency being calculated according to bearing parameter Rate theory value compares, and judges bearing state；
Step 7：Judge whether to connect cloud database, if it is, entering step eight；If it is not, then enter step Two；
Step 8：Upload local original signal data and dependent diagnostic report；
Step 9：Historical signal data and dependent diagnostic report are downloaded from cloud database.
The step 5 is to the detection data specific method that is handled and analyzed：
S1, auto-correlation transformation and wavelet transformation；
S2, the transformation results obtained to process one carry out Hilbert conversion, and ask for signal Hilbert envelope spectrums；
S3, by envelope spectrum carry out FFT transform ask for signal low-frequency spectra；
S4, pass through low-frequency spectra acquisition characteristics of low-frequency frequency；
S5, the feature frequency for analyzing the characteristic frequency of the failure mode of the rolling bearing obtained by theoretical calculation and S4 Rate is compared, and judges whether failure, and the concrete form of failure, and then generate result diagnosis report.
In a specific detection example, the results are shown in Figure 5 for its envelope spectrum, passes through formula
Inner ring fault characteristic frequency：
Outer ring fault characteristic frequency：
Rolling element fault characteristic frequency：
Calculate and understand, under rotating speed 600rpm (it is 10Hz to turn frequency), inner ring fault characteristic frequency theoretical value 71.4Hz, outside Fault characteristic frequency theoretical value 48.6Hz is enclosed, is sufficiently close to the peak value in Hilbert envelope spectrums, can be according to envelope spectrum As a result the fault type for judging the bearing is：Outer ring failure.
In addition, on the APP interfaces of the smart mobile phone, the setting of parameter can be directly carried out, the selection of various algorithms, is examined The inquiry of disconnected report, and the upload and download etc. of historical data.
In the present embodiment, all kinds of main algorithms that dsp system and smart mobile phone are related to are as follows：
(1) time-domain statistical analysis
Time domain map analysis is the simplest method for diagnosing faults of mechanical fault diagnosis, in the event of failure, on its time-domain diagram Obvious periodic shock signal occurs, analyzes amplitude or waveform on time-domain diagram and produces abnormal situation, it becomes possible to axis The operating condition held completes the diagnosis of tentative diagnosis.
In the analysis process, it usually needs complete fault diagnosis by some statistical indicators.Common amplitude domain statistical analysis There is dimension index to have：Average, variance, mean-square value, virtual value, flexure and kurtosis.Average represents the average value of signal amplitude, it is retouched The bias size of Shu Liao signal centers.Variance represents the dispersion degree of signal, and normal signal variance is usually smaller.Mean-square value and have Valid value represents the intensity of signal.Flexure expression is the asymmetric degree of signal probability distribution, and the deflection of signal is bigger, then askew Degree is bigger.Kurtosis is very sensitive to the pulse signal of signal, becomes larger if there is probability, then kurtosis will increase rapidly.
These parameters are essentially dependent on the probability density function of random signal.The amplitude probability of signal represents random signal In the probability size of certain amplitude generation in a flash.And the amplitude probability density of signal refer to it is general in the signal unit amplitude section Rate, it is the function of amplitude.For discrete-time series, the amplitude probability density function of signal can be defined as follows：
N is that the data of discrete signal are counted in formula, nxFall for signal amplitude at (x, x+ △ x).According to probability density function We can obtain the calculation formula of other indexs：
Average：
Variance：
Root-mean-square value：
Flexure：
Kurtosis：
Absolute mean：
Average：
In actual diagnosis, it is desirable to which statistical indicator can accurately reflect bearing fault situation, but be sent out in bearing rotating speed and load During changing, the change of statistical indicator is small, and five kinds of dimensionless indexs are introduced to this：
Waveform index：
Peak index：
Pulse index：
Margin index：
Kurtosis index：
Wherein, Xmax represents the peak value of signal, and Xrms represents virtual value.Waveform index and peak index can not reflect punching The change of signal is hit, it is slightly good that kurtosis index, margin index and pulse index then show, so usually three kinds of indexs are come below for selection Analyze bearing fault condition.
(2) Fourier transformation and fft algorithm
Time-domain analysis is only applicable to than more typical signal or not obvious failure, for waveform signal information contained with During fault relationship unobvious, it is difficult to carry out accurate judgement.According to Fourier space decomposition principle, periodic signal can be divided into some letters Humorous signal, these harmonic signals have different amplitudes, these are decomposited to the signal come and arranges and can be obtained from small to large by frequency To frequency spectrum, as shown in fig. 6, can intuitively see the signal of various frequency contents from frequency spectrum, signal point is carried out using frequency spectrum Analysis is a very important means.
If x (t) is periodic signal, then have：
Wherein, a0It is static component, nw0It is n-th harmonic (n=1,2,3 ...), T is fundamental frequency cycles, w0It is fundamental frequency, root According to Euler's formula, periodic signal x (t) can be expressed as in (- T/2, T/2) section with Fourier space：
When T tends to be infinite, Fourier transformation can obtain：
Understand that x (t) is that X (w) is obtained in frequency domain upper integral by formula, therefore X (w) can truly reflect that different frequency is humorous The amplitude of ripple and the change of phase.
Computer can not carry out analog signal continuous fourier transform, it is necessary to first change into discrete digital signal, then carry out Discrete Fourier transform (DFT), formula is as follows：
Wherein, n=0,1,2 ..., N-1；K=0,1,2 ..., N-1；WN=e-j2π/N。
Observation discrete Fourier transform formula needs N altogether it can be found that calculating all X (n)2Secondary complex multiplication, works as N When very big, amount of calculation can become very large, and a kind of fast algorithm FFT is proposed to this.Fft algorithm is first 2 length The data sequence of positive integer power is progressively extracted as odd, even, is calculated by fft algorithm, finally two be calculated A half section of X (n) and X (n+N/2) connect to obtain whole sequence X (n), and detailed step and calculation formula are as follows：
Fourier transformation is that periodic signal is expressed as to a series of superposition of different frequency sinusoidal signals, is obtained by FFT Frequency spectrum be to be arranged these sinusoidal signals from small to large by frequency, as shown in fig. 7, FFT calculation flow charts during N=8, On such frequency spectrum we have seen that be not the periodic impulse signal frequency produced by bearing fault, but periodic impulse signal point A series of different sinusoidal signal frequencies that solution obtains, and be mingled with the intrinsic frequency that bearing and bearing block produce, react when It is exactly that impact signal is modulated by high frequency sinusoidal signal on the figure of domain, therefore, directly carrying out spectrum analysis to signal cannot be managed It is thinking as a result, can not obtain the frequency content of impact signal.
(3) Hilbert envelope spectrums
Original signal containing modulation intelligence can be expressed as an analytic signal so as to be divided by Hilbert conversion Analysis, its physical significance is that 90 degree of the Retardation of all signals is reached demodulation purpose, and Hilbert transformation for mula is as follows:
Wherein, q (t) is exactly it is desirable that by converting obtained analytic signal, x'(t) it is exactly that the Hilbert of x (t) becomes Change.Obtain that the results are shown in Figure 8 after Hilbert conversion, analytic signal q (t) time-domain diagrams are shown on figure, it can be seen that this When signal segment pulse become readily apparent from, then envelope is asked to the analytic signal：
Because FFT transform is sensitive but insensitive to impact signal to the sinusoidal signal of standard；Envelope spectrum impacts amplitude Signal is sensitive, can highlight periodic impulse signal, insensitive to small magnitude standard sine signal.Therefore to the bag of analytic signal Network asks FFT transform to filter out the influence of intrinsic frequency, obtains the frequency of impact signal.As shown in Fig. 8 Hilbert envelope spectrums, It can be seen that the characteristic frequency of low frequency signal is significantly shown up, wherein sharp peaks characteristic frequency is exactly specific bearing fault Frequency of impact.
With reference to two systems software the method for operation it can be found that due to its data processing sum number of portable fault diagnosis tester Often limited according to storage capacity, therefore, we mainly complete processing and storage to detecting data by mobile phone, improve data Processing and data storage capacities, digital signal acquiring device device can complete simple signal processing in the case where lacking mobile phone Function, but its diagnostic function is limited.In this example, mobile phone and digital signal processor are to cooperate：At digital signal Reason device mainly completes the collecting work of signal, and mobile phone mainly completes the complicated algorithm processing of signal.

Claims (9)

  1. A kind of 1. remote failure diagnosis system based on Android, it is characterised in that：Including collection terminal and mobile terminal；
    The collection terminal and mobile terminal are equipped with communication module, for the data interaction between equipment；
    The collection terminal, further includes digital signal acquiring module；
    The mobile terminal, further includes digital signal processing module；
    Wherein, all kinds of detection data of the digital signal acquiring module collection Devices to test, and it is transferred to mobile terminal；
    After the digital signal processing module is handled and analyzed to detection data, result diagnosis report is generated.
  2. A kind of 2. remote failure diagnosis system based on Android as claimed in claim 1, it is characterised in that：
    Process is handled as follows to detection data in the digital signal acquiring module respectively：
    S1, auto-correlation transformation and wavelet transformation；
    S2, the transformation results obtained to process one carry out Hilbert conversion, and ask for signal Hilbert envelope spectrums；
    S3, by envelope spectrum carry out FFT transform ask for signal low-frequency spectra；
    S4, pass through low-frequency spectra acquisition characteristics of low-frequency frequency；
    S5, the characteristic frequency being calculated is compared with the characteristic frequency that S4 is analyzed, and generates result diagnosis report；
    Wherein, the characteristic frequency being calculated is the feature frequency of the failure mode of the rolling bearing obtained by theoretical calculation Rate；
    The result diagnosis report includes whether that there are the concrete form of failure, and failure.
  3. A kind of 3. remote failure diagnosis system based on Android as claimed in claim 1, it is characterised in that：
    Further include remote service end；
    The remote service end includes memory module, for storing the Various types of data from each equipment；
    The remote service end further includes communication module, and the data interaction between other equipment is realized by communication module.
  4. A kind of 4. remote failure diagnosis system based on Android as claimed in claim 3, it is characterised in that：
    The operational process of the mobile terminal is as follows：
    S2-1, system initialization；
    S2-2, judge whether to connect collection terminal；
    If judging result is "Yes", then step 2-3 is carried out；
    If judging result is "No", then step 2-6 is carried out；
    S2-3, to collection terminal send acquisition parameter and bearing parameter；
    S2-4, the collection vibration signal for waiting collection terminal, after collection, original signal is collected by communication module Data；
    S2-5, after original signal is handled and analyzed by signal processing module, extract characteristic frequency, and generate result and examine Disconnected report；
    S2-6, judge whether to connect remote service end；Rather than
    If judging result is "Yes", then step 2-7 is carried out；
    If judging result is "No", then step 2-2 is carried out；
    S2-7, by original signal data and dependent diagnostic report be uploaded to remote service end；
    S2-8, download historical signal data and dependent diagnostic report from remote service end.
  5. A kind of 5. remote failure diagnosis system based on Android as claimed in claim 4, it is characterised in that：
    Further include diagnostic module；
    The diagnostic module, according to the content of current result diagnosis report, is made whether to need the judgement of shutdown maintenance；
    When judging result is " needs ", it will determine that user interface of the result in mobile terminal is shown；
    When judging result is " being not required ", the diagnostic module, analyzes historical signal data and historical diagnostic report Afterwards, fault progression situation trend report is generated.
  6. A kind of 6. remote failure diagnosis system based on Android as described in claim 1-5 is any, it is characterised in that：
    The collection terminal, further includes digital signal primary treatment module；
    All kinds of detection data are carried out time-domain analysis and frequency-domain analysis by the digital signal primary treatment module.
  7. A kind of 7. remote failure diagnosis system based on Android as claimed in claim 6, it is characterised in that：
    The operational process of the collection terminal is as follows：
    S1-1, system initialization；
    S1-2, confirm acquisition parameter and bearing parameter；
    S1-3, start to gather vibration signal and preserve；
    S1-4, the signal for judging whether to need to collect are transmitted to mobile terminal；
    If judging result is "Yes", then step 1-7 is carried out；
    If judging result is "No", then step 1-5 is carried out；
    S1-5, extraction original signal, and time-domain analysis and/or frequency-domain analysis are carried out to original signal come obtain statistical indicator and/ Or characteristic frequency；And/or extraction resonance and demodulation signal, and frequency-domain analysis is carried out to resonance and demodulation signal to obtain characteristic frequency；
    In the present invention, it is preferred to the Comparative result diagnosed jointly using original signal diagnosis and resonance and demodulation diagnosis, determines diagnosis Accuracy, to prevent erroneous judgement.
    S1-6, according to statistical indicator and/or characteristic frequency judge bearing state；
    S1-7, judge whether to need to transmit the signal that collect and/or the judging result of S1-6 to mobile terminal；
    If judging result is "Yes", then step 1-8 is carried out；
    If judging result is "No", then into holding state；
    S1-8, system initialization communication module；
    S1-9, establish the link with mobile terminal；
    S1-10, by communication module be transferred to mobile terminal by the judging result of the signal collected and/or S1-6.
  8. A kind of 8. remote failure diagnosis system based on Android as claimed in claim 7, it is characterised in that：
    The step of operational process of the collection terminal can also play S1-7 is replaced as follows：
    S1-7, judge whether to need to transmit the signal that collect and/or the judging result of S1-6 to mobile terminal；
    If judging result is "Yes", then step 1-8 is carried out；
    If judging result is "No", then set aside all worries step 1-11；
    S1-8, system initialization communication module；
    S1-9, establish the link with mobile terminal；
    S1-10, by communication module be transferred to mobile terminal by the judging result of the signal collected and/or S1-6；
    S1-11, judge whether to connect remote service end；
    If judging result is "Yes", then step 1-12 is carried out；
    If judging result is "No", then into holding state；
    S1-12, by various types of signal data and dependent diagnostic report be uploaded to remote service end.
  9. A kind of 9. remote failure diagnosis system based on Android, it is characterised in that：Including collecting device, smart mobile phone and high in the clouds；
    The collecting device, for gathering the detection signal data of Devices to test；
    The smart mobile phone, for carrying out statistics and analysis to detection data；
    The high in the clouds, for storing history detection signal data and historical signal diagnosis report；
    Data transfer is realized in the collecting device, smart mobile phone and high in the clouds by communication module；
    Wherein, the collecting device includes the screen with operation interface, control panel, collection plate and the power supply system installed successively System；
    The collection plate includes signal acquisition module, is connected with sensor；
    The signal acquisition module includes two road signal acquisition circuits：Original signal Acquisition Circuit and resonance and demodulation signal acquisition electricity Road；
    The control panel includes signal processing module；
    Connected between the collection plate, control panel, screen by socket.
CN201711078434.3A 2017-11-06 2017-11-06 Android-based remote mechanical fault diagnosis system Expired - Fee Related CN107948251B (en)

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CN110177017A (en) * 2019-06-04 2019-08-27 沃德(天津)智能技术有限公司 A kind of speed reducer intelligent Fault Diagnose Systems and its diagnostic method
CN110779716A (en) * 2019-11-01 2020-02-11 苏州德姆斯信息技术有限公司 Embedded mechanical fault intelligent diagnosis equipment and diagnosis method
CN111189640A (en) * 2020-01-09 2020-05-22 珠海格力电器股份有限公司 Bearing fault monitoring method, monitoring device adopting same and washing machine
CN112350529A (en) * 2020-10-13 2021-02-09 深圳微米自动化科技有限公司 Servo motor maintenance method
CN112432791A (en) * 2020-12-16 2021-03-02 广东省科学院智能制造研究所 Automatic bearing vibration signal fault diagnosis method based on Alan variance
CN113044723A (en) * 2021-03-16 2021-06-29 永富建工集团有限公司 State monitoring, analyzing and fault diagnosing integrated system for hoisting machinery
CN113741378A (en) * 2021-11-04 2021-12-03 西安热工研究院有限公司 Fault analysis method and system for background abnormal point high-frequency acquisition of distributed control system
CN114353935A (en) * 2022-01-04 2022-04-15 北京英华达软件工程有限公司 Electric quantity controllable wireless vibration acceleration sensor
WO2023125465A1 (en) * 2021-12-30 2023-07-06 长沙巨杉智能科技有限公司 Rock ore specimen impedance remote measurement system and method

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EP1228490A1 (en) * 1999-10-28 2002-08-07 General Electric Company Method and system for remotely managing communication of data used for predicting malfunctions in a plurality of machines
CN1244801C (en) * 2003-08-01 2006-03-08 重庆大学 Rotary machine failure intelligent diagnosis method and device
CN100492236C (en) * 2007-12-13 2009-05-27 上海交通大学 Engineering machinery remote control system and method
CN104535323B (en) * 2015-01-12 2017-03-08 石家庄铁道大学 A kind of train wheel Method for Bearing Fault Diagnosis based on angular domain time-domain and frequency-domain
CN105425709A (en) * 2015-12-18 2016-03-23 杨斌 Remote monitoring and management system of ball mills based on wireless access into Internet and equipment of same

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Publication number Priority date Publication date Assignee Title
CN110177017A (en) * 2019-06-04 2019-08-27 沃德(天津)智能技术有限公司 A kind of speed reducer intelligent Fault Diagnose Systems and its diagnostic method
CN110177017B (en) * 2019-06-04 2023-09-19 沃德(天津)智能技术有限公司 Intelligent fault diagnosis system and diagnosis method for speed reducer
CN110779716A (en) * 2019-11-01 2020-02-11 苏州德姆斯信息技术有限公司 Embedded mechanical fault intelligent diagnosis equipment and diagnosis method
CN111189640A (en) * 2020-01-09 2020-05-22 珠海格力电器股份有限公司 Bearing fault monitoring method, monitoring device adopting same and washing machine
CN112350529A (en) * 2020-10-13 2021-02-09 深圳微米自动化科技有限公司 Servo motor maintenance method
CN112432791A (en) * 2020-12-16 2021-03-02 广东省科学院智能制造研究所 Automatic bearing vibration signal fault diagnosis method based on Alan variance
CN112432791B (en) * 2020-12-16 2022-11-01 广东省科学院智能制造研究所 Automatic bearing vibration signal fault diagnosis method based on Alan variance
CN113044723A (en) * 2021-03-16 2021-06-29 永富建工集团有限公司 State monitoring, analyzing and fault diagnosing integrated system for hoisting machinery
CN113741378A (en) * 2021-11-04 2021-12-03 西安热工研究院有限公司 Fault analysis method and system for background abnormal point high-frequency acquisition of distributed control system
CN113741378B (en) * 2021-11-04 2022-03-15 西安热工研究院有限公司 Fault analysis method and system for background abnormal point high-frequency acquisition of distributed control system
WO2023125465A1 (en) * 2021-12-30 2023-07-06 长沙巨杉智能科技有限公司 Rock ore specimen impedance remote measurement system and method
CN114353935A (en) * 2022-01-04 2022-04-15 北京英华达软件工程有限公司 Electric quantity controllable wireless vibration acceleration sensor

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