CN109765045A - It is a kind of for rotating the system and method for class mechanical remote monitoring and fault diagnosis - Google Patents
It is a kind of for rotating the system and method for class mechanical remote monitoring and fault diagnosis Download PDFInfo
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- CN109765045A CN109765045A CN201910175057.8A CN201910175057A CN109765045A CN 109765045 A CN109765045 A CN 109765045A CN 201910175057 A CN201910175057 A CN 201910175057A CN 109765045 A CN109765045 A CN 109765045A
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Abstract
The present invention discloses a kind of for rotating the system and method for class mechanical remote monitoring and fault diagnosis, including signal acquisition unit, Cloud Server unit and client；Wherein, the signal acquisition unit includes sensor and signal acquisition module, and the sensor includes vibrating sensor, vibrates generated acceleration signal for acquiring；The signal that the sensor detects is sent to Cloud Server unit by network；The Cloud Server unit includes network server and software module, and the software module includes data processing module, and the data that the data processing module is used to send over signal acquisition unit carry out original analysis.System and method of the invention carry out data sampling and processing, analysis and storage by the mechanical equipment to scene, to realize long-range monitoring and automatic fault diagnosis, it is ensured that the big data that the safe operation and acquisition of equipment are analyzed for the Life cycle to equipment.
Description
Technical field
The present invention relates to industrial equipment fault detection techniques, and in particular to one kind is for rotating the monitoring of class mechanical remote and event
Hinder the system and method for diagnosis.
Background technique
It is main driving member in mechanical equipment, such as Steam Turbine, the hydraulic turbine that bearing, gear etc., which rotate type component,
Group and pumping plant unit etc., operating status directly affects the performance of equipment.Since gearing is born for a long time during the work time
Various alternating loads, impact and the effect of frictional force or the defect itself left in the fabrication process, therefore it is easy to appear event
Barrier even damages, and for the transmission system of failure, light meeting generates noise, and acceleration equipment abrasion reduces equipment life,
It is serious directly to damage equipment, it influences to produce, brings economic loss, especially to some special important applications, one
Denier equipment breaks down, and loses inestimable.
In view of the above-mentioned problems, be usually to measure analysis to plant site by test equipment by professional technician,
And then determine fault type and position.But this traditional detection mode, it is stored without data, does not utilize big data pair
The foundation that the Life cycle of equipment is analyzed.
Summary of the invention
It is above-mentioned it is an object of the invention to overcome the problems, such as, it provides a kind of for rotating the monitoring of class mechanical remote and event
The system for hindering diagnosis carries out data sampling and processing, analysis and storage by the mechanical equipment to scene, to realize long-range prison
Survey and automatic fault diagnosis, it is ensured that the safe operation and acquisition of equipment are analyzed big for the Life cycle to equipment
Data.
It is another object of the present invention to provide a kind of for rotating the method for class mechanical remote monitoring and fault diagnosis.
The purpose of the present invention is achieved through the following technical solutions:
It is a kind of for rotating the system of class mechanical remote monitoring and fault diagnosis, including signal acquisition unit, Cloud Server
Unit and client；
Wherein, the signal acquisition unit includes sensor and signal acquisition module, and the sensor includes vibrating sensing
Device vibrates generated acceleration signal for acquiring, and the vibrating sensor is installed on close to the position of detected object；Institute
Stating signal acquisition module includes processor, memory and network module；The signal that the sensor detects passes to processing
Device, and store into memory, Cloud Server unit is sent to by network module；
The Cloud Server unit includes network server and software module, and the software module includes data processing mould
Block, the data that the data processing module is used to send over signal acquisition unit carry out original analysis；The data processing
Module carries out time-domain analysis and frequency-domain analysis to the collected vibration signal of vibrating sensor, wherein is obtained according to time-domain analysis
Time domain map, and kurtosis data k is calculated automatically, and is compared with the failure kurtosis data k ' of user's typing, as k >=k '
Obtain the analysis result to break down；Obtain spectrogram according to frequency-domain analysis, obtain real-time vibration frequency f, and with user's typing
Fault characteristic frequency f ' compare, the analysis result to break down is obtained as f >=f '；
The client accesses the analysis result in Cloud Server unit by network.
A preferred embodiment of the invention, wherein the sensor further includes temperature sensor, is used for collecting work environment
In temperature signal, the temperature sensor is installed on the position close to detected object.Generally, vibrating sensor and temperature
Sensor is arranged close to gear or position of bearings, if it is closed cabinet, then mounts on the shell.
A preferred embodiment of the invention, wherein lead between the signal acquisition unit, Cloud Server unit and client
It crosses internet and realizes data transmission；In work, when signal acquisition unit cannot connect to Cloud Server unit, it can incite somebody to action
The data temporary cache being collected is in memory, after being connected to Cloud Server unit and being successfully transmitted data, changes caching
Label.
A preferred embodiment of the invention, wherein the signal acquisition module further includes processing circuit, the processing circuit packet
Crystal oscillator circuit, reset circuit, filter circuit, voltage regulator circuit and firing program mouth circuit.
A preferred embodiment of the invention, wherein the signal acquisition module further includes communication interface and capture program, institute
Communication interface is stated using ICP/IP protocol, establishes connection with Cloud Server unit using IP address access；
The capture program is by the way of interrupt acquisition analog quantity, frequency acquisition >=5kHz, port number >=4 tunnels, each
Channel acquisition time 2s, collected data storage is in memory.
A preferred embodiment of the invention, wherein the memory uses the storage mode of data block, and acquisition is completed, number
Flash is transferred to according to from RAM.
Preferably, when storage space is filled with, and can not connect Cloud Server unit, new data can be by oldest stored
Data cover.
A preferred embodiment of the invention, wherein the software module further includes user management, database, images outputting
And data query.
Preferably, the Cloud Server unit has internet fixed ip addresse, using ICP/IP protocol, with signal acquisition
Unit and client communication.
A preferred embodiment of the invention, wherein the database includes user's table, equipment list, equipment record and number
According to table, user's table includes User ID, user name, password and unit name, and the equipment list includes that device number and equipment are returned
Belong to, equipment record includes acquisition time and its corresponding data table name, and the user management includes that user's registration, password are repaired
Change and is associated with equipment.
A preferred embodiment of the invention, wherein the client is presentation layer, for user's request to be sent to cloud clothes
It is engaged in device unit and is received the testing result that Cloud Server unit returns, and will test and come out as the result is shown.
A method of for rotating class mechanical remote monitoring and fault diagnosis, comprising the following steps:
(1) acceleration signal that rotary part generates at work is detected by sensor；
(2) working signal that sensor will test passes to processor, and stores into memory, passes through network module
It is sent to Cloud Server unit；
(3) data processing module carries out time-domain analysis and frequency-domain analysis to the collected working signal of sensor；
(4) time domain map is obtained according to time-domain analysis, and calculates kurtosis data k automatically, it is high and steep with the failure of user's typing
Degree is compared according to k ', and the analysis result to break down is obtained as k >=k '；
(5) spectrogram is obtained according to frequency-domain analysis, obtains live signal characteristic frequency f, and special with the failure of user's typing
Sign frequency f ' is compared, and the analysis result to break down is obtained as f >=f '.
A preferred embodiment of the invention, in step (1), the signal includes vibration frequency or/and operating temperature.
A preferred embodiment of the invention, in step (5), mode that the frequency-domain analysis generates spectrogram and voluntarily judges
It is as follows:
(1) it is found in VMD function with genetic algorithm, the optimal solution of parameter alpha and K:
A, objective function snmax=vmdfunction (K1, alpha1) is established, by inputting different K1 and alpha1
Value finds snmax maximum value；
B, ask parameter K1 and alpha1 corresponding most using matlab genetic algorithm function ga, iterative target function snmax
Excellent solution K and alpha, function are as follows:
[x, val]=ga (@snmax, nvars, [], [], [], [], lb, ub, [])；
Wherein, the number of arguments nvars=2 is set；Linear inequality constraint coefficient matrices A is nothing, is indicated with []；Linearly
Inequality constant matrices B is nothing, is indicated with []；Linear equality constraints coefficient matrices A eq is nothing, is indicated with []；Linear equality is normal
Number constraint number Beq is nothing, is indicated with []；Variable K and alpha lower limit lb takes [2,400]；Variable K and alpha upper limit ub takes
[20,4000]；Nonlinear restriction function nonlcon is nothing, is indicated with [].
(2) above-mentioned optimal solution K and alpha is substituted into above-mentioned VMD function, obtains u component, formula are as follows:
U=VMD (signal, alpha, tau, K, DC, init, tol)
Wherein signal is signal data, and alpha, K are the optimal solution found out in step (1), and parameter current noise is arranged
Error amount tau=0；Direct current component DC=0；Initial method init=0；Reconstruction error tol=1e-3；Current letter to be processed
Number group signal.
(3) spectrum analysis is carried out to u component:
A, automatic order judgement is carried out to u；
B, spectrum analysis is carried out to the u component of every single order, spectrogram is generated using the transform method of FFT, is checked for user；
C, fault characteristic frequency is compareed, whether judge automatically in the frequency spectrum of u component includes failure-frequency ingredient.
A preferred embodiment of the invention, in step (4), kurtosis data k is acquired by function formula below:
K=kurtosis (x)
Wherein, kurtosis (x) is function packaged in Matlab tool, and parameter x is real-time collected data, also
That is the acceleration information that detects of vibrating sensor.
Compared with the prior art, the invention has the following beneficial effects:
1, system of the invention can the rotary part at any time to the mechanical equipment in work detect, pass through acquisition number
According to, and the server at rear is sent data to, data are handled by the data processor in server, by control
Analysis, to voluntarily be judged, and transmits the result to client.
2, system through the invention, can be realized long-range monitoring, and technical staff can also set machinery without reaching scene
Standby rotary part is detected, time saving and energy saving.
It 3, in memory by all collected data storages, in this way can be to a large amount of in prolonged detection
Data carry out unified analysis, according to the tendency of big data, grasp the rule of its rotary part, and then push warning information, with
Just counter-measure is taken in advance.
Detailed description of the invention
Fig. 1 is the signal acquisition unit flow chart in the present invention.
Fig. 2 is the cloud server framework logic chart in the present invention.
Specific embodiment
In order to make those skilled in the art better understand technical solution of the present invention, below with reference to embodiment and attached drawing
The invention will be further described, but embodiments of the present invention are not limited only to this.
Referring to Fig. 1-2, in the present embodiment for rotating the system of class mechanical remote monitoring and fault diagnosis, including signal
Acquisition unit, Cloud Server unit and client；Wherein, the signal acquisition unit includes sensor and signal acquisition mould
Block, the sensor include vibrating sensor, vibrate generated acceleration signal for acquiring, the vibrating sensor installation
In the position close to detected object；The signal acquisition module includes processor, memory and network module；The sensing
The signal that device detects passes to processor, and stores into memory, is sent to Cloud Server unit by network module；Institute
Stating Cloud Server unit includes network server and software module, and the software module includes data processing module, the data
The data that processing module is used to send over signal acquisition unit carry out original analysis；The data processing module passes vibration
The collected vibration signal of sensor carries out time-domain analysis and frequency-domain analysis, wherein obtains time domain map according to time-domain analysis, and certainly
It is dynamic to calculate kurtosis data k, and compared with the failure kurtosis data k ' of user's typing, it obtains and breaks down as k >=k '
Analysis result；Spectrogram is obtained according to frequency-domain analysis, obtains real-time vibration frequency f, and frequently with the fault signature of user's typing
Rate f ' is compared, and the analysis result to break down is obtained as f >=f '；The client accesses Cloud Server list by network
Analysis result in member.
The sensor further includes temperature sensor, for the temperature signal in collecting work environment, the temperature sensing
Device is installed on close to the position of detected object.Generally, vibrating sensor and temperature sensor are arranged close to gear or axis
Position is held, if it is closed cabinet, is then mounted on the shell.
Data transmission is realized by internet between the signal acquisition unit, Cloud Server unit and client；Work
In, when signal acquisition unit cannot connect to Cloud Server unit, the data temporary cache being collected can deposited
In reservoir, after being connected to Cloud Server unit and being successfully transmitted data, change cache tag.
The signal acquisition module further includes processing circuit, communication interface and capture program, and the processing circuit includes
Crystal oscillating circuit, reset circuit, filter circuit, voltage regulator circuit and firing program mouth circuit；The communication interface uses TCP/IP
Agreement establishes connection with Cloud Server unit using IP address access；The capture program uses the side of interrupt acquisition analog quantity
Formula, frequency acquisition >=5kHz, port number >=4 tunnels, each channel acquisition time 2s, collected data storage is in memory.
When storage space is filled with, and can not connect Cloud Server unit, new data can be by the data cover of oldest stored.
The Cloud Server unit has internet fixed ip addresse, using ICP/IP protocol, with signal acquisition unit and
Client communication.
The memory uses the storage mode of data block, and acquisition is completed, and data are transferred to Flash from RAM.
The software module further includes user management, database, images outputting and data query, and the database includes
User's table, equipment list, equipment record and tables of data, user's table include User ID, user name, password and unit name,
The equipment list includes device number and equipment ownership, and the equipment record includes acquisition time and its corresponding data table name, institute
State user management include user's registration, password modification be associated with equipment.
The client is presentation layer, for being sent in Cloud Server unit and receiving Cloud Server for user's request
The testing result that unit returns, and will test and come out as the result is shown, it can be terminal computer or plate or mobile phone.
The method for being used to rotate class mechanical remote monitoring and fault diagnosis in the present embodiment, comprising the following steps:
(1) vibration frequency and temperature that rotary part generates at work are detected by sensor.
(2) working signal that sensor will test passes to processor, and stores into memory, passes through network module
It is sent to Cloud Server unit.
(3) data processing module carries out time-domain analysis and frequency-domain analysis to the collected working signal of sensor.
(4) time domain map is obtained according to time-domain analysis, and calculates kurtosis data k automatically, it is high and steep with the failure of user's typing
Degree is compared according to k ', and the analysis result to break down is obtained as k >=k '；Wherein, kurtosis data k passes through function below
Formula acquires:
K=kurtosis (x)
Wherein, kurtosis (x) is function packaged in Matlab tool, and parameter x is real-time collected data, also
That is acceleration information and temperature.
(5) spectrogram is obtained according to frequency-domain analysis, obtains live signal characteristic frequency f, and special with the failure of user's typing
Sign frequency f ' is compared, and the analysis result to break down is obtained as f >=f '；Specific processing mode is as follows:
One, the optimal solution of parameter is found with genetic algorithm:
A, objective function snmax=vmdfunction (K1, alpha1) is established, by inputting different K1 and alpha1
Value finds snmax maximum value.
B, ask parameter K1 and alpha1 corresponding most using matlab genetic algorithm function ga, iterative target function snmax
Excellent solution K and alpha, function are as follows:
[x, val]=ga (@snmax, 2, [], [], [], [], lb, ub, [], [12])；
Wherein, the number of arguments nvars=2 is set；Linear inequality constraint coefficient matrices A is nothing, is indicated with []；Linearly
Inequality constant matrices B is nothing, is indicated with []；Linear equality constraints coefficient matrices A eq is nothing, is indicated with []；Linear equality is normal
Number constraint number Beq is nothing, is indicated with []；Variable K and alpha lower limit lb takes [2,400]；Variable K and alpha upper limit ub takes
[20,4000]；Nonlinear restriction function nonlcon is nothing, is indicated with [].
Two, optimal solution K and alpha are substituted into VMD, obtain u component, formula are as follows:
U=VMD (signal, alpha, tau, K, DC, init, tol)
Wherein, signal is signal data, and alpha, K are the optimal solution found out in step (1), and parameter current noise is arranged
Error amount tau=0；Direct current component DC=0；Initial method init=0；Reconstruction error tol=1e-3；Current letter to be processed
Number group signal.
(3) spectrum analysis is carried out to u component:
A, automatic order judgement is carried out to u；
B, spectrum analysis is carried out to the u component of every single order, spectrogram is generated using the transform method of FFT, is checked for user；
C, fault characteristic frequency is compareed, whether judge automatically in the frequency spectrum of u component includes failure-frequency ingredient.
Above-mentioned is the preferable embodiment of the present invention, but embodiments of the present invention are not limited by the foregoing content,
His any changes, modifications, substitutions, combinations, simplifications done without departing from the spirit and principles of the present invention, should be
The substitute mode of effect, is included within the scope of the present invention.
Claims (10)
1. a kind of for rotating the system of class mechanical remote monitoring and fault diagnosis, which is characterized in that including signal acquisition unit,
Cloud Server unit and client；
Wherein, the signal acquisition unit includes sensor and signal acquisition module, and the sensor includes vibrating sensor, is used
Acceleration signal caused by vibrating in acquisition, the vibrating sensor are installed on close to the position of detected object；The letter
Number acquisition module includes processor, memory and network module；The signal that the sensor detects passes to processor, and
It stores in memory, Cloud Server unit is sent to by network module；
The Cloud Server unit includes network server and software module, and the software module includes data processing module, institute
It states data of the data processing module for sending over to signal acquisition unit and carries out original analysis；The data processing module pair
The collected vibration signal of vibrating sensor carries out time-domain analysis and frequency-domain analysis, wherein obtains time-domain diagram according to time-domain analysis
Spectrum, and kurtosis data k is calculated automatically, and is compared with the failure kurtosis data k ' of user's typing, it must set out as k >=k '
The analysis result of raw failure；Spectrogram is obtained according to frequency-domain analysis, obtains real-time vibration frequency f, and the failure with user's typing
Characteristic frequency f ' is compared, and the analysis result to break down is obtained as f >=f '；
The client accesses the analysis result in Cloud Server unit by network.
2. according to claim 1 for rotating the system of class mechanical remote monitoring and fault diagnosis, which is characterized in that institute
Stating sensor further includes temperature sensor, and for the temperature signal in collecting work environment, the temperature sensor, which is installed on, to be leaned on
The position of nearly detected object.
3. according to claim 1 for rotating the system of class mechanical remote monitoring and fault diagnosis, which is characterized in that institute
It states and data transmission is realized by internet between signal acquisition unit, Cloud Server unit and client；In work, when signal is adopted
Collection unit is when cannot connect to Cloud Server unit, by the data temporary cache being collected in memory, when being connected to
Cloud Server unit and after being successfully transmitted data, changes cache tag.
4. according to claim 1 for rotating the system of class mechanical remote monitoring and fault diagnosis, which is characterized in that institute
Stating signal acquisition module further includes processing circuit, which includes crystal oscillating circuit, reset circuit, filter circuit, pressure stabilizing electricity
Road and firing program mouth circuit.
5. according to claim 4 for rotating the system of class mechanical remote monitoring and fault diagnosis, which is characterized in that institute
Stating signal acquisition module further includes communication interface and capture program, and the communication interface uses ICP/IP protocol, uses IP address
Access establishes connection with Cloud Server unit；
The capture program is by the way of interrupt acquisition analog quantity, frequency acquisition >=5kHz, port number >=4 tunnels, each channel
Acquisition time 2s, collected data storage is in memory.
6. according to claim 1 or 5 for rotating the system of class mechanical remote monitoring and fault diagnosis, feature exists
In the memory uses the storage mode of data block, and acquisition is completed, and data are transferred to Flash from RAM.
7. according to claim 1 for rotating the system of class mechanical remote monitoring and fault diagnosis, which is characterized in that institute
Stating software module further includes user management, database, images outputting and data query；
The database includes that user's table, equipment list, equipment record and tables of data, user's table include User ID, user
Name, password and unit name, the equipment list include device number and equipment ownership, the equipment record include acquisition time and its
Corresponding data table name, the user management include user's registration, password modification be associated with equipment.
8. a kind of described in any item for rotating the system of class mechanical remote monitoring and fault diagnosis applied to claim 1-7
Method, which comprises the following steps:
(1) acceleration signal that rotary part generates at work is detected by vibrating sensor；
(2) working signal that vibrating sensor will test passes to processor, and stores into memory, passes through network module
It is sent to Cloud Server unit；
(3) data processing module carries out time-domain analysis and frequency-domain analysis to the collected working signal of vibrating sensor；
(4) time domain map is obtained according to time-domain analysis, and calculates kurtosis data k automatically, the failure kurtosis number with user's typing
It is compared according to k ', the analysis result to break down is obtained as k >=k '；
(5) spectrogram is obtained according to frequency-domain analysis, obtains live signal characteristic frequency f, and frequently with the fault signature of user's typing
Rate f ' is compared, and the analysis result to break down is obtained as f >=f '.
9. according to claim 8 for rotating the method for class mechanical remote monitoring and fault diagnosis, which is characterized in that step
Suddenly in (5), the mode that the frequency-domain analysis generates spectrogram and voluntarily judges is as follows:
(1) it is found in VMD function with genetic algorithm, the optimal solution of parameter alpha and K:
A, objective function snmax=vmdfunction (K1, alpha1) is established, by inputting different K1 and alpha1 values, is sought
Look for snmax maximum value；
B, using matlab genetic algorithm function ga, iterative target function snmax, the corresponding optimal solution of parameter K1 and alpha1 is sought
K and alpha, function are as follows:
[x, val]=ga (@snmax, nvars, [], [], [], [], lb, ub, [])；
Wherein, the number of arguments nvars=2 is set；Linear inequality constraint coefficient matrices A is nothing, is indicated with []；Linearly differ
Formula constant matrices B is nothing, is indicated with []；Linear equality constraints coefficient matrices A eq is nothing, is indicated with []；Linear equality constant is about
Beam number Beq is nothing, is indicated with []；Variable K and alpha lower limit 1b takes [2,400]；Variable K and alpha upper limit ub take [20,
4000]；Nonlinear restriction function nonlcon is nothing, is indicated with [].
(2) above-mentioned optimal solution K and alpha is substituted into above-mentioned VMD function, obtains u component, formula are as follows:
U=VMD (signal, alpha, tau, K, DC, init, tol)
Wherein signal is signal data, and alpha, K are the optimal solution found out in step (1), and parameter current noise error is arranged
Value tau=0；Direct current component DC=0；Initial method init=0；Reconstruction error tol=1e-3；Current signal number to be processed
Group signal.
(3) spectrum analysis is carried out to u component:
A, automatic order judgement is carried out to u；
B, spectrum analysis is carried out to the u component of every single order, spectrogram is generated using the transform method of FFT, is checked for user；
C, fault characteristic frequency is compareed, whether judge automatically in the frequency spectrum of u component includes failure-frequency ingredient.
10. according to claim 8 for rotating the method for class mechanical remote monitoring and fault diagnosis, which is characterized in that
In step (4), kurtosis data k is acquired by function formula below:
K=kurtosis (x)
Wherein, kurtosis (x) is function packaged in Matlab tool, and parameter x is real-time collected acceleration information.
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| CN113295445A (en) * | 2021-05-19 | 2021-08-24 | 郑州大学 | Vibration signal acquisition and fault real-time monitoring system and method for rotary machine |
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| CN110233776A (en) * | 2019-05-31 | 2019-09-13 | 湃方科技(北京)有限责任公司 | A kind of rotary-type mechanical equipment state monitoring method and equipment |
| CN113155469A (en) * | 2021-03-19 | 2021-07-23 | 黑龙江机智通智能科技有限公司 | Engine fault diagnosis alarm system and device |
| CN113295445A (en) * | 2021-05-19 | 2021-08-24 | 郑州大学 | Vibration signal acquisition and fault real-time monitoring system and method for rotary machine |
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