CN105738805A - Data analysis method and device - Google Patents
Data analysis method and device Download PDFInfo
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- CN105738805A CN105738805A CN201610074308.XA CN201610074308A CN105738805A CN 105738805 A CN105738805 A CN 105738805A CN 201610074308 A CN201610074308 A CN 201610074308A CN 105738805 A CN105738805 A CN 105738805A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/34—Testing dynamo-electric machines
Abstract
The objective of the invention is to provide a data analysis method and device. Parameter state classification is performed on detection data of each parameter within a preset time period according to a preset parameter state classification standard so that the parameter state within the preset time period is obtained; the parameters include one or multiple of the temperature parameter, the vibration parameter, the noise parameter, the current parameter and the electromagnetic field parameter of a motor sensor and the wind direction and wind speed parameters of a cooling motor; and matching of the state rules of the required motor state classification standard and the combination of the parameter state is performed so as to determine the motor state. Each parameter state, such as the temperature state and the vibration state, is obtained by performing parameter state classification on the detection data of each parameter based on the detection data of each parameter in operation of the motor; and then matching of the state rules of the required motor state classification standard and the combination of the parameter state is performed to determine the motor state so that analysis of faults or prediction of the service life can be realized.
Description
Technical field
The present invention relates to data analysis technique, particularly relate to a kind of data analysing method and device.
Background technology
At present, the Fuse Type temperature relay that domestic high iron machine uses can only play the function of detection motor temperature, can not meet far away the needs of Fault Analysis of Driving Motor, biometry.
Summary of the invention
It is an object of the invention to provide a kind of data analysing method and device, it is possible to realize Fault Analysis of Driving Motor and biometry.
The technical solution adopted for the present invention to solve the technical problems is:
A kind of data analysing method, including:
According to predetermined parameter state criteria for classification, respectively each parameter detection data within a predetermined period of time are carried out parameter state classification, obtain this parameter state in predetermined amount of time；It is one or more that described parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；
The combination of the state of required motor state classification standard rule and parameter state is mated, it is determined that motor status.
On this basis, further, each parameter detection data within a predetermined period of time are quantity of state or process variable.
On the basis of above-mentioned any embodiment, further, each parameter detection data within a predetermined period of time are carried out the mode of parameter state classification based on time domain or frequency domain.
On the basis of above-mentioned any embodiment, further, motor status criteria for classification includes failure modes standard and life-span criteria for classification.
On the basis of above-mentioned any embodiment, further, the acquisition mode of required motor state classification standard is:
According to the instruction that user sends, obtain required motor state classification standard；Or,
According to clock rate, it is determined that required motor state classification standard.
On the basis of above-mentioned any embodiment, further, each state rule of motor status criteria for classification one or more groups parameter state corresponding.
On the basis of above-mentioned any embodiment, further, also include:
According to motor status, start alarm device.
A kind of data analysis set-up, including:
Each parameter detection data within a predetermined period of time for according to predetermined parameter state criteria for classification, are carried out parameter state classification, obtain this parameter state in predetermined amount of time by parameter state sort module respectively；It is one or more that described parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；
Motor status matching module, for mating the combination of the state of required motor state classification standard rule and parameter state, it is determined that motor status.
On this basis, further, the mode of described motor status matching module acquisition required motor state classification standard is:
According to the instruction that user sends, obtain required motor state classification standard；Or,
According to clock rate, it is determined that required motor state classification standard.
On the basis of above-mentioned any embodiment, further, also include:
Alarm module, for according to motor status, starting alarm device.
The invention has the beneficial effects as follows:
It is an object of the invention to provide a kind of data analysing method and device, according to predetermined parameter state criteria for classification, respectively each parameter detection data within a predetermined period of time are carried out parameter state classification, obtain this parameter state in predetermined amount of time；It is one or more that described parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；The combination of the state of required motor state classification standard rule and parameter state is mated, it is determined that motor status.The present invention, based on the detection data of parameters in motor operation, is classified by the parameter state of the detection data to parameters, obtains parameters state, for instance state of temperature and vibrational state etc.；Mate again through by the state rule of required motor state classification standard and the combination of parameter state, it is determined that motor status, it is achieved to the analysis of fault or the prediction etc. to the life-span.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the present invention is further described.
Fig. 1 illustrates the flow chart of a kind of data analysing method that the embodiment of the present invention provides；
Fig. 2 illustrates the structural representation of a kind of data analysis set-up that the embodiment of the present invention provides.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein is only in order to explain the present invention, is not intended to limit the present invention.
Specific embodiment one
As it is shown in figure 1, embodiments provide a kind of data analysing method, including:
Each parameter detection data within a predetermined period of time according to predetermined parameter state criteria for classification, are carried out parameter state classification, obtain this parameter state in predetermined amount of time by step S101 respectively；It is one or more that parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；
Step S102, mates the combination of the state of required motor state classification standard rule and parameter state, it is determined that motor status.
Predetermined amount of time can be one day, one week, one month or 1 year.State rule in parameter state criteria for classification is predetermined, and for temperature parameter, state of temperature can be normal, abnormal；Can also be high temperature, low temperature；It can also be numerical range standard；For the ease of labeled bracketing result, it is also possible to be numbered for parameter state.In like manner, the state rule in motor status criteria for classification is also predetermined, and motor status includes malfunction and the service life state of motor, and malfunction can be stator failure, rotor fault, bearing fault etc.；Service life state can be the length of bimetry.Electrical fault includes electric fault and mechanical breakdown.Electric fault includes the open circuit of coil windings, short circuit, the connection error of winding, and wired earth is bad, and wire connection impedance is excessive, main relevant to temperature parameter, electromagnetic field parameters and current parameters.Mechanical breakdown includes shaft bending, bearing fault, bolt looseness, magnet fault, rotor fault, gearbox fault, non-uniform air-gap etc., and these faults are main and temperature parameter, vibration parameters, noise parameters, electromagnetic field parameters, and current parameters is correlated with.The combination of the state of required motor state classification standard rule and parameter state is mated, the i.e. state combined in the corresponding one or more motor status criteria for classification rule of parameter state, as long as situation about comprising in the combination of parameter state in state rule, mean that the motor status occurring that this state rule is corresponding.The embodiment of the present invention, based on the detection data of parameters in motor operation, is classified by the parameter state of the detection data to parameters, is obtained parameters state, for instance state of temperature and vibrational state etc.；Mate again through by the state rule of required motor state classification standard and the combination of parameter state, it is determined that motor status, it is achieved to the analysis of fault or the prediction etc. to the life-span.
The data mode of the detection data of parameters is not limited by the embodiment of the present invention, and each parameter detection data within a predetermined period of time can be quantity of state or process variable.
The mode that the detection data of parameters are carried out parameter state classification by the embodiment of the present invention does not limit, it is preferred that the mode that each parameter detection data within a predetermined period of time carry out parameter state classification can based on time domain or frequency domain.Based on the detection of time domain, mainly for electric fault；Based on the detection of frequency domain, it is primarily directed to mechanical breakdown.The mode that each parameter detection data within a predetermined period of time carry out parameter state classification can also is that the fault diagnosis based on model, for instance neutral net；Artificial intelligence；Finite element；Mathematical model based on dominant circuit；Fuzzy logic analysis.
Motor status criteria for classification is not limited by the embodiment of the present invention, it is preferred that motor status criteria for classification can include failure modes standard and life-span criteria for classification.Failure modes standard can also be sub-divided into the classification of each component faults, and life-span classification can also be sub-divided into the biometry of each assembly.
The acquisition mode of motor status criteria for classification is not limited by the embodiment of the present invention, preferably, the acquisition mode of required motor state classification standard can be the instruction sent according to user, obtain required motor state classification standard, such as when the instruction that user sends is accident analysis, required motor state classification standard is failure modes standard；When the instruction that user sends is biometry, required motor state classification standard is life-span criteria for classification.Or, the acquisition mode of required motor state classification standard can also be according to clock rate, it is determined that required motor state classification standard.
In the embodiment of the present invention, each state rule of motor status criteria for classification can one or more groups parameter state corresponding.Parameter state corresponding to the state rule of such as air cooling system fault can include stator temperature higher than certain temperature threshold and wind speed beyond certain wind speed threshold value.Therefore stator temperature height illustrates that its air cooling system lost efficacy, higher than certain wind speed threshold value, wind speed also illustrates that air cooling system lost efficacy, namely stator temperature abnormal parameters and wind speed parameter can detect the fault of air cooling system extremely, advantage of this is that, increase redundancy and the reliability of this data analysing method of the embodiment of the present invention, when certain parameter cannot normal operation time, obtaining the detection data of other parameters also can motor conditions sensed in time.
On the basis of above-mentioned any embodiment, further, it is also possible to include, according to motor status, starting alarm device.Embodiments provide warning function, when motor status is in alert levels, it is possible to start alarm device automatic alarm, advantage of this is that, improve the safety of motor work.
Specific embodiment two
As in figure 2 it is shown, embodiments provide a kind of data analysis set-up, including:
Each parameter detection data within a predetermined period of time for according to predetermined parameter state criteria for classification, are carried out parameter state classification, obtain this parameter state in predetermined amount of time by parameter state sort module 201 respectively；It is one or more that parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；
Motor status matching module 202, for mating the combination of the state of required motor state classification standard rule and parameter state, it is determined that motor status.
The detection data of parameters in running based on motor, the parameter state of the detection data of parameters is classified by parameter state sort module 201, obtains parameters state, for instance state of temperature and vibrational state etc.；The state rule of required motor state classification standard and the combination of parameter state are mated by motor status matching module 202, it is determined that motor status, it is achieved to the analysis of fault or the prediction etc. to the life-span.
The mode that motor status matching module is obtained motor status criteria for classification by the embodiment of the present invention does not limit, preferably, it can be the instruction sent according to user that motor status matching module 202 obtains the mode of required motor state classification standard, obtains required motor state classification standard；Or it is according to clock rate, it is determined that required motor state classification standard.
On the basis of above-mentioned any embodiment, further, also include alarm module, for according to motor status, starting alarm device.
Specific embodiment three
Embodiments provide the data analysing method of a kind of stator failure, including:
Each parameter detection data within a predetermined period of time according to predetermined parameter state criteria for classification, are carried out parameter state classification, obtain this parameter state in predetermined amount of time by step S301 respectively；Parameter includes the wind direction and wind velocity parameter of the temperature parameter relevant to stator failure, vibration parameters, current parameters and cooling motor；
Step S302, mates the combination of the state of required motor state classification standard rule and parameter state, it is determined that motor status.
Stator failure includes defect unshakable in one's determination, circulation, ground connection, and winding insulation damages, gate break.Damaging for wherein winding insulation, thermal stress is the most important reason causing winding insulation damaged, and parameter therefore associated with it includes temperature parameter.By temperature sensor or infrared sensor, the temperature of monitoring motor stator, the detection data of temperature parameter are carried out parameter state classification, obtains state of temperature, for instance whether higher than predetermined temperature threshold；Find the criteria for classification of required motor state classification standard and winding state, and mate with state of temperature, it is assumed that said temperature state correspondence winding insulation damages, then can determine that the situation occurring that winding insulation damages.
Specific embodiment four
Stator aging effects electrical machinery life, additionally, electrical machinery life is also and bearing, rotor bar breaking fault, fault of eccentricity, Damper Winding fault, fault of demagnetizing, interturn in stator windings fault, rotor turn-to-turn fault is relevant.In certain frequency of vibration section, vibration distorted signal is more few, and the stator life-span is more long；In certain frequency of vibration section, vibration distorted signal amplitude is more few, and the stator life-span is more long；In certain frequency of vibration section, vibration phase deviation is more few, and the stator life-span is more long；Under certain operating conditions (load, ambient temperature, voltage), in stator, temperature jump amplitude is more few, and the stator life-span is more long；Under certain operating conditions (load, ambient temperature, voltage), the temperature PROFILE temperature difference is more few, and the stator life-span is more long；Under certain operating conditions (load, ambient temperature, voltage), local discharge signal amplitude is more few, and the stator life-span is more long；Under certain operating conditions (load, ambient temperature, voltage), local discharge signal frequency is more few, and the stator life-span is more long.Therefore for the prediction in motor stator life-span, it is necessary to consider many factors, including vibration parameters, temperature parameter and current parameters.
Embodiments provide the data analysing method in a kind of stator life-span, including:
Each parameter detection data within a predetermined period of time according to predetermined parameter state criteria for classification, are carried out parameter state classification, obtain this parameter state in predetermined amount of time by step S401 respectively；Parameter includes the temperature parameter relevant to the stator life-span, vibration parameters and current parameters；
Step S402, mates the combination of the state of required motor state classification standard rule and parameter state, it is determined that motor status.
The detection data of temperature parameter, vibration parameters and current parameters are carried out parameter state classification, obtain state of temperature, vibrational state and current status by the monitoring temperature parameter of stator, vibration parameters and current parameters respectively；Find the criteria for classification of required motor state classification standard and stator biometry, and mate with the combination of state of temperature, vibrational state and current status, assume that the stator life-span that above three parameter state is corresponding is 256～300 hours, then measurable when the front stator life-span be 256～300 little time.
Although present invention has been a degree of description, it will be apparent that, without departing from the spirit and scope of the present invention when, can carry out the suitable change of each condition.Being appreciated that and the invention is not restricted to described embodiment, and be attributed to scope of the claims, it includes the equivalent replacement of described each factor.
Claims (10)
1. a data analysing method, it is characterised in that including:
According to predetermined parameter state criteria for classification, respectively each parameter detection data within a predetermined period of time are carried out parameter state classification, obtain this parameter state in predetermined amount of time；It is one or more that described parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；
The combination of the state of required motor state classification standard rule and parameter state is mated, it is determined that motor status.
2. data analysing method according to claim 1, it is characterised in that each parameter detection data within a predetermined period of time are quantity of state or process variable.
3. data analysing method according to claim 1, it is characterised in that each parameter detection data within a predetermined period of time are carried out the mode of parameter state classification based on time domain or frequency domain.
4. data analysing method according to claim 1, it is characterised in that motor status criteria for classification includes failure modes standard and life-span criteria for classification.
5. data analysing method according to claim 1, it is characterised in that the acquisition mode of required motor state classification standard is:
According to the instruction that user sends, obtain required motor state classification standard；Or,
According to clock rate, it is determined that required motor state classification standard.
6. data analysing method according to claim 1, it is characterised in that each state rule one or more groups parameter state corresponding of motor status criteria for classification.
7. the data analysing method according to any one of claim 1-6, it is characterised in that also include:
According to motor status, start alarm device.
8. a data analysis set-up, it is characterised in that including:
Each parameter detection data within a predetermined period of time for according to predetermined parameter state criteria for classification, are carried out parameter state classification, obtain this parameter state in predetermined amount of time by parameter state sort module respectively；It is one or more that described parameter includes in the wind direction and wind velocity parameter of the temperature parameter of electromechanical transducer, vibration parameters, noise parameters, current parameters, electromagnetic field parameters and cooling motor；
Motor status matching module, for mating the combination of the state of required motor state classification standard rule and parameter state, it is determined that motor status.
9. data analysis set-up according to claim 8, it is characterised in that described motor status matching module obtains the mode of required motor state classification standard and is:
According to the instruction that user sends, obtain required motor state classification standard；Or,
According to clock rate, it is determined that required motor state classification standard.
10. data analysis set-up according to claim 8, it is characterised in that also include:
Alarm module, for according to motor status, starting alarm device.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201610074308.XA CN105738805A (en) | 2016-02-02 | 2016-02-02 | Data analysis method and device |
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| CN201610074308.XA CN105738805A (en) | 2016-02-02 | 2016-02-02 | Data analysis method and device |
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| CN105738805A true CN105738805A (en) | 2016-07-06 |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112148749A (en) * | 2020-11-24 | 2020-12-29 | 车智互联（北京）科技有限公司 | Data analysis method, computing device and storage medium |
| CN112556755A (en) * | 2020-12-07 | 2021-03-26 | 广东鉴面智能科技有限公司 | Method and device for judging fault according to motor temperature |
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Patent Citations (4)
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| JP2000092792A (en) * | 1998-09-17 | 2000-03-31 | Hitachi Building Systems Co Ltd | Diagnostic apparatus for motor |
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| CN1611955A (en) * | 2003-05-17 | 2005-05-04 | 杜玉晓 | Distributed intelligent monitoring system for motor |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112148749A (en) * | 2020-11-24 | 2020-12-29 | 车智互联（北京）科技有限公司 | Data analysis method, computing device and storage medium |
| CN112148749B (en) * | 2020-11-24 | 2021-04-20 | 车智互联（北京）科技有限公司 | Data analysis method, computing device and storage medium |
| CN112556755A (en) * | 2020-12-07 | 2021-03-26 | 广东鉴面智能科技有限公司 | Method and device for judging fault according to motor temperature |
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Application publication date: 20160706 |