CN115571585B - Belt conveyor intelligent diagnosis method based on characteristic value alarm - Google Patents
Belt conveyor intelligent diagnosis method based on characteristic value alarm Download PDFInfo
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- CN115571585B CN115571585B CN202211462754.XA CN202211462754A CN115571585B CN 115571585 B CN115571585 B CN 115571585B CN 202211462754 A CN202211462754 A CN 202211462754A CN 115571585 B CN115571585 B CN 115571585B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G43/00—Control devices, e.g. for safety, warning or fault-correcting
- B65G43/02—Control devices, e.g. for safety, warning or fault-correcting detecting dangerous physical condition of load carriers, e.g. for interrupting the drive in the event of overheating
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G15/00—Conveyors having endless load-conveying surfaces, i.e. belts and like continuous members, to which tractive effort is transmitted by means other than endless driving elements of similar configuration
- B65G15/30—Belts or like endless load-carriers
- B65G15/32—Belts or like endless load-carriers made of rubber or plastics
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G45/00—Lubricating, cleaning, or clearing devices
- B65G45/02—Lubricating devices
- B65G45/04—Lubricating devices for rollers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G2203/00—Indexing code relating to control or detection of the articles or the load carriers during conveying
- B65G2203/02—Control or detection
- B65G2203/0266—Control or detection relating to the load carrier(s)
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- Engineering & Computer Science (AREA)
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- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention provides a belt conveyor intelligent diagnosis method based on characteristic value alarming, which comprises the following steps: searching the frequency of the equipment, comparing the amplitude, and setting an alarm line; if the diagnosis amplitude value belongs to the equipment fault type, entering an equipment fault type diagnosis process if the diagnosis amplitude value belongs to the equipment fault type, and otherwise, entering a step S3; and if the frequency of the diagnostic equipment belongs to the bearing fault type, entering a bearing fault type diagnostic process if the frequency of the diagnostic equipment belongs to the bearing fault type, and if the frequency of the diagnostic equipment does not belong to the bearing fault type, judging that the equipment has no fault. The invention has the beneficial effects that: the problem that the automatic alarm of the equipment only represents the integral running state of the equipment is solved, and the intelligent alarm can automatically position the fault according to the unique fault characteristic frequency of the equipment component; the problem of alarm of a fault building of some important parts is avoided, and the alarm accuracy of the system is improved; meanwhile, the working efficiency of personnel for fault diagnosis through frequency spectrum is improved.
Description
Technical Field
The invention belongs to the technical field of mechanical fault diagnosis, and particularly relates to a belt conveyor intelligent diagnosis method based on characteristic value alarming.
Background
In the prior art, mechanical fault diagnosis automatic alarm is still in an overall alarm state at present, and only total value alarm and effective value alarm are distinguished, the alarm principle is based on that a time domain waveform computer acquired by a sensor calculates all frequencies in the whole data to obtain an overall characteristic quantity, and the characteristic quantity only possibly represents an overall state condition of equipment. The first case when there is a problem with the device: since this particular quantity is calculated from the entire piece of data with some rare faults and does not trigger an alarm of the system; in the second case: the system triggers an alarm, but only prompts that the equipment is in a bad state, the regulation severity of the equipment cannot be accurately reflected, and the fault position and the fault component of the equipment cannot be reflected.
Disclosure of Invention
In view of the above, the present invention is directed to a belt conveyor intelligent diagnosis method based on a characteristic value alarm, so as to solve the above-mentioned deficiencies of the prior art.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
a belt conveyor intelligent diagnosis method based on characteristic value alarming comprises the following steps:
s1, searching equipment frequency and comparing amplitude, and setting an alarm line;
s2, diagnosing whether the amplitude belongs to the equipment fault type or not according to the alarm line, if so, entering an equipment fault type diagnosis process, and if not, entering a step S3;
and S3, diagnosing whether the frequency of the equipment belongs to the bearing fault type according to an alarm line, if so, entering a bearing fault type diagnosis process, and if not, judging that the equipment has no fault.
Further, the setting of the alarm line in step S1 includes the following steps:
s11, according to frequency groups in historical data frequency spectrums of the equipment database, a plurality of frequency groups with the maximum amplitude are selected;
s12, calculating the average value of a plurality of maximum amplitude values
Setting four grades of normal, early warning, alarming and danger respectively;
s13, setting
In order to be normal, the operation of the device is carried out,
in order to provide an early warning,
an alarm is given out, and the alarm is given out,
for danger, simultaneously setting alarm when the edge frequency amplitude is more than or equal to 30 percent of the central frequency amplitude, alarm when the edge frequency number is more than or equal to the maximum edge frequency number average number plus 4, and alarm when the side band number is more than or equal to the maximum edge frequency number average number plus 4And alarming when the frequency amplitude is greater than or equal to 50% of the central frequency amplitude.
Further, the device fault type diagnosis process in step S2 includes the following steps:
s21, judging whether the amplitude value of 1X exceeds an alarm line, if so, entering a step S22, and if not, entering a step S25;
s22, judging whether the harmonic frequency amplitude exceeds an alarm line, if so, entering a step S23, and if not, judging that the output equipment has an unbalance fault;
s23, judging whether the 2X frequency amplitude is larger than or equal to 1X, if so, judging that the output equipment has a centering fault, otherwise, entering the step S24;
s24, judging whether the fundamental frequency and the harmonic frequency thereof have polar passing frequency sidebands, if so, judging that the rotor bars of the output equipment break and fail, and if not, judging that the output equipment has a structure loosening fault;
s25, judging whether the 2X frequency amplitude exceeds an alarm line, if so, if the output equipment has a centering fault, otherwise, the step S26 is carried out;
s26, judging whether the passing frequency of the rotor bars exceeds an alarm line, the harmonic frequency of the rotor bars exists and the frequency is 2FL, if yes, judging that the output equipment has an electrical fault, and if not, entering the step S3.
Further, the bearing fault type diagnosis process in step S3 includes the following steps:
s31, judging whether an energy cluster exists in the high-frequency range of 2000-8000Hz or not and whether the overall total value exceeds an alarm line or not, if so, simultaneously entering the steps S32, S33, S34 and S35, and if not, judging that the equipment has no fault;
s32, judging whether the characteristic frequency of the bearing outer ring fault or the harmonic frequency amplitude exceeds an alarm line, if so, outputting the bearing outer ring fault, and if not, outputting poor lubrication of the bearing;
s33, judging whether inner ring fault characteristic frequency exists or whether harmonic frequency amplitude exceeds an alarm line and a frequency conversion sideband exists, if yes, outputting bearing inner ring faults, and if not, outputting poor lubrication of the bearing;
s34, judging whether the characteristic frequency of the fault of the rolling body or the harmonic frequency amplitude of the fault of the rolling body exceeds an alarm line, if so, outputting the fault of the rolling body of the bearing, and if not, outputting poor lubrication of the bearing;
s35, judging whether the characteristic frequency of the fault of the retainer or the harmonic frequency amplitude of the fault exceeds an alarm line, if so, judging that the retainer of the output bearing has a fault, and if not, judging that the lubrication of the output bearing is poor.
Compared with the prior art, the belt conveyor intelligent diagnosis method based on characteristic value alarming has the following advantages:
the belt conveyor intelligent diagnosis method based on characteristic value alarming solves the problems that automatic alarming of equipment only represents the integral operation state of the equipment, field workers often do not have deep training for analyzing the equipment according to frequency spectrum, and the fault position of the equipment cannot be known in alarming information, so that the effect of an intelligent diagnosis system is reduced; the intelligent alarm can automatically locate the fault according to the unique fault characteristic frequency of the equipment component; the problem of alarm of a fault building of some important parts is avoided, and the alarm accuracy of the system is improved; meanwhile, the working efficiency of personnel for fault diagnosis through frequency spectrum is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic view of an overall method diagnosis process according to an embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "central," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientations and positional relationships indicated in the drawings, which are based on the orientations and positional relationships indicated in the drawings, and are used for convenience in describing the present invention and for simplicity in description, but do not indicate or imply that the device or element so referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
As shown in fig. 1, a belt conveyor intelligent diagnosis method based on characteristic value alarm includes the following steps:
s1, searching equipment frequency and comparing amplitude, and setting an alarm line;
s2, diagnosing whether the amplitude belongs to the equipment fault type or not according to the alarm line, if so, entering an equipment fault type diagnosis process, and if not, entering a step S3;
and S3, diagnosing whether the frequency of the equipment belongs to the bearing fault type according to an alarm line, if so, entering a bearing fault type diagnosis process, and if not, judging that the equipment has no fault.
The invention solves the problems that the automatic alarm of the equipment only represents the integral running state of the equipment, field workers often do not have deep training for analyzing the equipment according to frequency spectrum and cannot know the fault position of the equipment in alarm information, thus reducing the effect of an intelligent diagnosis system; the intelligent alarm can automatically locate the fault according to the unique fault characteristic frequency of the equipment component; the problem of alarm of a fault building of some important parts is avoided, and the alarm accuracy of the system is improved; meanwhile, the working efficiency of personnel performing fault diagnosis through frequency spectrum is improved.
In a preferred embodiment of the present invention, the setting of the alarm line in step S1 includes the steps of:
s11, according to frequency groups in historical data frequency spectrums of the equipment database, a plurality of frequency groups with the maximum amplitude are selected;
s12, calculating the average value of a plurality of maximum amplitude values
Setting four grades of normal, early warning, alarming and danger respectively;
s13, setting
In order to be normal, the operation of the device is carried out,
in order to provide an early warning,
an alarm is given out, and the alarm is given out,
and (4) alarming when the side frequency amplitude is larger than or equal to 30% of the central frequency amplitude, alarming when the side frequency number is larger than or equal to the maximum side frequency number average plus 4, and alarming when the side frequency amplitude is larger than or equal to 50% of the central frequency amplitude.
In a preferred embodiment of the present invention, the device fault type diagnosis process in step S2 includes the following steps:
s21, judging whether the amplitude value of 1X exceeds an alarm line, if so, entering a step S22, and if not, entering a step S25;
s22, judging whether the harmonic frequency amplitude exceeds an alarm line, if so, entering a step S23, and if not, judging that the output equipment has an unbalanced fault;
s23, judging whether the 2X frequency amplitude is larger than or equal to 1X, if so, judging that the output equipment has a centering fault, otherwise, entering the step S24;
s24, judging whether the fundamental frequency and the harmonic frequency thereof have polar passing frequency sidebands, if so, judging that the rotor bars of the output equipment break and fail, and if not, judging that the output equipment has a structure loosening fault;
s25, judging whether the 2X frequency amplitude exceeds an alarm line, if so, judging that the output equipment has a centering fault, otherwise, entering a step S26;
s26, judging whether the passing frequency of the rotor bars exceeds an alarm line, the harmonic frequency exists and the frequency is 2FL, if yes, judging that the output equipment has an electrical fault, and if not, entering the step S3.
In a preferred embodiment of the present invention, the bearing fault type diagnosis process in step S3 includes the steps of:
s31, judging whether an energy cluster exists in the high-frequency range of 2000-8000Hz or not and whether the overall total value exceeds an alarm line (the total value calculation does not contain harmonic frequency components related to the masterwork), if so, simultaneously entering the steps S32, S33, S34 and S35, and if not, judging that the equipment has no fault;
s32, judging whether the characteristic frequency (frequency error +/-4%) of the bearing outer ring fault or the harmonic frequency amplitude exceeds an alarm line, if so, outputting the bearing outer ring fault, otherwise, outputting poor lubrication of the bearing;
s33, judging whether inner ring fault characteristic frequency exists or whether harmonic frequency amplitude exceeds an alarm line and a frequency conversion sideband exists, if yes, outputting bearing inner ring faults, and if not, outputting poor lubrication of the bearing;
s34, judging whether the characteristic frequency of the fault of the rolling body or the harmonic frequency amplitude of the fault of the rolling body exceeds an alarm line, if so, outputting the fault of the rolling body of the bearing, and if not, outputting poor lubrication of the bearing;
s35, judging whether the characteristic frequency of the fault of the retainer or the harmonic frequency amplitude of the fault exceeds an alarm line, if so, judging that the retainer of the output bearing has a fault, and if not, judging that the lubrication of the output bearing is poor.
Example 1
At present, the main principle of detecting equipment through vibration signal acquisition is that the amplitude of vibration of equipment (components) is higher than that of normal vibration when a fault occurs, and each component of the equipment has unique fault characteristic frequency, so that the amplitude and the structural change of the fault characteristic frequency of the component of the equipment are observed through frequency spectrum to judge the health condition of the equipment. It is particularly important to obtain the fault signature of the equipment components for each frequency and to identify the amplitude of these frequencies in the spectrum, as well as the spectral structure variations.
Setting and triggering conditions for automatic generation of alarm lines:
assuming that the equipment normally operates for a long enough time, the alarm line is set according to a corresponding frequency group (such as a gear is damaged and a sideband with a fault axis standard is added with the meshing frequency to form a frequency group) in a historical data frequency spectrum, a plurality of frequency groups (such as 10, 50 and 100 groups) with the maximum amplitude are taken, and the average value of a plurality of maximum amplitudes is obtained
Respectively setting four grades of normal, early warning, alarming and danger,
is normal,
Early warning,
An alarm is given,
And (4) danger. And simultaneously, alarming when the edge frequency amplitude is larger than or equal to 30 percent of the central frequency amplitude, and alarming when the edge frequency number is larger than or equal to the average number of the maximum edge frequency number plus 4. And when the amplitude of the sideband frequency is greater than or equal to 50% of the amplitude of the central frequency, an alarm is triggered.
The belt conveyor driving system can obtain information useful for vibration diagnosis in actual production, and comprises the following steps: the motor stage number (converted into frequency output); the number of motor rotor bars (rotor bar passing frequency); the motor operating current frequency; motor speed (frequency); a slip frequency; motor bearing model, obtainable by the following bearing model:
1. the outer ring fault passing frequency of the characteristic coefficient of the outer ring of the bearing;
2. the failure passing frequency of the inner ring of the bearing inner ring characteristic coefficient;
3. bearing rolling element characteristic coefficient rolling element fault passing frequency;
4. bearing cage characteristic coefficient rolling element fault passing frequency.
The number of shafts of the speed reducer; the number of teeth of each level of the speed reducer (converted into meshing frequency for output); the speed ratio of the speed reducer and the output rotating speed of the speed reducer (converted into the input and output rotating frequency of the speed reducer); the models (characteristic coefficients) of all levels of bearings of the speed reducer are the same as the models of bearings of the motor; the belt pulley drives the rotating speed of the roller; drive roller diameter (circumference); a belt length; the belt passing frequency can be obtained by the rotating speed of the belt pulley driving roller, the diameter (perimeter) of the driving roller and the length of the belt.
Detailed description:
1X: frequency conversion of a device driving part; 2X, 3X, 4X …: harmonic frequencies of the device driver component frequency transitions; FL: the current frequency at which the device operates normally; PPF: pole pass frequency; RBF: rotor bar pass frequency; f. of o : outer ring fault frequency; f. of i : inner ring failure frequency; f. of R : frequency of rolling element failure; f. of c : cage failure frequency.
1) Main fault frequency of motor and calculation method
Loosening: 1XHz rising with 2X, 3X … harmonics;
unbalance: 1XHz rises and is much higher than 2X, 3X … (judging that 1X is more than 1.5 times 2X, 3X …);
centering: 1X and 2X are increased, and the 2X amplitude is more than or equal to 70 percent of the 1X amplitude;
and (3) breaking the rotor bars: 1X, 2X, 3X … are present with a pole pass frequency;
rotor bar loosening (electrical failure): 1X (number of rotor cages) with a sideband of FL X2 Hz;
bearing failure, see the diagnostic flow chart.
2) Main fault frequency of speed reducer and calculation method
Poor meshing and abrasion of gears at all stages:
bearing failure, see the diagnostic flow chart.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (5)
1. A belt conveyor intelligent diagnosis method based on characteristic value alarming is characterized in that: the method comprises the following steps:
s1, searching equipment frequency and comparing amplitude, and setting an alarm line;
s2, diagnosing whether the amplitude belongs to the equipment fault type or not according to the alarm line, if so, entering an equipment fault type diagnosis process, and if not, entering a step S3;
s3, diagnosing whether the frequency of the equipment belongs to the bearing fault type or not according to an alarm line, if so, entering a bearing fault type diagnosis process, and if not, judging that the equipment has no fault;
the setting of the alarm line in step S1 includes the steps of:
s11, according to frequency groups in historical data frequency spectrums of the equipment database, a plurality of frequency groups with the maximum amplitude are selected;
s12, calculating the average value of a plurality of maximum amplitude values
Setting four grades of normal, early warning, alarming and danger respectively;
s13, setting
In order to be normal, the operation of the device is carried out,
in order to provide an early warning,
an alarm is given to the user, and the alarm is given,
setting alarm when the edge frequency amplitude is more than or equal to 30% of the central frequency amplitude and alarm when the edge frequency number is more than or equal to the average number of the maximum edge frequency number plus 4;
the device fault type diagnosis process in step S2 includes the steps of:
s21, judging whether the amplitude value of 1X exceeds an alarm line, if so, entering a step S22, and if not, entering a step S25;
s22, judging whether the harmonic frequency amplitude exceeds an alarm line, if so, entering a step S23, and if not, judging that the output equipment has an unbalanced fault;
s23, judging whether the 2X frequency amplitude is larger than or equal to 1X, if so, judging that the output equipment has a centering fault, otherwise, entering the step S24;
s24, judging whether the fundamental frequency and the harmonic frequency thereof have polar passing frequency sidebands, if so, judging that the rotor bars of the output equipment have a breakage fault, otherwise, judging that the output equipment has a structure loosening fault;
s25, judging whether the 2X frequency amplitude exceeds an alarm line, if so, judging that the output equipment has a centering fault, otherwise, entering the step S26;
s26, judging whether the passing frequency of the rotor bars exceeds an alarm line, the harmonic frequency exists and the harmonic frequency is 2FL, if yes, judging that the output equipment has an electrical fault, and if not, entering the step S3;
wherein 1X represents a device driving part frequency conversion; 2X represents a harmonic frequency of the device driving part frequency conversion; 2FL represents twice the frequency of the normal operating current of the device.
2. The belt conveyor intelligent diagnosis method based on characteristic value alarming as claimed in claim 1, is characterized in that: the bearing fault type diagnosis process in step S3 includes the steps of:
s31, judging whether an energy cluster exists in the high-frequency range of 2000-8000Hz or not and whether the overall total value exceeds an alarm line or not, if so, simultaneously entering the steps S32, S33, S34 and S35, and if not, judging that the equipment has no fault;
s32, judging whether the characteristic frequency of the bearing outer ring fault or the harmonic frequency amplitude exceeds an alarm line, if so, outputting the bearing outer ring fault, and if not, outputting poor lubrication of the bearing;
s33, judging whether inner ring fault characteristic frequency exists or whether harmonic frequency amplitude exceeds an alarm line and a frequency conversion sideband exists, if yes, outputting bearing inner ring faults, and if not, outputting poor lubrication of the bearing;
s34, judging whether the characteristic frequency of the rolling element fault or the harmonic frequency amplitude exceeds an alarm line, if so, outputting the bearing rolling element fault, otherwise, outputting poor lubrication of the bearing;
s35, judging whether the characteristic frequency of the fault of the retainer or the harmonic frequency amplitude of the fault exceeds an alarm line, if so, judging that the retainer of the output bearing has a fault, and if not, judging that the lubrication of the output bearing is poor.
3. An electronic device comprising a processor and a memory communicatively coupled to the processor and configured to store processor-executable instructions, wherein: the processor is used for executing the belt conveyor intelligent diagnosis method based on the characteristic value alarm in any one of the claims 1-2.
4. A server, characterized by: comprising at least one processor, and a memory communicatively coupled to the processor, the memory storing instructions executable by the at least one processor, the instructions being executable by the processor to cause the at least one processor to perform a method of intelligent belt conveyor diagnosis based on characteristic value alarms according to any of claims 1-2.
5. A computer-readable storage medium storing a computer program, characterized in that: the computer program is used for realizing the belt conveyor intelligent diagnosis method based on the characteristic value alarm in any one of claims 1-2 when being executed by a processor.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| JP2020199017A (en) * | 2019-06-07 | 2020-12-17 | 株式会社ユニバーサルエンターテインメント | Game machine |
| CN113834657A (en) * | 2021-09-24 | 2021-12-24 | 北京航空航天大学 | Bearing fault early warning and diagnosis method based on improved MSET and frequency spectrum characteristics |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2020199017A (en) * | 2019-06-07 | 2020-12-17 | 株式会社ユニバーサルエンターテインメント | Game machine |
| 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 |
| CN113834657A (en) * | 2021-09-24 | 2021-12-24 | 北京航空航天大学 | Bearing fault early warning and diagnosis method based on improved MSET and frequency spectrum characteristics |
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| Title |
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| 基于证据理论的高压防爆电机转子故障在线诊断方法研究;张建文等;《华北电力大学学报(自然科学版)》;20080330(第02期);37-43 * |
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