CN114563189B - Unmanned aerial vehicle engine fault diagnosis method based on instantaneous rotation speed - Google Patents
Unmanned aerial vehicle engine fault diagnosis method based on instantaneous rotation speed Download PDFInfo
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Abstract
The invention relates to an unmanned aerial vehicle engine fault diagnosis method based on instantaneous rotation speed, which comprises the following steps: acquiring a rotating speed signal of an output shaft of an engine; noise reduction is carried out on the rotating speed signal to obtain a purified high signal-to-noise ratio rotating speed signal; calculating to obtain the instantaneous rotation speed of the output shaft of the engine according to the purified rotation speed signal; calculating the instantaneous rotational speed fluctuation rate of the output shaft in a working period according to the instantaneous rotational speed; calculating the instantaneous rotational speed average fluctuation rate of each cylinder according to the instantaneous rotational speed fluctuation rate; according to the method, the instantaneous rotation speed signal measured by the flywheel end of the engine is used for processing to obtain the instantaneous rotation speed of the output shaft of the engine, and the method can be suitable for non-stationary and nonlinear signal analysis, so that the fault diagnosis of the engine is more accurate.
Description
Technical Field
The invention relates to the technical field of engines, in particular to an unmanned aerial vehicle engine fault diagnosis method based on instantaneous rotation speed.
Background
At present, the unmanned aerial vehicle engine at home and abroad mainly uses a piston type, and the piston type engine has smaller size and lighter weight for a small unmanned aerial vehicle and is economical for a large unmanned aerial vehicle, so the piston type oil injection engine is the most old but the most popular engine at present. However, the piston engine also has the defects of lower thrust weight ratio, higher fault rate, poorer running performance in high air, obvious vibration and noise and the like, and the engine is the part which is most prone to generate faults in the parts of the unmanned aerial vehicle, once the faults are generated, the unmanned aerial vehicle has extremely high crash risk in the air, so that the fault diagnosis of the unmanned aerial vehicle engine is very necessary.
The unmanned aerial vehicle has a compact internal structure, proper sensors and advanced technology are required to be arranged for acquiring more accurate diagnosis information, signals used for general diagnosis are vibration signals acquired by a vibration displacement sensor or a vibration acceleration sensor, main diagnosis modes are a frequency spectrum diagnosis method, a resonance demodulation method, a refined frequency spectrum analysis technology, a cepstrum analysis technology, a wavelet analysis method and the like, but the methods cannot be applied to non-stationary nonlinear signals, when the number of engine cylinders is large, instantaneous rotation speed fluctuation is complex, accurate engine fault diagnosis information cannot be acquired by using the method, and therefore the problem is solved by using the unmanned aerial vehicle engine fault diagnosis method based on the instantaneous rotation speed.
Disclosure of Invention
The invention aims to solve the problem that the traditional engine fault diagnosis method is not suitable for non-stable and nonlinear signals, and provides an unmanned aerial vehicle engine fault diagnosis method based on instantaneous rotation speed.
The invention provides an unmanned aerial vehicle engine fault diagnosis method based on instantaneous rotation speed, which comprises the following steps:
acquiring a rotating speed signal of an output shaft of an engine;
noise reduction is carried out on the rotating speed signal to obtain a purified high signal-to-noise ratio rotating speed signal;
calculating to obtain the instantaneous rotation speed of the output shaft of the engine according to the purified rotation speed signal;
calculating the instantaneous rotational speed fluctuation rate of the output shaft in a working period according to the instantaneous rotational speed;
calculating the instantaneous rotational speed average fluctuation rate of each cylinder according to the instantaneous rotational speed fluctuation rate;
and calculating membership values of the engine in different states according to the average fluctuation rate of the instantaneous rotation speed of the engine in different states, and judging whether the engine cylinder fails according to the membership values.
Preferably, the method for acquiring the rotation speed signal of the engine output shaft comprises the following steps:
acquiring a rotating speed signal of an engine output shaft and a calibrated top dead center signal according to a magneto-electric sensor at a flywheel end when the engine works;
preferably, the method for obtaining the high signal-to-noise ratio purified rotating speed signal by noise reduction of the rotating speed signal comprises the following steps:
the self-adaptive decomposition method is adopted to carry out noise reduction treatment, the lumped intrinsic characteristic scale decomposition method is provided on the basis of the intrinsic characteristic scale decomposition method, and the method is utilized to carry out noise reduction treatment on the rotating speed signal, and the specific steps are as follows:
(1) uniformly distributed white noise sequences: n is n 1 (t),n 2 (t),...,n m (t) adding the new sequence into an original rotating speed signal acquired by a sensor to form a new original rotating speed signal sequence: x (t) +n 1 (t),x(t)+n 2 (t),...,x(t)+n m (t)；
(2) And carrying out intrinsic feature scale decomposition treatment on each element in the new original rotating speed signal sequence:
x(t)+n 1 (t) carrying out intrinsic feature scale decomposition treatment to obtain c 11 (t),c 12 (t),...,c 1h (t)；
x(t)+n 2 (t) carrying out intrinsic feature scale decomposition treatment to obtain c 21 (t),c 22 (t),...,c 2h (t)
…
x(t)+n m (t) carrying out intrinsic feature scale decomposition treatment to obtain c m1 (t),c m2 (t),...,c mh (t)；
(3) And carrying out collective average processing on each corresponding component to obtain:
i.e. c 1 (t),c 2 (t),...,c h (t) the component rotating speed signal after the decomposition processing by using the lumped intrinsic characteristic scale, m is the number of white noise in the added white noise sequence, and the value of m is selected to be 50 and 100;
and (3) decomposing each component rotating speed signal after the lumped intrinsic characteristic scale decomposition, and selecting the component rotating speed signal containing main information to reconstruct based on the correlation maximum principle so as to obtain the rotating speed signal with high signal-to-noise ratio.
Preferably, the method for calculating the instantaneous rotation speed of the output shaft of the engine according to the purified rotation speed signal comprises the following steps:
calculating the instantaneous rotational speed of the engine output shaft across each tooth of the flywheel according to the following formula (1):
wherein speed represents the instantaneous rotational speed (r/min), f s The number of teeth of the Z flywheel is the sampling frequency (HZ) of the magneto-electric sensor, and K is the number of sampling points among one sine wave in the purified rotating speed signal with high signal-to-noise ratio.
Preferably, the method for calculating the instantaneous rotational speed fluctuation rate of the output shaft in one working period according to the instantaneous rotational speed comprises the following steps:
dividing the working period of the engine according to the top dead center signals acquired by calibrating the top dead center, and calculating the instantaneous rotation speed fluctuation rate epsilon in one working period according to the following formula (2):
in the method, in the process of the invention,average rotational speed (r/min).
Preferably, the method for calculating the instantaneous rotational speed average fluctuation rate of each cylinder according to the instantaneous rotational speed fluctuation rate comprises the following steps:
calculating the instantaneous rotation speed average fluctuation rate eta of each cylinder in the alpha zone according to the following formula (3) i ：
Wherein i is the ith cylinder after sequencing the cylinders according to the firing sequence of the cylinders of the multi-cylinder engine, and J is the number of all instantaneous rotation speed signals of each cylinder in the instantaneous rotation speed interval with the length alpha. Wherein alpha represents the minimum phase angle between two adjacent cylinders, ε j The j-th instantaneous rotational speed fluctuation rate of each cylinder in the instantaneous rotational speed interval with the length alpha is provided.
Preferably, the method for judging whether each cylinder of the engine fails according to the instantaneous rotation speed average fluctuation rate comprises the following steps:
according to 3 sigma principle in mathematical statistics theory, establishing membership function of engine in different states, comprising the following specific steps:
(1) establishing a membership function in a normal state according to the mean value and the variance of the instantaneous rotational speed average fluctuation rate of each cylinder in the normal state of the engine as a standard value and a standard deviation, and selecting and using the Z-shaped membership function;
(2) according to the mean value and variance of the instantaneous rotational speed average fluctuation rate of each cylinder of the engine in the oil leakage state as the standard value and standard deviation, establishing a membership function in the oil leakage state, and selecting and using a pi-shaped membership function;
(3) establishing a membership function in a flameout state according to the mean value and the variance of the instantaneous rotating speed average fluctuation rate of each cylinder in the flameout state of the engine as a standard value and a standard deviation, and selecting and using an S-shaped membership function;
(4) and selecting a state corresponding to the maximum value of the membership value as the working state of the air cylinder at the moment according to the corresponding membership value calculated by the instantaneous rotating speed average fluctuation rate of each air cylinder and the membership function of the engine in different states.
Compared with the prior art, the unmanned aerial vehicle engine fault diagnosis method based on the instantaneous rotating speed has the beneficial effects that:
1. according to the invention, the rotating speed signal of the engine output shaft is obtained through the magneto-electric sensor, and the rotating speed signal is processed by using the method of lumped intrinsic characteristic scale decomposition to obtain the purified high signal-to-noise ratio rotating speed signal.
2. According to the invention, the instantaneous rotating speed interval corresponding to each cylinder is divided by utilizing the minimum phase angle alpha of the adjacent cylinders, the instantaneous rotating speed fluctuation rate in the instantaneous rotating speed interval of each cylinder is calculated, and the instantaneous rotating speed average fluctuation rate is further obtained.
3. According to the invention, the membership function of the air cylinders belonging to different states is established by using the characteristic parameter of the instantaneous rotating speed average fluctuation rate, and the working state of each air cylinder of the engine can be judged according to the membership belonging to different states.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The following describes the embodiment of the present invention in detail with reference to fig. 1, but it should be understood that the scope of the present invention is not limited by the embodiment.
As shown in fig. 1, the unmanned aerial vehicle engine fault diagnosis method based on the instantaneous rotation speed provided by the invention comprises the following steps:
s1, acquiring a rotating speed signal of an engine flywheel end, wherein the method comprises the following steps:
the magneto-electric sensor is arranged at the flywheel end of the engine, and two non-contact magneto-electric sensors are respectively utilized to collect the rotating speed signal and the calibrated top dead center signal of the flywheel end.
S2, noise reduction is carried out on the rotating speed signal to obtain a purified high signal-to-noise ratio rotating speed signal, and the method comprises the following steps:
the self-adaptive decomposition method is adopted to carry out noise reduction treatment, the lumped intrinsic characteristic scale decomposition method is provided on the basis of the intrinsic characteristic scale decomposition method, and the method is utilized to carry out noise reduction treatment on the rotating speed signal, and the specific steps are as follows:
s2-1, uniformly distributing white noise sequences: n is n 1 (t),n 2 (t),...,n m (t) adding the new sequence into an original rotating speed signal acquired by a sensor to form a new original rotating speed signal sequence: x (t) +n 1 (t),x(t)+n 2 (t),...,x(t)+n m (t)；
S2-2, carrying out intrinsic feature scale decomposition treatment on each element in the new original rotating speed signal sequence:
x(t)+n 1 (t) carrying out intrinsic feature scale decomposition treatment to obtain c 11 (t),c 12 (t),...,c 1h (t)；
x(t)+n 2 (t) carrying out intrinsic feature scale decomposition treatment to obtain c 21 (t),c 22 (t),...,c 2h (t)
…
x(t)+n m (t) carrying out intrinsic feature scale decomposition treatment to obtain c m1 (t),c m2 (t),...,c mh (t)；
S2-3, performing collective average processing on the obtained corresponding components to obtain:
i.e. c 1 (t),c 2 (t),...,c h (t) is the component rotation speed signal after decomposition processing using lumped intrinsic feature scaleThe number m is the number of white noise in the added white noise sequence, and the value of m is generally selected to be 50 and 100;
and (3) decomposing each component rotating speed signal after the lumped intrinsic characteristic scale decomposition, and selecting the component rotating speed signal containing main information to reconstruct based on the correlation maximum principle so as to obtain the rotating speed signal with high signal-to-noise ratio.
S3, calculating the instantaneous rotation speed of the output shaft of the engine according to the purified rotation speed signal, wherein the method comprises the following steps of:
calculating the instantaneous rotational speed of the engine output shaft across each tooth of the flywheel according to the following formula (1):
wherein speed represents the instantaneous rotational speed (r/min), f s The number of teeth of the Z flywheel is the sampling frequency (HZ) of the magneto-electric sensor, and K is the number of sampling points among one sine wave in the purified rotating speed signal with high signal-to-noise ratio.
S4, calculating the instantaneous rotation speed fluctuation rate of the output shaft in a working period according to the instantaneous rotation speed, wherein the method comprises the following steps:
calculating the instantaneous rotational speed fluctuation rate epsilon in one working period according to the following formula (2):
in the method, in the process of the invention,average rotational speed (r/min).
S5, calculating the instantaneous rotational speed average fluctuation rate of each cylinder according to the instantaneous rotational speed fluctuation rate, wherein the method comprises the following steps:
calculating the instantaneous rotation speed average fluctuation rate eta of each cylinder in the alpha zone according to the following formula (3) i ：
Wherein i is the ith cylinder after sequencing the cylinders according to the firing sequence of the cylinders of the multi-cylinder engine, J is the number of all instantaneous rotation speed signals of each cylinder in an instantaneous rotation speed interval with the length of alpha, wherein alpha represents the angle of minimum phase angle between two adjacent cylinders, epsilon j The j-th instantaneous rotational speed fluctuation rate of each cylinder in the instantaneous rotational speed interval with the length alpha is provided.
S5, judging whether each cylinder of the engine fails according to the instantaneous rotating speed average fluctuation rate, wherein the method comprises the following steps:
according to the 3 sigma principle in the mathematical statistics theory, if the difference between the instantaneous rotating speed average fluctuation rate test value and the standard value is within one standard deviation, the test value belongs to a normal state, between one standard deviation and two standard deviations, the test value belongs to an oil leakage state, and the test value is in a flameout state outside the two standard deviations, so that membership functions of all states are established, and the specific steps are as follows:
s5-1, establishing a membership function in a normal state according to the mean value and the variance of the instantaneous rotational speed average fluctuation rate of each cylinder in the normal state as a standard value and a standard deviation, and selecting a Z-shaped membership function, wherein the Z-shaped membership function is in the following form:
wherein the values of a and b are determined by the standard value and the standard deviation, the standard value is mu, the standard deviation is sigma, and the values of a and b can be selected as a=mu+sigma and b=mu+3sigma in the normal state.
S5-2, establishing a membership function in the oil leakage state according to the mean value and the variance of the instantaneous rotational speed average fluctuation rate of each cylinder in the oil leakage state as a standard value and a standard deviation, and selecting and using a pi-shaped membership function, wherein the pi-shaped membership function is in the following form:
the value of a, b, c, d is determined by the standard value and standard deviation, the standard value is μ, the standard deviation is σ, and the value of a, b, c, d in oil leakage state can be selected to be a=μ+σ, b=μ+3σ, c=μ+3σ, d=μ+5σ.
S5-3, establishing a membership function in the flameout state according to the mean value and the variance of the instantaneous rotating speed average fluctuation rate of each cylinder in the flameout state as a standard value and a standard deviation, and selecting and using an S-shaped membership function, wherein the S-shaped membership function is in the following form:
wherein the values of a and b are determined by the standard value and standard deviation, the standard value is mu, the standard deviation is sigma, and the values of a and b in the flameout state can be selected as a=mu+3sigma, and b=mu+5sigma.
S5-4, substituting the instantaneous rotating speed average fluctuation rate in the current state into the Z-shaped membership function, the pi-shaped membership function and the S-shaped membership function respectively, correspondingly obtaining membership values of the engine in different states, and selecting the state corresponding to the maximum value of the membership values as the working state of the air cylinder.
In summary, the invention obtains the rotation speed signal and the top dead center signal of the engine output shaft through the magneto-electric sensor, and proposes to process the rotation speed signal measured by the flywheel end of the engine by using the lumped intrinsic feature scale decomposition method to obtain the accurate instantaneous rotation speed of the engine. The accuracy of engine fault diagnosis is improved.
The foregoing disclosure is merely illustrative of preferred embodiments of the present invention, but the embodiments of the present invention are not limited thereto, and any variations within the scope of the present invention will be apparent to those skilled in the art.
Claims (3)
1. The unmanned aerial vehicle engine fault diagnosis method based on the instantaneous rotating speed is characterized by comprising the following steps of:
acquiring a rotating speed signal of an output shaft of an engine;
noise reduction is carried out on the rotating speed signal to obtain a purified high signal-to-noise ratio rotating speed signal;
calculating to obtain the instantaneous rotation speed of the output shaft of the engine according to the purified rotation speed signal;
calculating the instantaneous rotational speed fluctuation rate of the output shaft in a working period according to the instantaneous rotational speed;
calculating the instantaneous rotational speed average fluctuation rate of each cylinder according to the instantaneous rotational speed fluctuation rate;
calculating membership values of the engine in different states according to the average fluctuation rate of the instantaneous rotation speed of the engine in different states, and judging whether the engine cylinder fails according to the membership values;
the method for obtaining the purified high signal-to-noise ratio rotating speed signal by reducing the noise of the rotating speed signal comprises the following steps:
the rotational speed signal is subjected to noise reduction treatment by utilizing a lumped intrinsic feature scale decomposition method, and the method comprises the following specific steps:
(1) uniformly distributed white noise sequences: n is n 1 (t),n 2 (t),...,n m (t) adding the new sequence into an original rotating speed signal acquired by a sensor to form a new original rotating speed signal sequence:
x(t)+n 1 (t),x(t)+n 2 (t),...,x(t)+n m (t)；
(2) and carrying out intrinsic feature scale decomposition treatment on each element in the new original rotating speed signal sequence:
x(t)+n 1 (t) carrying out intrinsic feature scale decomposition treatment to obtain c 11 (t),c 12 (t),...,c 1h (t)；
x(t)+n 2 (t) carrying out intrinsic feature scale decomposition treatment to obtain c 21 (t),c 22 (t),...,c 2h (t)
…
x(t)+n m (t) carrying out intrinsic feature scale decomposition treatment to obtain c m1 (t),c m2 (t),...,c mh (t)；
(3) And carrying out collective average processing on each corresponding component to obtain:
i.e. c 1 (t),c 2 (t),...,c h (t) the component rotating speed signal after the decomposition processing by using the lumped intrinsic characteristic scale, m is the number of white noise in the added white noise sequence, and the value of m is selected to be 50 and 100;
each component rotating speed signal after the decomposition of the lumped intrinsic characteristic scale is selected to reconstruct based on the principle of maximum correlation, so as to obtain a rotating speed signal with high signal-to-noise ratio;
the method for calculating the instantaneous rotating speed of the output shaft of the engine according to the purified rotating speed signal comprises the following steps:
calculating the instantaneous rotational speed of the engine output shaft across each tooth of the flywheel according to the following formula (1):
wherein speed is the instantaneous rotation speed (r/min), f s The number of teeth of the Z flywheel is the sampling frequency (HZ) of the magneto-electric sensor, and K is the number of sampling points among one sine wave in the purified rotating speed signal with high signal-to-noise ratio;
the method for calculating the instantaneous rotational speed fluctuation rate of the output shaft in one working period according to the instantaneous rotational speed comprises the following steps:
dividing the working period of the engine according to the top dead center signals acquired by calibrating the top dead center, and calculating the instantaneous rotation speed fluctuation rate epsilon in one working period according to the following formula (2):
wherein speed is the instantaneous rotational speed (r/min),average rotation speed (r/min);
the method for calculating the instantaneous rotational speed average fluctuation rate of each cylinder according to the instantaneous rotational speed fluctuation rate comprises the following steps:
calculating the instantaneous rotation speed average fluctuation rate eta of each cylinder in the alpha zone according to the following formula (3) i ：
Wherein i is the ith cylinder after sequencing the cylinders according to the firing sequence of the cylinders of the multi-cylinder engine, J is the number of all instantaneous rotation speed signals of each cylinder in an instantaneous rotation speed interval with the length of alpha, and alpha is the phase angle with the minimum distance between two adjacent cylinders, epsilon j The j-th instantaneous rotational speed fluctuation rate of each cylinder in the instantaneous rotational speed interval with the length alpha is provided.
2. The unmanned aerial vehicle engine fault diagnosis method based on the instantaneous rotation speed according to claim 1, wherein the method for acquiring the rotation speed signal of the engine output shaft is as follows:
and acquiring a rotating speed signal of an engine output shaft and a calibrated top dead center signal according to a magneto-electric sensor at a flywheel end when the engine works.
3. The unmanned aerial vehicle engine fault diagnosis method based on the instantaneous rotation speed of claim 1, wherein the method for calculating the membership value of the engine in different states according to the instantaneous rotation speed average fluctuation rate of the engine in different states and judging whether the engine cylinder is faulty according to the membership value is as follows:
according to 3 sigma principle in mathematical statistics theory, establishing membership function of engine in different states, comprising the following specific steps:
(1) establishing a membership function in a normal state according to the mean value and the variance of the instantaneous rotational speed average fluctuation rate of each cylinder in the normal state of the engine as a standard value and a standard deviation, and selecting and using the Z-shaped membership function;
(2) according to the mean value and variance of the instantaneous rotational speed average fluctuation rate of each cylinder of the engine in the oil leakage state as the standard value and standard deviation, establishing a membership function in the oil leakage state, and selecting and using a pi-shaped membership function;
(3) establishing a membership function in a flameout state according to the mean value and the variance of the instantaneous rotating speed average fluctuation rate of each cylinder in the flameout state of the engine as a standard value and a standard deviation, and selecting and using an S-shaped membership function;
(4) and selecting a state corresponding to the maximum value of the membership value as the working state of the air cylinder at the moment according to the corresponding membership value calculated by the instantaneous rotating speed average fluctuation rate of each air cylinder and the membership function of the engine in different states.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102788696A (en) * | 2012-07-21 | 2012-11-21 | 辽宁大学 | Evaluation method for health degree of bearing on basis of improved BP (Back Propagation) neural network and fuzzy set theory |
| CN103900824A (en) * | 2014-03-27 | 2014-07-02 | 哈尔滨工程大学 | Method for diagnosing faults of diesel engine based on instant rotary speed clustering analysis |
| CN104568445A (en) * | 2013-10-18 | 2015-04-29 | 镇江中研电控有限公司 | Engine load detection device and engine load detection method |
| CN104598926A (en) * | 2015-01-29 | 2015-05-06 | 西北工业大学 | Aircraft engine transient state fault detecting method |
| JP2016090374A (en) * | 2014-11-04 | 2016-05-23 | ヤンマー株式会社 | Rotating speed detection device |
| CN105784377A (en) * | 2016-03-28 | 2016-07-20 | 中国船舶工业系统工程研究院 | Working balance fault diagnosis method and device for diesel engine based on instantaneous rotating speed |
| CN205404125U (en) * | 2016-03-18 | 2016-07-27 | 长安大学 | A failure diagnosis device that catches fire for engine rig test |
| CN111413095A (en) * | 2020-04-13 | 2020-07-14 | 西安电子科技大学 | Instantaneous angular velocity-based distributed fault diagnosis and analysis method for planetary bearing |
| CN112067306A (en) * | 2020-08-13 | 2020-12-11 | 武汉理工大学 | Method, equipment and system for online monitoring and evaluating health state of marine engine |
| CN112964893A (en) * | 2021-03-09 | 2021-06-15 | 一汽解放汽车有限公司 | Engine instantaneous rotating speed measuring device, fluctuation rate measuring system and method |
| WO2021139331A1 (en) * | 2020-01-08 | 2021-07-15 | 重庆交通大学 | Bearing fault diagnosis method based on instantaneous frequency optimization vmd |
-
2022
- 2022-02-28 CN CN202210189173.7A patent/CN114563189B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102788696A (en) * | 2012-07-21 | 2012-11-21 | 辽宁大学 | Evaluation method for health degree of bearing on basis of improved BP (Back Propagation) neural network and fuzzy set theory |
| CN104568445A (en) * | 2013-10-18 | 2015-04-29 | 镇江中研电控有限公司 | Engine load detection device and engine load detection method |
| CN103900824A (en) * | 2014-03-27 | 2014-07-02 | 哈尔滨工程大学 | Method for diagnosing faults of diesel engine based on instant rotary speed clustering analysis |
| JP2016090374A (en) * | 2014-11-04 | 2016-05-23 | ヤンマー株式会社 | Rotating speed detection device |
| CN104598926A (en) * | 2015-01-29 | 2015-05-06 | 西北工业大学 | Aircraft engine transient state fault detecting method |
| CN205404125U (en) * | 2016-03-18 | 2016-07-27 | 长安大学 | A failure diagnosis device that catches fire for engine rig test |
| CN105784377A (en) * | 2016-03-28 | 2016-07-20 | 中国船舶工业系统工程研究院 | Working balance fault diagnosis method and device for diesel engine based on instantaneous rotating speed |
| WO2021139331A1 (en) * | 2020-01-08 | 2021-07-15 | 重庆交通大学 | Bearing fault diagnosis method based on instantaneous frequency optimization vmd |
| CN111413095A (en) * | 2020-04-13 | 2020-07-14 | 西安电子科技大学 | Instantaneous angular velocity-based distributed fault diagnosis and analysis method for planetary bearing |
| CN112067306A (en) * | 2020-08-13 | 2020-12-11 | 武汉理工大学 | Method, equipment and system for online monitoring and evaluating health state of marine engine |
| CN112964893A (en) * | 2021-03-09 | 2021-06-15 | 一汽解放汽车有限公司 | Engine instantaneous rotating speed measuring device, fluctuation rate measuring system and method |
Non-Patent Citations (1)
| Title |
|---|
| 发动机失火故障的马氏距离研究;杜金博 等;《农业装备与车辆工程》;第56卷(第3期);全文 * |
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