CN111256928A - Method for detecting faults of vibrating screen of combine harvester - Google Patents
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Abstract
A method for detecting faults of a vibrating screen of a combine harvester comprises a vibration signal acquisition device and a vibration signal processing device, wherein the vibration signal acquisition device is arranged at a screen frame of the vibrating screen and comprises at least one vibration signal sensor; the vibration signal processing device comprises a wireless transmission device; a data analysis device; and the fault display device comprises a liquid crystal display and an alarm indicator light. The fault of the vibrating screen can be timely and accurately reported under the complex condition.
Description
Technical Field
The invention relates to the field of combine harvesters, in particular to a method for detecting faults of a vibrating screen of a combine harvester.
Background
The combine harvester is a large-scale complex agricultural machine, and plays an extremely important role in agricultural production in China. The cleaning efficiency of the cleaning device is of great importance to the combine harvester, and the cleaning efficiency of the combine harvester is determined by the working efficiency of the vibrating screen in the cleaning device. When the combine harvester works normally, the vibrating screen mechanism can also generate larger inertia force. This will excite the frame or other parts, causing strong vibration and noise, affecting the working accuracy, reliability, life and cleaning efficiency of the harvester. Therefore, the study on fault diagnosis of the combine harvester vibrating screen becomes important.
The vibration sensor is a main method for acquiring the fault characteristics of the vibrating screen of the combine harvester. Many methods are available for processing vibration signals, such as fast fourier transform, wavelet analysis, etc. Because the vibrating screen of the combine harvester is influenced by uncertain factors in the working process, the generated signals often have the characteristics of weakness, aliasing, nonlinearity and the like in the analysis process, so that the traditional methods cannot obtain satisfactory characteristic parameters for representing faults, and no good fault detection method is available for quickly and accurately diagnosing the vibrating screen of the combine harvester under the condition of uncertain information contained in a large amount of noise.
Disclosure of Invention
In order to solve the technical problem, the invention provides a method for detecting the fault of the vibrating screen of the combine harvester, which can timely and accurately alarm the fault of the vibrating screen under a complex condition.
In order to realize the technical purpose, the adopted technical scheme is as follows: a method for detecting faults of a vibrating screen of a combine harvester is characterized in that detection is carried out through a detection system, wherein the detection system comprises a vibration signal acquisition device, a vibration signal processing module and a fault display device;
the vibration signal acquisition device comprises a vibration sensor module, a controller and a wireless transmitter, wherein the vibration sensor module is arranged at a screen frame of the vibrating screen, is connected with a signal input port of the controller and is used for acquiring vibration signals, and a wireless signal transmitting end of the controller is connected with the wireless transmitter to transmit the vibration signals;
the vibration signal processing module comprises a wireless transmission device and a processor, the wireless transmission device is used for receiving vibration signals sent by the wireless transmitter, the wireless transmission device is connected with the processor, the processor is connected with the data storage, and the data storage stores the vibration signals;
the fault display device comprises a display module and an alarm indicator lamp;
the wireless transmission device acquires vibration signals acquired by a vibration sensor on a combine harvester vibrating screen under a normal working condition, the acquired signals are sent to a processor, a data storage device stores the vibration signals acquired under the normal working condition and sets a rated range under the normal working condition, the vibrating screen continues to work under the actual working condition, the wireless transmission device transmits the vibration signals received from the vibration sensor to the processor to carry out signal decomposition on the initial vibration signals, the initial vibration signals are compared with the vibration signals acquired under the normal working condition, if the initial vibration signals are within the rated range, the vibrating screen is considered to work normally, and if the initial vibration signals are not within the rated range, an alarm indicator lamp gives an alarm and the alarm indicator lamp keeps in the data storage device.
Further, the vibration sensor module is arranged at the bottom of the screen frame of the vibrating screen.
Furthermore, the vibration signal acquisition device also comprises an acceleration sensor which is arranged at a rocker of the vibrating screen and used for detecting whether the vibrating screen runs abnormally in the running process
Further, the signal decomposition process of the initial vibration signal by the processor comprises the following steps:
step (1), all extreme points of the signal x (t) are found and are marked as (delta)k,μk) K is 1,2,3 …, K; wherein deltakIs time, μkIs amplitude, K is the number of the collected signals;
and (2) carrying out weighted average on every three adjacent points, and defining the weighted average as:
wherein P is a right;
step (3) of averaging all points (delta) after weightingk,mk) And (delta)k,Ak) K is 1,2,3 …, K; dividing into two parts, respectively interpolating all points with cubic spline curve to obtain two groups of mean value curves m1(t)、m2(t) and two sets of envelope curves A1(t)、A2(t), and averaging them to obtain a mean curve m (t) and an envelope curve A (t):
step (4), if m (t) satisfies the condition of eigenmode component, then m (t) is imf1;
Step (5) removing imf from the signal x (t)1Obtain a signal x1(t) converting x1(t) as new signal to be analyzed and repeating steps (1) - (4) until xn(t) is a monotonic function;
through the steps, a series of linear superposition of the intrinsic mode components and the residual part can be obtained, and each component in the intrinsic mode components represents each frequency component in the original signal.
Further, the eigenmode component criterion in step (3) adopts a three-threshold method, which specifically comprises the following steps: definition ofWherein the three threshold value method is the middle threshold value (theta)1,θ2β) in the sense of ensuring that there is a large variation in theta for a local short time, and a small variation in the rest of the time, say theta < theta during the β time period2Theta < theta for the remaining time (1- β)1Wherein 0.01 is not more than theta1≤0.1,θ2=10*θ1,β=0.05。
Further, the value of theta obtained in the actual working condition is analyzed,recording the theta value obtained under the normal working condition as thetaxAnd the value of theta obtained by analysis under the actual working condition is recorded as thetamWhen theta ismAt a thetaxAnd b θxIn time between, i.e. a θx≤θm≤bθxWhen a is more than or equal to 1.2 and less than or equal to 1.8; b is more than or equal to 2.0 and less than or equal to 2.4; considering the normal operation of the vibrating screen, if the theta obtained by analysis is normalmIf the vibration signal is not in the interval range, fault alarming is carried out, the fault vibration signal is stored in the data storage, and when the vibration screen sensor collects the fault vibration signal next time, fault alarming is directly carried out.
The invention has the beneficial effects that: the invention adopts an optimized empirical mode decomposition method, and can carry out high-efficiency and real-time analysis on the vibration signal generated by the combine harvester vibrating screen during working. By the method, effective fault feature extraction can be carried out on existing weak information, and after intrinsic mode function components of different time scales are obtained, cyclic empirical mode decomposition is carried out, so that the weak fault information submerged in noise is effectively extracted. And whether the state is a fault state is judged by signal comparison, and a fault signal is stored in the data memory, so that the comparison can be carried out more quickly and conveniently next time, and the time and the accuracy required by fault diagnosis are further improved.
Drawings
FIG. 1 is a block diagram of the system architecture of the present invention;
FIG. 2 is a diagrammatic view of a combine vibratory screen mechanism;
FIG. 3 is a flow chart of vibration signal data analysis of the present invention;
fig. 4 is a flow chart of the fault discrimination of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
Referring to fig. 1, a method for diagnosing and detecting a fault of a combine harvester includes a vibration signal acquisition device S1, a vibration signal processing module S2, a vibration signal processing module S3 and a fault display device S4; the vibration signal acquisition device S1 comprises a vibration sensor module S5, a controller S6 and a wireless transmitter S7, the vibration signal acquisition device S1 is arranged at a screen frame CD of the vibrating screen and is connected with a signal input port of the controller S6 and used for acquiring vibration signals, a wireless signal sending end of the controller S6 is connected with the wireless transmitter S7, and a wireless signal sending end of the controller S6 is connected with the wireless transmitter S7 for sending vibration signals; the vibration signal processing module S3 includes a wireless transmission device S8 for receiving the vibration signal from the wireless transmitter S7, and a processor S9 connected to the wireless transmission device S8 and the processor S9, wherein the processor S9 is connected to a data storage S10, and the data storage S10 stores the vibration signal. The fault display device S4 includes a display module S11 and an alarm indicator lamp S12.
Referring to fig. 2, the combine harvester vibrating and screening mechanism is shown, wherein AB is a rocker arm which rotates at an angular velocity when operating and drives a connecting rod BC to move. The connecting rod BC drives the screen frame CD to do reciprocating motion, and the materials are screened and cleaned. Wherein vibration sensor installs in reel CD department for gather vibration signal, sets up the vibration signal of easily gathering the shale shaker in this department, and can not disturbed by too much external factor. And an acceleration sensor is arranged at the position AB so as to detect whether the vibrating screen runs abnormally or not in the running process.
The wireless transmission device S8 obtains vibration signals collected by a vibration sensor on a combine harvester vibrating screen under normal working conditions, the obtained signals are sent to a processor S9, a data storage S10 stores the vibration signals obtained under the normal working conditions and sets a rated range under the normal working conditions, the vibrating screen continues to work under the actual working conditions, the vibration signals received from the vibration sensor are transmitted to the processor S9 through the wireless transmission device S8 to carry out signal decomposition on the initial vibration signals, the initial vibration signals are compared with the vibration signals obtained under the normal working conditions, if the initial vibration signals are within the rated range, the vibrating screen is considered to work normally, if the initial vibration signals are not within the rated range, an alarm indicator lamp S12 gives an alarm, and the alarm indicator lamp is kept in the data storage S10.
Referring to fig. 3, a vibration signal of the combine harvester vibrating screen under normal working conditions transmitted by the vibration sensor is received by the wireless transmission device S8 and is transmitted to the processor S9 for processing, and since the obtained vibration signal includes a noise signal and a vibration signal generated by vibrating of the vibrating screen, an optimized empirical mode decomposition algorithm is performed by the processor, and the process includes:
(1) find all the extreme points of the signal x (t), denoted as (delta)k,μk) K is 1,2,3 …, K; wherein deltakIs time, μkIs the amplitude, and K is the number of acquired signals.
(2) Each adjacent three points are weighted averaged and defined as:
wherein P is a right;
in order to inhibit the end point effect, an end point continuation method is adopted to obtain end points of two ends;
(3) weighted average of all points (delta)k,mk) And (delta)k,Ak) K is 1,2,3 …, K; dividing into two parts, respectively interpolating all points with cubic spline curve to obtain two groups of mean value curves m1(t)、m2(t) and two sets of envelope curves A1(t)、A2(t) and averaging them to obtain a mean curve and an envelope curve:
(4) if m (t) satisfies the condition of Intrinsic Mode Function (IMF), then m (t) is IMF1;
(5) Removal imf from signal x (t)1Obtain a signal x1(t) converting x1(t) as new signal to be analyzed and repeating steps (1) - (4) until xn(t) is a monotonic function.
Through the steps, a series of IMFs and linear superposition of the remaining part can be obtained, and each component in the IMFs represents each frequency component in the original signal. When the combine harvester works, the signals transmitted by the vibration sensor are compared with the standard signals one by one, and an alarm is given when the error exceeds a rated range.
The IMF criterion adopts a three-threshold method, which specifically comprises the following steps: definition ofWherein the three threshold value method is the middle threshold value (theta)1,θ2β) in the sense of ensuring that there is a large variation in theta for a local short time, and a small variation in the rest of the time, say theta < theta during the β time period2Theta < theta for the remaining time (1- β)1Wherein 0.01 is not more than theta1Less than or equal to 0.1, in general theta1=0.05,θ2=10*θ1,β=0.05。
Referring to fig. 4, the fault diagnosis method includes: analyzing the theta value obtained in the actual working condition,recording the theta value obtained under the normal working condition as thetaxAnd the value of theta obtained by analysis under the actual working condition is recorded as thetamWhen theta ismAt a thetaxAnd b θxIn time between, i.e. a θx≤θm≤bθxWhen the vibrating screen works normally, a is more than or equal to 1.2 and less than or equal to 1.8; b is more than or equal to 2.0 and less than or equal to 2.4; if analyzed, is obtainedθmIf the vibration signal is not in the interval range, a fault alarm is carried out, the vibration signal is stored in the data storage, and the fault alarm is directly carried out when the vibration signal is collected by the vibrating screen sensor next time.
Although the present invention has been described with reference to a preferred embodiment, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A method for detecting the fault of a vibrating screen of a combine harvester is characterized by comprising the following steps: the method comprises the steps that detection is carried out through a detection system, and the detection system comprises a vibration signal acquisition device (S1), a vibration signal processing module (S2), a vibration signal processing module (S3) and a fault display device (S4);
the vibration signal acquisition device (S1) comprises a vibration sensor module (S5), a controller (S6) and a wireless transmitter (S7), wherein the vibration sensor module (S5) is arranged at a screen frame of the vibrating screen, is connected with a signal input port of the controller (S6) and is used for acquiring vibration signals, and a wireless signal sending end of the controller (S6) is connected with the wireless transmitter (S7) to send out vibration signals;
the vibration signal processing module (S3) comprises a wireless transmission device (S8) and a processor (S9), wherein the wireless transmission device is used for receiving a vibration signal sent by a wireless transmitter (S7), the wireless transmission device (S8) is connected with the processor (S9), the processor (S9) is connected with a data storage (S10), and the data storage (S10) stores the vibration signal;
the fault display device (S4) comprises a display module (S11) and an alarm indicator lamp (S12);
the wireless transmission device (S8) acquires vibration signals acquired by a vibration sensor on a combine harvester vibrating screen under normal working conditions, the acquired signals are sent to a processor (S9), a data storage device (S10) stores the vibration signals acquired under the normal working conditions and sets a rated range under the normal working conditions, the vibrating screen continues to work under the actual working conditions, the vibration signals received from the vibration sensor are transmitted to the processor (S9) through the wireless transmission device (S8) to decompose the initial vibration signals, the initial vibration signals are compared with the vibration signals acquired under the normal working conditions, if the initial vibration signals are within the rated range, the vibrating screen is considered to work normally, and if the initial vibration signals are not within the rated range, an alarm indicator lamp (S12) gives an alarm and the alarm is kept in the data storage device (S10).
2. A combine harvester shaker fault detection method as in claim 1, wherein: the vibration sensor module (S5) is arranged at the bottom of a screen frame of the vibrating screen.
3. A combine harvester shaker fault detection method as in claim 1, wherein: the vibration signal acquisition device (S1) further comprises an acceleration sensor, wherein the acceleration sensor is arranged at a rocker of the vibrating screen and used for detecting whether the vibrating screen runs abnormally in the running process.
4. A combine harvester shaker fault detection method as in claim 1, wherein: the signal decomposition process of the initial vibration signal by the processor (S9) includes:
step (1), all extreme points of the signal x (t) are found and are marked as (delta)k,μk) K is 1,2,3 …, K; wherein deltakIs time, μkIs amplitude, K is the number of the collected signals;
and (2) carrying out weighted average on every three adjacent points, and defining the weighted average as:
wherein P is a right;
step (3) of averaging all points (delta) after weightingk,mk) And (delta)k,Ak) K is 1,2,3 …, K; dividing into two parts, respectively interpolating all points with cubic spline curve to obtain two groups of mean value curves m1(t)、m2(t) and two sets of envelope curves A1(t)、A2(t), and averaging them to obtain a mean curve m (t) and an envelope curve A (t):
step (4), if m (t) satisfies the condition of eigenmode component, then m (t) is imf1;
Step (5) removing imf from the signal x (t)1Obtain a signal x1(t) converting x1(t) as new signal to be analyzed and repeating steps (1) - (4) until xn(t) is a monotonic function;
through the steps, a series of linear superposition of the intrinsic mode components and the residual part can be obtained, and each component in the intrinsic mode components represents each frequency component in the original signal.
5. A combine harvester shaker fault detection method as in claim 4, wherein: the eigenmode component criterion in the step (3) adopts a three-threshold method, which specifically comprises the following steps: definition ofWherein the three threshold value method is the middle threshold value (theta)1,θ2β) in the sense of ensuring that there is a large variation in theta for a local short time, and a small variation in the rest of the time, say theta < theta during the β time period2Theta < theta for the remaining time (1- β)1Wherein 0.01 is not more than theta1≤0.1,θ2=10*θ1,β=0.05。
6. A combine harvester shaker fault detection method as in claim 4, wherein: analyzing the theta value obtained in the actual working condition,recording the theta value obtained under the normal working condition as thetaxAnd the value of theta obtained by analysis under the actual working condition is recorded as thetamWhen theta ismAt a thetaxAnd b θxIn time between, i.e. a θx≤θm≤bθxWhen a is more than or equal to 1.2 and less than or equal to 1.8; b is more than or equal to 2.0 and less than or equal to 2.4; considering the normal operation of the vibrating screen, if the theta obtained by analysis is normalmIf the vibration signal is not in the interval range, fault alarming is carried out, the fault vibration signal is stored in the data storage, and when the vibration screen sensor collects the fault vibration signal next time, fault alarming is directly carried out.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112014046A (en) * | 2020-08-11 | 2020-12-01 | 河南科技大学 | Combine harvester assembling quality vibration monitoring test bed and test method |
CN112364291A (en) * | 2020-11-17 | 2021-02-12 | 哈工大机器人(合肥)国际创新研究院 | Pre-filtering extreme point optimization set empirical mode decomposition method and device |
CN117094992A (en) * | 2023-10-17 | 2023-11-21 | 广州长川科技有限公司 | Electrical equipment fault detection method and system based on image processing |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN201302674Y (en) * | 2008-11-11 | 2009-09-02 | 西安锦程振动科技有限责任公司 | Portable vibrating screen measuring and controlling instrument |
CN104438072A (en) * | 2013-09-18 | 2015-03-25 | 宝钢不锈钢有限公司 | Vibrating screen operation detection device |
CN107389323A (en) * | 2017-06-29 | 2017-11-24 | 西安建筑科技大学 | A kind of vibratory sieve remote fault diagnosis based on cloud computing and maintenance system and method |
CN206847885U (en) * | 2017-06-08 | 2018-01-05 | 广东星磁检测技术研究有限公司 | A kind of novel vibrating testboard |
CN108152064A (en) * | 2017-12-26 | 2018-06-12 | 华侨大学 | A kind of vibrating screen fault signature extracting method and failure monitoring system |
CN108332955A (en) * | 2017-12-22 | 2018-07-27 | 江苏新道格自控科技有限公司 | A kind of mechanical linkages loosening detection and method for early warning based on vibration signal |
WO2019234832A1 (en) * | 2018-06-05 | 2019-12-12 | 日本電気株式会社 | Diagnosis device, diagnosis method, and computer readable storage medium |
-
2020
- 2020-02-21 CN CN202010106244.3A patent/CN111256928A/en active Pending
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN201302674Y (en) * | 2008-11-11 | 2009-09-02 | 西安锦程振动科技有限责任公司 | Portable vibrating screen measuring and controlling instrument |
CN104438072A (en) * | 2013-09-18 | 2015-03-25 | 宝钢不锈钢有限公司 | Vibrating screen operation detection device |
CN206847885U (en) * | 2017-06-08 | 2018-01-05 | 广东星磁检测技术研究有限公司 | A kind of novel vibrating testboard |
CN107389323A (en) * | 2017-06-29 | 2017-11-24 | 西安建筑科技大学 | A kind of vibratory sieve remote fault diagnosis based on cloud computing and maintenance system and method |
CN108332955A (en) * | 2017-12-22 | 2018-07-27 | 江苏新道格自控科技有限公司 | A kind of mechanical linkages loosening detection and method for early warning based on vibration signal |
CN108152064A (en) * | 2017-12-26 | 2018-06-12 | 华侨大学 | A kind of vibrating screen fault signature extracting method and failure monitoring system |
WO2019234832A1 (en) * | 2018-06-05 | 2019-12-12 | 日本電気株式会社 | Diagnosis device, diagnosis method, and computer readable storage medium |
Non-Patent Citations (1)
Title |
---|
JINDE ZHENG 等: "Extreme-point weighted mode decomposition", 《SIGNAL PROCESSING》 * |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112014046A (en) * | 2020-08-11 | 2020-12-01 | 河南科技大学 | Combine harvester assembling quality vibration monitoring test bed and test method |
CN112364291A (en) * | 2020-11-17 | 2021-02-12 | 哈工大机器人(合肥)国际创新研究院 | Pre-filtering extreme point optimization set empirical mode decomposition method and device |
CN112364291B (en) * | 2020-11-17 | 2024-05-14 | 哈工大机器人(合肥)国际创新研究院 | Empirical mode decomposition method and device for pre-filtering extreme point optimization set |
CN117094992A (en) * | 2023-10-17 | 2023-11-21 | 广州长川科技有限公司 | Electrical equipment fault detection method and system based on image processing |
CN117094992B (en) * | 2023-10-17 | 2024-03-12 | 广州长川科技有限公司 | Electrical equipment fault detection method and system based on image processing |
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