CN118190397B - Gear abrasion rapid measurement method for industrial cooling fan - Google Patents

Abstract

The invention relates to the technical field of fan operation data processing, in particular to a gear abrasion rapid measurement method for an industrial cooling fan. Firstly, vibration data and rotation speed data of a cooling fan gear are obtained; further acquiring vibration abnormal parameters of each data period to be analyzed; further acquiring the gear wear rate of each data period to be analyzed; further acquiring a time sequence of the gear wear rate; further acquiring a local data segment; finally, according to the change characteristics of the abrasion rate of the internal gear of each partial data segment, combining the change characteristics of the abrasion rate of the gears in the time sequence to obtain the abrasion degree of the gears. According to the invention, the influence of the rotation speed of the gear on the vibration data is eliminated by analyzing the difference of the vibration data in other sampling periods and the reference period and combining the difference of the rotation speed data; and then the gear wear degree is obtained according to the change characteristics of the sequence formed by the gear wear rate, so that the accuracy of the detection method is improved.

Description

A fast measurement method for gear wear in industrial cooling fans

Technical Field

The invention relates to the technical field of fan operation data processing, and in particular to a gear wear rapid measurement method for an industrial cooling fan.

Background Art

Industrial cooling fan gears usually refer to the gears used to drive the fan in the industrial cooling system. During the operation of the fan, the fan gears may wear out due to the increase in usage time, and the worn gears will have a certain impact on the stability of the fan operation. Therefore, it is necessary to detect the wear of the fan gears. When the degree of wear is large, it is necessary to maintain or replace it in time to avoid the degree of wear and tear affecting the normal operation of the fan.

Existing gear wear detection is generally carried out through visual means or by collecting gear-related vibration data. When using gear vibration-related data for gear wear detection, since the operating speed of the fan is related to the actual cooling demand, that is, the speed of the gear varies in different time periods, the collected vibration data will also change. When using vibration data for gear wear detection, it is difficult to unify the variables of the influencing factors, resulting in inaccurate gear wear detection results.

Summary of the invention

In order to solve the technical problem that the gear speed affects the vibration data and causes inaccurate gear wear detection results, the purpose of the present invention is to provide a rapid measurement method for gear wear of industrial cooling fans. The technical solution adopted is as follows:

A method for quickly measuring gear wear of an industrial cooling fan, the method comprising:

The vibration data and speed data of the cooling fan gear are obtained at a preset sampling period; the first sampling period is used as a reference period, and the other sampling periods are used as data periods to be analyzed;

According to the difference characteristics of the vibration data between each data cycle to be analyzed and the reference cycle, combined with the difference characteristics of the speed data between each data cycle to be analyzed and the reference cycle, the vibration abnormality parameter of each data cycle to be analyzed is obtained; according to the sampling time interval between each data cycle to be analyzed and the reference cycle, combined with the corresponding vibration abnormality parameter, the gear wear rate of each data cycle to be analyzed is obtained;

A time series of the gear wear rate is obtained; in the time series, a local data segment is obtained based on preset neighborhood parameters with each gear wear rate as the center; and the gear wear degree is obtained based on the change characteristics of the gear wear rate in each local data segment and in combination with the change characteristics of the gear wear rate in the time series.

Furthermore, the method for obtaining the abnormal vibration parameters includes:

Acquire a first difference parameter for each period of data to be analyzed according to a difference characteristic of the amplitude in the vibration data between each period of data to be analyzed and the reference period;

Acquire a second difference parameter for each period of data to be analyzed according to a difference characteristic of the frequency in the vibration data between each period of data to be analyzed and the reference period;

Acquire a third difference parameter for each data period to be analyzed according to difference characteristics of the data curve fitted by the vibration data between each data period to be analyzed and the reference period;

Acquire a fourth difference parameter of each data period to be analyzed according to the difference characteristics of the rotation speed data between each data period to be analyzed and the reference period;

The vibration abnormality parameter of each data period to be analyzed is obtained according to the first difference parameter, the second difference parameter, the third difference parameter and the fourth difference parameter between each data period to be analyzed and the reference period; the first difference parameter, the second difference parameter and the third difference parameter are all positively correlated with the vibration abnormality parameter; the fourth difference parameter is negatively correlated with the vibration abnormality parameter.

Furthermore, the method for obtaining the second difference parameter includes:

According to the difference characteristics of the number of extreme value points in the vibration data between each data period to be analyzed and the reference period, a second difference parameter of each data period to be analyzed is obtained.

Furthermore, the method for obtaining the gear wear degree includes:

According to the variation characteristics of the gear wear rate in each local data segment, a reference data segment is obtained;

Obtaining a first wear parameter according to the difference characteristics of the gear wear rate in the reference data segment and other local data segments;

Obtaining a second wear parameter according to the statistical characteristics of the gear wear rate in the time series;

The time series is segmented at the center of the reference data segment, and a third wear parameter is obtained according to the difference characteristics of the gear wear rates in the time series on the left and right sides after the segmentation;

The gear wear degree is obtained according to the first wear parameter, the second wear parameter and the third wear parameter; the first wear parameter, the second wear parameter and the third wear parameter are all positively correlated with the gear wear degree.

Furthermore, the method for obtaining the reference data segment includes:

Obtaining the variance of the gear wear rate in each local data segment as a first stable parameter;

Obtaining an absolute value of a difference between a mean value of the gear wear rate in each local data segment and a mean value of the time series as a second stable parameter;

According to the first stability parameter and the second stability parameter, a stability parameter of each local data segment is obtained; the local data segment with the largest stability parameter is used as a reference data segment; the first stability parameter and the second stability parameter are both negatively correlated with the stability parameter.

Furthermore, the method for obtaining the first wear parameter includes:

The absolute value of the difference between the mean value of the gear wear rate in the reference data segment and the mean value of the gear wear rate in other local data segments is taken as an operation fluctuation parameter, and the average value of all the operation fluctuation parameters is taken as the first wear parameter.

Furthermore, the method for obtaining the third wear parameter includes:

The ratio of the mean value of the gear wear rate in the right time series after segmentation to the mean value of the gear wear rate in the left time series is used as the third wear parameter; wherein the right side is the side with the largest sampling time.

Furthermore, the method for calculating the gear wear degree includes:

After the product of the first wear parameter, the second wear parameter and the third wear parameter is normalized, the normalized result is used as the gear wear degree.

Furthermore, the algorithm used when acquiring the third difference parameter is a DTW algorithm.

Furthermore, the method for obtaining the gear wear rate includes:

The sampling time interval between each data cycle to be analyzed and the reference cycle is used as the denominator, the corresponding vibration abnormality parameter is used as the numerator, and the fraction is used as the gear wear rate of each data cycle to be analyzed.

The present invention has the following beneficial effects:

The present invention first obtains the vibration data and speed data of the cooling fan gear in a preset sampling period, so as to provide an analysis basis for subsequent analysis; further, the first sampling period in which the fan gear wear is the smallest is used as the reference period, and other sampling periods are used as the data period to be analyzed, which is more conducive to the subsequent understanding of the gear wear condition; further, according to the difference characteristics of the vibration data and speed data between each data period to be analyzed and the reference period, the vibration abnormality parameters of each data period to be analyzed are obtained, the influence of the gear speed on the vibration data is eliminated, and the accuracy of the final detection result is improved; further, according to the sampling time interval between each data period to be analyzed and the reference period, combined with the corresponding vibration abnormality parameters, the gear wear rate of each data period to be analyzed is obtained, so as to provide a basis for the subsequent analysis of the change of gear wear; further, the time series sequence of the gear wear rate is obtained and the local data segment is obtained, so as to facilitate the subsequent analysis of the change of gear wear from both the overall and local perspectives; finally, according to the change characteristics of the gear wear rate in each local data segment, combined with the change characteristics of the gear wear rate in the time series sequence, the gear wear degree is obtained. The present invention eliminates the influence of gear speed on vibration data by analyzing the difference between vibration data in other sampling periods and the reference period, combined with the difference in speed data; then, the gear wear degree is obtained according to the changing characteristics of the sequence composed of gear wear rate, thereby improving the accuracy of the detection method.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

FIG1 is a flow chart of a method for rapid measurement of gear wear for industrial cooling fans provided by an embodiment of the present invention;

FIG2 is a flow chart of a method for obtaining abnormal vibration parameters provided by an embodiment of the present invention;

FIG. 3 is a flow chart of a method for obtaining the degree of gear wear provided by an embodiment of the present invention.

DETAILED DESCRIPTION

In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a gear wear rapid measurement method for industrial cooling fans proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

The specific scheme of the method for rapid measurement of gear wear for industrial cooling fans provided by the present invention is described in detail below with reference to the accompanying drawings.

Please refer to FIG1 , which shows a flow chart of a method for rapid measurement of gear wear for industrial cooling fans provided by an embodiment of the present invention, which specifically includes:

Step S1: Acquire the vibration data and speed data of the cooling fan gear in a preset sampling period; take the first sampling period as a reference period, and the other sampling periods as data periods to be analyzed.

In the embodiment of the present invention, considering the different refrigeration demands at different times and the different working modes of the industrial cooling fan, the monitoring data is obtained in a preset sampling period; and in order to analyze the relationship between the gear speed and the vibration data, the vibration data and speed data of the cooling fan gear are obtained in a preset sampling period to provide an analysis basis for subsequent analysis. Considering that the degree of wear of the fan gear increases with the increase of the use time during use, in order to understand the change of gear wear, the first sampling period is used as the reference period, and the other sampling periods are used as the data period to be analyzed, and the difference between the data in other sampling periods and the reference period is analyzed later.

It should be noted that, in one embodiment of the present invention, the preset sampling period is 1 minute and the sampling frequency is 1 second/time; in other embodiments of the present invention, implementers can adjust the sampling period and sampling frequency by themselves.

Step S2: According to the difference characteristics of the vibration data between each data cycle to be analyzed and the reference cycle, combined with the difference characteristics of the speed data between each data cycle to be analyzed and the reference cycle, the vibration abnormality parameters of each data cycle to be analyzed are obtained; according to the sampling time interval between each data cycle to be analyzed and the reference cycle, combined with the corresponding vibration abnormality parameters, the gear wear rate of each data cycle to be analyzed is obtained.

In the embodiment of the present invention, it is considered that the greater the difference in vibration data between the data cycle to be analyzed and the reference cycle, the greater the vibration difference, and the more obvious the abnormal characteristics exhibited by the data cycle to be analyzed; and the greater the difference in speed data between the data cycle to be analyzed and the reference cycle, the greater the difference in the operating mode of the fan, and the lower the credibility of the abnormal characteristics exhibited by the vibration data. Therefore, according to the difference characteristics of vibration data between each data cycle to be analyzed and the reference cycle, combined with the difference characteristics of speed data between each data cycle to be analyzed and the reference cycle, the vibration abnormality parameters of each data cycle to be analyzed are obtained, and the influence of different speeds of different operating modes of the fan on the vibration data is eliminated, thereby providing a basis for subsequent analysis of gear wear characteristics.

Preferably, in one embodiment of the present invention, the method for obtaining abnormal vibration parameters includes:

Please refer to FIG. 2 , which shows a flow chart of a method for obtaining abnormal vibration parameters provided by an embodiment of the present invention:

Step S101: acquiring a first difference parameter of each data period to be analyzed according to a difference characteristic of the amplitude in the vibration data between each data period to be analyzed and a reference period.

Considering that the amplitude of vibration data is an important indicator in vibration analysis, the amplitude can reflect the operating status and health of the fan. Therefore, according to the difference characteristics of the amplitude in the vibration data between each data period to be analyzed and the reference period, the first difference parameter of each data period to be analyzed is obtained, and the first difference parameter is positively correlated with the vibration abnormality parameter.

In one embodiment of the present invention, the absolute value of the difference between the average amplitude of the vibration data in the data period to be analyzed and the average amplitude of the vibration data in the reference period is used as the first difference parameter. In other embodiments of the present invention, the first difference parameter can also be obtained through other amplitude difference angles such as the difference in amplitude fluctuation range and the difference in amplitude change rate.

Step S102: acquiring a second difference parameter of each data period to be analyzed according to a difference characteristic of the frequency in the vibration data between each data period to be analyzed and a reference period.

Considering that the frequency of vibration data is also an important indicator of vibration analysis, when mechanical parts fail or wear out, the frequency characteristics in the vibration signal will change. Therefore, according to the difference characteristics of the frequency in the vibration data between each data period to be analyzed and the reference period, the second difference parameter of each data period to be analyzed is obtained, and the second difference parameter is positively correlated with the vibration abnormality parameter.

In one embodiment of the present invention, considering that the higher the frequency of the vibration signal, the more extreme points there are, and the number of extreme points indirectly reflects the frequency characteristics of the vibration data, the absolute value of the difference in the number of extreme points in the vibration data between each data period to be analyzed and the reference period is used as the second difference parameter based on the difference characteristics of the number of extreme points in the vibration data between the data period to be analyzed and the reference period.

In other embodiments of the present invention, the implementer may also obtain other existing technologies with the help of the spectrum diagram, extract the main frequency of the vibration data in the data period to be analyzed and the main frequency of the vibration data in the reference period, analyze the difference characteristics of the main frequencies, and obtain the second difference parameter; or analyze the range difference and distribution difference of the frequency to obtain the second difference parameter.

Step S103: acquiring a third difference parameter of each data period to be analyzed according to the difference characteristics of the data curve fitted by the vibration data between each data period to be analyzed and the reference period.

Considering the fitting curve of the vibration data, the difference characteristics of the data curve can also reflect the abnormal characteristics of the vibration data in the data period to be analyzed. Therefore, the third difference parameter of each data period to be analyzed is obtained based on the difference characteristics of the data curve fitted by the vibration data between each data period to be analyzed and the reference period. The third difference parameter is positively correlated with the vibration abnormality parameter.

In one embodiment of the present invention, a DTW (Dynamic Time Warping) algorithm is used to obtain the DTW distance of a data curve fitted by vibration data between a data period to be analyzed and a reference period. The larger the DTW distance, the lower the similarity between the two data curves and the greater the degree of difference. Therefore, the DTW distance is used as the third difference parameter.

In other embodiments of the present invention, the implementer may also indirectly obtain the third difference parameter through algorithms such as cosine similarity and Pearson correlation coefficient in the prior art, which are technical means well known to those skilled in the art and will not be described in detail here.

Step S104: acquiring a fourth difference parameter of each data period to be analyzed according to the difference characteristics of the rotation speed data between each data period to be analyzed and the reference period.

Taking into account that the rotation speed represents the cooling demand of the cooling fan and also reflects the working mode of the cooling fan, and different rotation speeds will inevitably cause changes in the vibration characteristics, the fourth difference parameter of each data period to be analyzed is obtained according to the difference characteristics of the rotation speed data between each data period to be analyzed and the reference period. The larger the fourth difference parameter is, the more likely it is that the vibration data change is caused by the working mode. The fourth difference parameter is used for correction. The fourth difference parameter is negatively correlated with the abnormal vibration parameter.

In one embodiment of the present invention, the absolute value of the difference between the mean of the rotational speed data in the data period to be analyzed and the mean of the rotational speed data in the reference period is used as the fourth difference parameter. In other embodiments of the present invention, considering that the rotational speed change will also cause the vibration data to fluctuate, the fourth difference parameter can also be obtained from the perspective of the rotational speed change, according to the rotational speed change rate and the distribution range of the rotational speed.

Step S105: Obtain the vibration abnormality parameter of each data period to be analyzed according to the first difference parameter, the second difference parameter, the third difference parameter and the fourth difference parameter between each data period to be analyzed and the reference period.

After obtaining the difference parameters between the data period to be analyzed and the reference period, the vibration abnormality parameters of the data period to be analyzed can be obtained by combining the difference features of multiple angles.

In one embodiment of the present invention, the sum of the first difference parameter, the second difference parameter and the third difference parameter is mapped using an exponential function, and the ratio of the mapping result to the fourth difference parameter is used as the vibration abnormality parameter. The calculation formula of the vibration abnormality parameter includes:

;

in, Indicates the serial number of the data period to be analyzed; Indicates The vibration anomaly parameters of the data period to be analyzed; Indicated by natural constant The exponential function with base ; Indicates The first difference parameter of the data period to be analyzed; Indicates A second difference parameter of the data period to be analyzed; Indicates The third difference parameter of the data period to be analyzed; Indicates The fourth difference parameter of the data period to be analyzed, is a division by zero parameter. In one embodiment of the present invention, .

It should be noted that in other embodiments of the present invention, other basic mathematical operations or function mappings may also be used to implement relevant mappings, which are technical means well known to those skilled in the art and will not be elaborated herein.

Among them, a positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. The specific relationship can be a multiplication relationship, an addition relationship, or the power of an exponential function, which is determined by actual application; a negative correlation means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by actual application.

Taking into account that the degree of wear of fan gears will increase with the increase of usage time during use, in order to analyze the changes in gear wear, the gear wear rate of each data cycle to be analyzed is obtained according to the sampling time interval between each data cycle to be analyzed and the reference cycle, combined with the corresponding vibration abnormality parameters, and the speed of change of gear wear is measured. At the same time, it is convenient to analyze the changes in gear wear rate and the degree of gear wear in subsequent steps.

Preferably, in one embodiment of the present invention, the sampling time interval between each data cycle to be analyzed and the reference cycle is used as the denominator, the corresponding vibration abnormality parameter is used as the numerator, and the fraction is used as the gear wear rate of each data cycle to be analyzed.

It should be noted that the time interval between the first sampling moments of different sampling periods is used as the sampling time interval between the period of the data to be analyzed and the reference period.

Step S3: Obtain a time series of gear wear rates; in the time series, take each gear wear rate as the center and obtain a local data segment according to preset neighborhood parameters; obtain the gear wear degree according to the change characteristics of the gear wear rate in each local data segment and the change characteristics of the gear wear rate in the time series.

Experience shows that the wear rate of mechanical equipment such as fan gears will not remain constant during actual use. Instead, as the mechanical system operates, aging and fatigue damage of material components continue to accumulate. At the same time, the meshing degree between gear lubricants and gears continues to decrease, and the gear wear rate will change. At the same time, different operating modes of the fan produce different loss rates. Therefore, the changing characteristics of the gear wear rate can reflect the wear condition of the gear, so the time series of the gear wear rate is obtained.

It should be noted that, in the embodiment of the present invention, the time series is composed of gear wear rates, and the gear wear rates in the time series are sorted in ascending order according to the first sampling time of the sampling period to which they belong.

In the embodiment of the present invention, considering that during the operation of the fan, the higher the frequency of switching the operating mode in a short period of time, the more likely it is to cause wear on the gears, so in the time series sequence, with the wear rate of each gear as the center, local data segments are obtained according to preset neighborhood parameters, which is convenient for subsequent analysis in the analysis of the local data segments.

Preferably, in one embodiment of the present invention, the preset neighborhood parameter is 5, that is, the length of the local data segment is 5. In other embodiments of the present invention, the implementer may set other preset neighborhood parameters; for the beginning and end of the time series sequence, other prediction or fitting methods in the prior art such as polynomial fitting may be used to supplement the data values to facilitate the acquisition of the corresponding local data segment.

After obtaining the time series of the gear wear rate and the local data segments, the gear wear degree is obtained according to the change characteristics of the gear wear rate in each local data segment combined with the change characteristics of the gear wear rate in the time series.

Preferably, in one embodiment of the present invention, the method for obtaining the gear wear degree includes:

Please refer to FIG3 , which shows a flow chart of a method for obtaining the degree of gear wear provided by an embodiment of the present invention:

Step S201: Obtain a reference data segment according to the variation characteristics of the gear wear rate in each local data segment.

Considering that there are relatively stable local data segments among all the local data segments, they are used as reference data segments to facilitate comparison of the fluctuation characteristics of other local data segments.

In one embodiment of the present invention, considering that the smaller the variance is, the more stable the data fluctuation is, the variance of the gear wear rate in each local data segment is obtained as the first stability parameter, and the first stability parameter is negatively correlated with the stability parameter;

Considering that the smaller the difference between the mean of the gear wear rate in the local data segment and the mean of the time series is, the more the local data segment can represent the overall sequence characteristics, so the absolute value of the difference between the mean of the gear wear rate in each local data segment and the mean of the time series is obtained as the second stability parameter, and the second stability parameter is negatively correlated with the stability degree parameter;

According to the first stability parameter and the second stability parameter, a stability parameter of each local data segment is obtained; and the local data segment with the largest stability parameter is used as a reference data segment.

In one embodiment of the present invention, the product of the first stability parameter and the second stability parameter is negatively correlated and normalized, and the normalized result is used as the stability parameter; the calculation formula of the stability parameter includes:

;

in, Indicates the sequence number of the local data segment; Indicates The stability parameter of a local data segment; Indicated by natural constant The exponential function with base ; Indicates The first stable parameter of a local data segment; Indicates The second stable parameter of a local data segment.

It should be noted that in other embodiments of the present invention, other data characteristics such as mean absolute deviation and coefficient of variation can also be obtained to analyze the stability of the data, and other basic mathematical operations or function mappings can also be used to achieve relevant mappings. These are technical means well known to those skilled in the art and will not be elaborated here.

It should be noted that when there are multiple maximum stability parameters, considering that the shorter the running time, the lower the degree of wear of the fan gear and the stronger the reference, the local time period with the earliest sampling time among all local time periods with the largest stability parameters is selected as the reference time period.

Step S202: Obtain a first wear parameter according to the difference characteristics of the gear wear rates in the reference data segment and other local data segments.

Considering that the greater the difference between the gear wear rate in the reference data segment and other local data segments, the worse the consistency of the wear rate, it reflects that the higher the frequency of changes in the gear operation mode, the greater the gear wear degree, and the first wear parameter is positively correlated with the gear wear degree.

In one embodiment of the present invention, considering that the mean of the gear wear rate in a local data segment represents the overall characteristics of the data segment, the absolute value of the difference between the mean of the gear wear rate in the reference data segment and the mean of the gear wear rate in other local data segments is taken as an operating fluctuation parameter, and the average of all operating fluctuation parameters is taken as the first wear parameter.

In other embodiments of the present invention, the implementer may also average the difference between the stability parameters of other local data segments and the stability parameters of the reference data segment according to the difference in the stability parameters, and use the average as the first wear parameter.

Step S203: Obtain a second wear parameter according to the statistical characteristics of the gear wear rate in the time series.

Considering that the greater the gear wear rate of the overall time series, the greater the gear wear degree, the second wear parameter is obtained according to the statistical characteristics of the gear wear rate in the time series, and the second wear parameter is positively correlated with the gear wear degree.

In one embodiment of the present invention, the mean of the wear rates of all gears in the time series is used as the second wear parameter. In other embodiments of the present invention, the implementer may also obtain the second wear parameter based on the mid-range number, mode, etc., for example, the mean, mode, and average of the mid-range number of the wear rates of all gears are used as the second wear parameter.

Step S204: segmenting the time series at the center of the reference data segment, and obtaining a third wear parameter according to the difference characteristics of the gear wear rates in the time series on the left and right sides after segmentation.

Considering that the wear rate of gears increases with the increase of working time under the same operating conditions, the time series shows an increasing trend as a whole, and the faster the increase, the greater the degree of gear wear; therefore, the time series is segmented at the center of the reference data segment, and the third wear parameter is obtained based on the difference characteristics of the gear wear rates in the time series on the left and right sides after segmentation.

In one embodiment of the present invention, the ratio of the mean gear wear rate in the right time series after segmentation to the mean gear wear rate in the left time series is used as the third wear parameter; wherein the right side is the side with the largest sampling time.

The overall gear wear rate in the right timing sequence is larger than that in the left timing sequence, which means that the wear rate increases faster, which is more consistent with the characteristics of gear wear in actual wind turbine operation. The larger the third wear parameter, the greater the degree of gear wear.

In other embodiments of the present invention, the implementer may also divide the time sequence into two equal parts according to the median of the time sequence to obtain the third wear parameter; wherein when the time sequence is an odd number, the gear wear rate at the median is not included in the calculation.

Step S205: Obtain the gear wear degree according to the first wear parameter, the second wear parameter and the third wear parameter.

In one embodiment of the present invention, after the product of the first wear parameter, the second wear parameter and the third wear parameter is normalized, the normalized result is used as the gear wear degree.

In other embodiments of the present invention, other basic mathematical operations or function mappings may be used to implement relevant mappings, which are technical means well known to those skilled in the art and will not be elaborated herein.

In other embodiments of the present invention, the implementer may also analyze the degree of gear wear in combination with the operating time of the industrial cooling fan. Since the longer the operating time, the greater the loss to the gear, the operating time is positively correlated with the degree of gear wear.

It should be noted that the embodiment of the present invention is also applicable to real-time detection. It only needs to use the sampling data acquired in real time as the data in the new data cycle to be analyzed, and then execute step S2, update the timing sequence, and then execute step S3 to output the real-time gear wear degree.

It should be noted that, in one embodiment of the present invention, when the gear wear degree is greater than 0.3, it is considered that the gear of the cooling fan is in an abnormal working state and needs to be maintained or replaced in time.

In summary, the present invention aims at the technical problem that the gear speed affects the vibration data and causes the gear wear detection result to be inaccurate, and proposes a fast gear wear measurement method for industrial cooling fans. The present invention first obtains the vibration data and speed data of the cooling fan gear with a preset sampling period; takes the first sampling period as the reference period, and the other sampling periods as the data period to be analyzed; further, according to the difference characteristics of the vibration data and speed data between each data period to be analyzed and the reference period, obtains the vibration abnormality parameters of each data period to be analyzed; further, according to the sampling time interval between each data period to be analyzed and the reference period, combined with the corresponding vibration abnormality parameters, obtains the gear wear rate of each data period to be analyzed; further obtains the time series of the gear wear rate; further in the time series, with each gear wear rate as the center, obtains the local data segment according to the preset neighborhood parameters; finally, according to the change characteristics of the gear wear rate in each local data segment, combined with the change characteristics of the gear wear rate in the time series, obtains the gear wear degree. The present invention eliminates the influence of gear speed on vibration data by analyzing the difference between vibration data in other sampling periods and the reference period, combined with the difference in speed data; then, the gear wear degree is obtained according to the changing characteristics of the sequence composed of gear wear rate, thereby improving the accuracy of the detection method.

It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims (7)

1. The method for rapidly measuring the gear wear facing the industrial cooling fan is characterized by comprising the following steps of:

Obtaining vibration data and rotation speed data of a cooling fan gear according to a preset sampling period; taking the first sampling period as a reference period, and taking other sampling periods as data periods to be analyzed;

according to the difference characteristics of the vibration data between each data period to be analyzed and the reference period, combining the difference characteristics of the rotating speed data between each data period to be analyzed and the reference period to obtain vibration abnormal parameters of each data period to be analyzed; according to the sampling time interval between each data period to be analyzed and the reference period, combining the corresponding vibration abnormal parameters to obtain the gear wear rate of each data period to be analyzed;

Acquiring a time sequence of the gear wear rate; in the time sequence, taking each gear abrasion rate as a center, and acquiring a local data segment according to a preset neighborhood parameter; according to the change characteristics of the gear wear rate in each local data segment, combining the change characteristics of the gear wear rate in the time sequence to obtain the gear wear degree;

The method for acquiring the vibration abnormal parameters comprises the following steps:

acquiring a first difference parameter of each data period to be analyzed according to the difference characteristic of the amplitude in the vibration data between each data period to be analyzed and the reference period;

Acquiring a second difference parameter of each data period to be analyzed according to the difference characteristic of the frequency in the vibration data between each data period to be analyzed and the reference period;

According to the difference characteristics of the data curve fitted by the vibration data between each data period to be analyzed and the reference period, obtaining a third difference parameter of each data period to be analyzed;

According to the difference characteristics of the rotating speed data between each data period to be analyzed and the reference period, a fourth difference parameter of each data period to be analyzed is obtained;

Acquiring the vibration abnormal parameter of each data period to be analyzed according to the first difference parameter, the second difference parameter, the third difference parameter and the fourth difference parameter between each data period to be analyzed and the reference period; the first difference parameter, the second difference parameter and the third difference parameter are all positively correlated with the vibration anomaly parameter; the fourth difference parameter is inversely related to the vibration anomaly parameter;

the method for acquiring the abrasion degree of the gear comprises the following steps:

Obtaining a reference data segment according to the change characteristic of the gear wear rate in each local data segment;

obtaining a first abrasion parameter according to the difference characteristic of the abrasion rate of the gear in the reference data segment and other local data segments;

obtaining a second wear parameter according to the statistical characteristics of the gear wear rate in the time sequence;

dividing the time sequence by the center of the reference data segment, and acquiring a third abrasion parameter according to the difference characteristic of the abrasion rate of the gears in the divided time sequence on the left side and the right side;

acquiring the abrasion degree of the gear according to the first abrasion parameter, the second abrasion parameter and the third abrasion parameter; the first wear parameter, the second wear parameter, and the third wear parameter are all positively correlated with the gear wear level;

the method for acquiring the gear wear rate comprises the following steps:

Taking the sampling time interval between each data period to be analyzed and the reference period as a denominator, taking the corresponding vibration abnormal parameter as a numerator, and taking the formula as the gear wear rate of each data period to be analyzed.

2. The method for quickly measuring gear wear for an industrial cooling fan according to claim 1, wherein the method for acquiring the second difference parameter comprises the following steps:

And obtaining a second difference parameter of each data period to be analyzed according to the difference characteristic of the number of extreme points in the vibration data between each data period to be analyzed and the reference period.

3. The rapid gear wear measurement method for an industrial cooling fan according to claim 1, wherein the reference data segment acquisition method comprises:

acquiring a variance of the gear wear rate in each local data segment as a first stability parameter;

Acquiring a difference absolute value of the average value of the gear wear rate in each local data segment and the average value of the time sequence as a second stable parameter;

Acquiring a stability degree parameter of each local data segment according to the first stability parameter and the second stability parameter; taking the local data segment with the maximum stability parameter as a reference data segment; the first stability parameter and the second stability parameter are both inversely related to the stability level parameter.

4. The rapid gear wear measurement method for an industrial cooling fan according to claim 1, wherein the method for obtaining the first wear parameter comprises:

And taking the absolute value of the difference between the average value of the gear wear rate in the reference data segment and the average value of the gear wear rate in other local data segments as an operation fluctuation parameter, and taking the average value of all the operation fluctuation parameters as the first wear parameter.

5. The rapid gear wear measurement method for an industrial cooling fan according to claim 1, wherein the third wear parameter obtaining method comprises:

taking the ratio of the average value of the gear wear rate in the divided right time sequence to the average value of the gear wear rate in the left time sequence as a third wear parameter; wherein the right side is the side with the largest sampling time.

6. The rapid gear wear measurement method for an industrial cooling fan according to claim 1, wherein the gear wear degree calculation method comprises:

and normalizing the product of the first abrasion parameter, the second abrasion parameter and the third abrasion parameter, and taking the normalized result as the abrasion degree of the gear.

7. The rapid gear wear measurement method for an industrial cooling fan according to claim 1, wherein the algorithm used in the third difference parameter acquisition is a DTW algorithm.