JP6365526B2 - Bearing deterioration detection method and bearing deterioration detection device for small diameter roll - Google Patents

Description

  The present invention relates to a bearing deterioration detection method and a bearing deterioration detection device for a small diameter roll in a rolling line.

  In steel plate processing facilities such as cold rolling mills and tension levelers, it is known that various product defects occur due to abnormal vibration.

  For example, as shown in FIG. 1 (a), it is widely known that chatter marks, which are deformations accompanied by fluctuations in plate thickness, are generated in a steel sheet due to abnormal vibration in a rolling mill.

  The following patent documents 1 and 2 are cited as documents disclosing techniques for preventing the occurrence of chatter marks.

  In Patent Document 1, vibration intensity is obtained by frequency analysis of vibration measured by a vibration sensor installed in a cold rolling mill, and occurrence of chatter marks is detected. More specifically, a technique is disclosed in which a threshold value of vibration intensity is set for each frequency band, and a chatter mark is determined to be generated when a vibration intensity larger than the threshold value is observed.

  Patent Document 2 discloses a technology for detecting chatter marks by a device in which a laser distance meter and a radiation thickness meter are arranged in a steel plate traveling direction on a C-shaped frame provided so as to sandwich the upper and lower sides of a steel plate. It is disclosed.

Japanese Patent Laying-Open No. 2015-9261 JP 2005-83820 A

  However, as a product defect of the steel plate that occurs during rolling, apart from chatter marks that accompany the plate thickness variation of the steel plate, wavy deformation that does not involve the plate thickness variation of the steel plate also occurs. According to the study by the present inventors, as shown in FIG. 1B, the wavy deformation of the steel sheet does not occur due to abnormal vibration in the rolling mill such as chatter marks, but supports the steel sheet before and after the rolling mill. It was found that it was caused by abnormal vibration in the small diameter roll. More specifically, the bearing of the small-diameter roll deteriorates (wears), and abnormal vibration occurs when the small-diameter roll rotates. By this abnormal vibration, the steel sheet receives repeated bending forces in the vertical direction. It has been found that wavy deformation of the steel sheet occurs.

  However, conventionally, there is no known method for detecting such abnormal vibration of a small-diameter roll. Further, it is difficult to detect such abnormal vibration of the small-diameter roll even if a conventionally known method used for detecting the chatter mark is used.

  The first reason that it is difficult to detect the wavy deformation of the steel sheet with the prior art is that the vibration due to the deterioration of the roll bearing has a different vibration frequency depending on the speed of the line, the location where the bearing is worn, etc. It is done. For example, as in Patent Document 1, in the method of setting a threshold value in a frequency band close to the natural frequency of the rolling mill body, a peak is seen in a frequency band that is distant from the natural frequency of the rolling mill. It is impossible to accurately detect the vibration caused by.

  The second reason why it is difficult to detect wavy deformation with the prior art is that there are a large number of rolls that support the steel sheet on the entry side and the exit side of the rolling mill, and the bearing wear of any roll is subject to vibration. It is difficult to identify the cause. For example, in the method of measuring the vibration of the steel sheet at only one location on the line as in Patent Document 2, it is difficult to specify which abnormal vibration has occurred due to wear of the bearing of which roll. It is.

  If the deterioration of the bearing is remarkable (abnormal), a large wave-like deformation occurs in the steel sheet, resulting in a product defect. In such a case, it is necessary to detect the roll with deteriorated bearings at an early stage and to take measures such as replacement of the bearings to suppress the expansion of product defects. However, as described above, in the conventional method, it is difficult to specify which roll bearing is abnormal, and the bearing causing the product failure cannot be detected at an early stage. A defective product cannot be prevented from being produced for a long time.

  The present invention has been completed in view of the above problems, and it is an object of the present invention to provide a bearing deterioration detection method and a bearing deterioration detection device for a small-diameter roll that can detect a deteriorated roll bearing at an early stage. And

Means of the present invention are as follows.
[1] A vibration signal collecting step for collecting vibration signals detected by at least one of the small diameter rolls provided on the entry side or the exit side of the rolling mill, and a fast Fourier transform method for the collected vibration signals. The frequency analysis is performed to obtain the frequency component included in the vibration signal and the spectrum value thereof, and from the result of the frequency analysis, the peak of the fundamental frequency derived from the deterioration of the bearing of the small diameter roll, and the fundamental frequency When a peak in a frequency band of n times (n is a positive integer greater than or equal to 2) is extracted and one of the spectral values of these peaks exceeds a preset threshold value, a bearing abnormality of a small diameter roll is detected. A bearing deterioration detection method for a small-diameter roll, characterized in that it is determined to be present.
[2] A vibration sensor that is attached to at least one of the small-diameter rolls provided on the entry side or exit side of the rolling mill and collects vibration signals, and a fast Fourier transform method for the vibration signals from the vibration sensors The frequency component included in the vibration signal and the spectrum value thereof are obtained, and the peak of the fundamental frequency derived from the deterioration of the bearing of the small diameter roll and n times the fundamental frequency (n is a positive value of 2 or more) An arithmetic device that extracts a peak in the frequency band and determines that the bearing of the small-diameter roll is abnormal when any of the peak spectral values exceeds a preset threshold value. A bearing deterioration detection device for small-diameter rolls.

  According to the present invention, it is possible to detect the deterioration of the bearing of the small-diameter roll in the rolling line at an early stage and prevent a large number of product defects from occurring.

FIG. 1 is an explanatory view of generation of chatter marks on a steel sheet due to abnormal vibration derived from a rolling mill and generation of wavy deformation of a steel sheet due to abnormal vibration derived from a small diameter roll. FIG. 2 is a block diagram of a bearing deterioration detecting device for a small-diameter roll according to the present invention. FIG. 3 is an explanatory diagram showing a processing flow in the arithmetic device. FIG. 4 is a graph showing the FFT frequency analysis results before and after the bearing replacement in the example.

  First, the present invention will be specifically described with reference to FIG.

  Many small-diameter rolls 2 are provided on the entry side (left side of the drawing) and the exit side (right side of the drawing) of the rolling mill 11 that rolls the steel plate 9. Examples of the small diameter roll 2 include a tension meter roll, a deflector roll, and a pass line roll. In the present invention, vibration sensors (not shown) are provided on at least one of these small diameter rolls 2, preferably all the small diameter rolls 2 on the entry side and the exit side of the rolling mill 11. Examples of the rolling mill 11 include a cold rolling mill and a temper rolling mill (skin pass mill).

  The vibration sensor can be tapped on a roll chock of a bearing on both end sides (also referred to as an op side and a dr side) that supports the small-diameter roll 2 and can be attached by screwing. As a vibration sensor, a piezoelectric element type vibration sensor is a preferred example, but any other type of vibration sensor may be used. The vibration sensor 1 detects the vibration of the small-diameter roll 2 that occurs when the steel plate 9 passes.

  The vibration data measured by the vibration sensor 1 is converted into an electric signal by an amplifier built in the vibration sensor 1. This electrical signal is sent to the arithmetic device 3. More specifically, the arithmetic device 3 includes a data processing unit 4 and a data storage unit 5, and vibration data is first sent to the data processing unit 4.

  The data processing unit 4 performs frequency analysis on the vibration data by a Fast Fourier Transform (FFT) method, extracts a vibration peak due to the bearing abnormality of the small diameter roll 2, compares it with a threshold value, and performs a bearing abnormality. Is detected.

  On the other hand, the data storage unit 5 stores and stores data input and processed by the data processing unit 4 in order to be useful for future frequency analysis.

  The flow in the arithmetic unit 3 will be described with reference to FIG. First, vibration signals measured by a vibration sensor installed on the bearing of each small-diameter roll are collected (S1). Next, by performing frequency analysis using the vibration signal, the frequency component included in the vibration signal and its magnitude (spectrum value) are obtained (S2).

  Next, from the result of the frequency analysis, the peak of vibration (cause of wave deformation) caused by the bearing of the small diameter roll is extracted (S3). More specifically, as vibration signals, vibrations caused by rolling mills (causes of chatter marks) and vibrations caused by bearings of small-diameter rolls (causes of occurrence of wave deformation) can be mainly measured. Only the peaks corresponding to the latter are extracted.

  In the case of vibration caused by a rolling mill, the peak of the spectrum value exists independently before and after the natural frequency of the rolling mill, and almost no periodic peak is observed. On the other hand, in the case of vibration caused by a small-diameter roll bearing, the peak of the spectral value is a fundamental frequency (f) determined by the line speed and the wear position of the bearing, and n times the fundamental frequency (n is an integer of 2 or more). It occurs periodically in the frequency band (2 × f, 3 × f,...). The fundamental frequency (f) is usually larger than the natural frequency of the rolling mill and is about 5 Hz to 1000 Hz.

  The arithmetic device 3 extracts a peak at the fundamental frequency (f). Next, the magnitude relationship between the peak spectrum value at the fundamental frequency (f) and a preset threshold value is compared (S4 in FIG. 3). When the spectrum value is larger than the threshold value, it is determined that an abnormality resulting from the deterioration of the bearing has occurred. When an abnormality is detected, the arithmetic device 3 preferably issues an alarm.

  Further, the arithmetic device 3 extracts not only the fundamental frequency (f) but also a peak in a frequency band n times the fundamental frequency (f) (n is an integer of 2 or more). In this case as well, the arithmetic device 3 determines the magnitude relationship between the spectrum value of each peak and a predetermined spectrum value. If at least one of the spectral values of these multiple peaks (f peak, 2 × f peak, 3 × f peak,...) Exceeds the threshold value, an abnormality caused by bearing deterioration Is determined to have occurred.

  The frequency band of n times the fundamental frequency (f) is not only an integer multiple of the fundamental frequency (2 × f, 3 × f,...) But also a frequency region slightly around the integer multiple. Including. For example, a region of about ± 10 Hz that is an integral multiple of the fundamental frequency may be included.

  The threshold value used for the determination is appropriately determined according to various rolling conditions. Examples of such conditions include coil information (steel type, application, plate thickness, plate width, etc.) and line information (line speed, tracking length, tension, etc.). These various conditions are appropriately input to the arithmetic unit 3 so that they can be considered when setting the threshold. For example, in the example of FIG. 2, coil information, line information, and the like can be appropriately input to the data processing unit 4 from the processing devices 6, 7, and 8 configured separately from the arithmetic device 3.

  Moreover, when setting a threshold value, it is possible to refer to the past performance. For example, the data processing unit 4 may search for past frequency analysis results stored in the data storage unit 5 and set a threshold value by comparing the past operation status and the current operation status. .

  The threshold value set in the fundamental frequency (f) and the threshold value set in the frequency band n times the fundamental frequency (f) may be the same value or different values.

  In an example in which vibration sensors are provided in a plurality of small-diameter rolls, signals output from the respective small-diameter rolls are separately subjected to FFT frequency analysis, peak extraction, and peak spectral value comparison with a threshold value. Thereby, when abnormality of a bearing is detected, it can be specified which small diameter roll corresponds.

  When it is determined that any one of the bearings is abnormal, the steel sheet is likely to be wave-like deformed, leading to a product defect. Therefore, the operator can perform various avoidance measures so that the product defect does not further expand. Specifically, first, it is confirmed whether or not the already manufactured steel sheet is defective. If there is a defect in the steel plate that has already been manufactured, the corresponding small-diameter roll or bearing may be replaced after the line is stopped.

  In order to detect the occurrence of instantaneous vibrations, it is preferable to make the interval for collecting and analyzing vibration signals as small as possible. Preferably, the vibration signal is collected and the frequency analysis is performed about once every 1 to 3 seconds. As an example, a vibration signal for 0.6 seconds is collected at a period of 0.2 ms, and FFT frequency analysis, peak extraction, and bearing abnormality determination are processed in the subsequent 0.4 second to obtain 1 second. Vibration signals can be collected and analyzed at a frequency of once.

  In addition, the arithmetic unit 3 can detect not only abnormal vibration derived from a small diameter roll but also abnormal vibration derived from a rolling mill. Abnormal vibration derived from a rolling mill is a vibration generated in a steel plate by the rolling mill and transmitted to a small-diameter roll through the steel plate. Specifically, the arithmetic device 3 extracts peaks before and after the natural frequency of the rolling mill, and issues a warning that there is a risk that chatter marks will occur if the spectral value of this peak is higher than a threshold value. You may do it. In this case, if it is possible to distinguish between an alarm informing about the danger of chatter marks and an alarm informing about the danger of wavy deformation due to vibration caused by a small-diameter roll, the operator will take appropriate measures according to each abnormality. be able to.

  As an example of the present invention, a general mild steel having a thickness of 0.504 mm and a width of 1235 mm is subjected to temper rolling at a sheeting speed of 700 prm, and vibration sensors provided on small-diameter rolls before and after the temper rolling mill. Used to measure vibration. The FFT frequency analysis result in one of the small diameter rolls is shown on the upper side of FIG. In this small-diameter roll, spectrum peaks were observed in the fundamental frequency (f) 61 Hz and frequency bands (121 Hz, 182 Hz, and 243 Hz) that are integral multiples of f. Of these peaks, the spectrum value at 243 Hz was determined to be larger than the set threshold value. Thereby, it was determined that an abnormality due to deterioration occurred in the bearing of the small-diameter roll.

  The small diameter roll in which the abnormality was detected was replaced with a new small diameter roll together with the bearing, and the same experiment was performed. The FFT frequency analysis result after replacement is shown in the lower side of FIG. By exchanging the small-diameter roll, the fundamental frequency and the peak in the frequency band of n times disappeared, and the abnormal vibration derived from the small-diameter roll could be eliminated.

DESCRIPTION OF SYMBOLS 1 Vibration sensor 2 Small diameter roll 3 Calculation apparatus 4 Data processing part 5 Data storage part 6, 7, 8 Processing apparatus 9 Steel plate 11 Rolling mill

Claims (2)

A vibration signal collecting step for collecting vibration signals detected by at least one small-diameter roll among small-diameter rolls provided on the entry side or the exit side of the rolling mill;
FFT frequency analysis step of performing frequency analysis of the fast Fourier transform method of the collected vibration signal and obtaining a frequency component and its spectrum value included in the vibration signal;
From the result of the frequency analysis, the peak of the fundamental frequency derived from the deterioration of the bearing of the small-diameter roll, and the peak in the frequency band of n times (n is a positive integer of 2 or more) of the fundamental frequency generated periodically . And detecting that the small-diameter roll has a bearing abnormality when any of the peak spectral values exceeds a preset threshold value. A vibration sensor that is attached to at least one small-diameter roll among the small-diameter rolls provided on the entry side or the exit side of the rolling mill and collects vibration signals;
The frequency analysis of the fast Fourier transform method is performed on the vibration signal from the vibration sensor, the frequency component included in the vibration signal and the spectrum value thereof are obtained, the peak of the fundamental frequency and the periodicity derived from the deterioration of the bearing of the small diameter roll When a peak in a frequency band of n times (n is a positive integer greater than or equal to 2) of the fundamental frequency generated in (1) is extracted and one of the peak spectral values exceeds a preset threshold value, A bearing deterioration detecting device for a small-diameter roll, comprising: an arithmetic unit that determines that the bearing of the small-diameter roll is abnormal.

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