KR102416964B1 - System for prediction of damage and life of chain of large bucket elevator for charging of fine ore into 3finex fluidized furnace - Google Patents

Abstract

An embodiment of the present invention relates to a diagnostic system for a bucket elevator including a sprocket, a conveyor chain rotating in conjunction with rotation of the sprocket, and a plurality of buckets attached to the conveyor chain, and a method thereof. The diagnostic system for the bucket elevator may comprise: at least one vibration sensor disposed on a driving shaft rotating the sprocket; and a monitoring device obtaining an impact cycle of each of a plurality of chain links constituting the conveyor chain by analyzing vibration data obtained through the at least one vibration sensor, and diagnosing whether each chain link is damaged based on the impact cycle of each of the plurality of chain links.

Description

SYSTEM FOR PREDICTION OF DAMAGE AND LIFE OF CHAIN OF LARGE BUCKET ELEVATOR FOR CHARGING OF FINE ORE INTO 3FINEX FLUIDIZED FURNACE}

The present disclosure relates to a chain diagnosis system for a bucket elevator and a method therefor, and more particularly, to a large-scale for charging spectroscopy into a flow path in a molten iron manufacturing facility for manufacturing molten iron using the FINEX method. It relates to a system and method for diagnosing chain damage of a bucket elevator and predicting its lifespan.

Molten iron manufacturing facilities, also known as FINEX, are facilities for manufacturing molten iron by directly using spectral iron ore, and include a multi-stage flow furnace, compaction facility, and a melting furnace connected thereto. Spectroscopy and auxiliary raw materials at room temperature are reduced by sequentially passing through multi-stage flow paths. The reduced iron produced in this way is compressed into a compacted material through a compaction facility and charged into a melting furnace, and the reduced iron ore is melted in the melting furnace to manufacture molten iron.

In such a molten iron manufacturing facility, a bucket elevator is used as a transfer device for charging the spectroscopy into the flow path. A bucket elevator is a machine for vertically transporting materials, such as spectroscopic, to an upper part, and transports the material by rotating a chain to which a bucket is attached.

The bucket elevator used in the molten iron manufacturing facility is a large, high-load facility with an approximate vertical height of 60 m and an operating rate of 90% or more. Therefore, damage to the chain of the bucket elevator may cause production loss, and in serious cases, a hazardous situation.

However, in the bucket elevator manual provided by the supplier, only the chain replacement criteria (for example, the degree of chain wear) are uniformly specified. There is a difficult problem.

An object to be solved through the embodiment is to provide a bucket elevator diagnostic system and method capable of quantitatively predicting whether or not the chain is damaged and the lifespan of a bucket elevator operating with a large high-load facility such as a molten iron manufacturing facility.

Diagnosis of a bucket elevator including a sprocket, a conveyor chain rotating in association with the rotation of the sprocket, and a plurality of buckets attached to the conveyor chain according to an embodiment for solving the above problems The system obtains an impact period of each of a plurality of chain links constituting the conveyor chain by analyzing vibration data obtained through at least one vibration sensor disposed on a drive shaft rotating the sprocket, and the at least one vibration sensor and a monitoring device for diagnosing whether each chain link is damaged based on an impact period of each of the plurality of chain links.

The monitoring device may analyze the vibration data to detect peak values, and acquire the shock period based on the occurrence time of the peak values.

The monitoring device may acquire the impact period based on peak values occurring within a first range based on an average impact period of the plurality of chain links among the peak values.

The bucket elevator diagnostic system may further include a rotation sensor for detecting a rotational position of the conveyor chain. The monitoring device may detect a rotation period of the conveyor chain through the rotation sensor, and detect the average impact period based on the number of the plurality of chain links and the rotation period.

The monitoring device may determine that the conveyor chain is damaged when an impact period exceeding a second range is detected based on the average impact period.

The monitoring device may perform filtering to remove a noise component from the vibration data acquired through the at least one vibration sensor, and detect the peak values from the vibration data from which the noise component is removed.

The at least one vibration sensor may include first and second vibration sensors respectively disposed on bearings coupled to both ends of the drive shaft. In this case, the monitoring device obtains first and second vibration data through the first and second vibration sensors, respectively, and obtains the peak values from the vibration data generated by multiplying the first and second vibration data can do.

The monitoring device analyzes the vibration data to obtain an average value of impact energy according to the collision with the sprocket for a predetermined period for the plurality of chain links, and substitutes the average value of the impact energy into a preset lifespan prediction model, The life of the conveyor chain can be predicted.

The monitoring device divides the vibration data obtained for every rotation period of the conveyor chain for each of the plurality of chain links, and measures kurtosis, root mean square (RMS) and standard deviation obtained from the vibration data of each chain link. Based on the calculation of the impact energy according to the friction between each chain link and the sprocket, it is possible to obtain the average value of the impact energy based on the impact energy calculated for each chain link for every rotation period of the conveyor chain.

The monitoring device may update the life expectancy prediction model through a regression analysis using an actual measured value obtained by actually measuring the degree of wear of the conveyor chain and the average value of the impact energy.

In addition, the diagnostic method of a bucket elevator including a sprocket, a conveyor chain rotating in association with the rotation of the sprocket, and a plurality of buckets attached to the conveyor chain according to an embodiment of the present invention acquiring vibration data through at least one vibration sensor disposed on a drive shaft rotating the sprocket, analyzing the vibration data obtained through the at least one vibration sensor to form the conveyor chain; It may include acquiring each impact period, and diagnosing whether each chain link is damaged based on the impact period of each of the plurality of chain links.

The acquiring of the shock period may include analyzing the vibration data to detect peak values, and acquiring the shock period based on the occurrence time of the peak values.

The peak values may be peak values generated within a first range based on an average impact period of the plurality of chain links.

The bucket elevator diagnosis method includes: detecting a rotation period of the conveyor chain through a rotation sensor that detects a rotation position of the conveyor chain; and the average impact period based on the number and rotation period of the plurality of chain links It may further include the step of detecting.

The diagnosing may include determining that the conveyor chain is damaged when an impact period exceeding a second range is detected based on the average impact period.

The bucket elevator diagnosis method may further include performing filtering to remove a noise component from the vibration data acquired through the at least one vibration sensor. In this case, the detecting of the peak values may include detecting the peak values from vibration data from which the noise component is removed.

The acquiring of the vibration data may include acquiring first and second vibration data respectively through first and second vibration sensors respectively disposed on bearings coupled to both ends of the drive shaft, and the first and multiplying the second vibration data to obtain the vibration data.

The bucket elevator diagnosis method includes: analyzing the vibration data to obtain an average value of shock energy according to collision with the sprocket for a predetermined period for the plurality of chain links; It may further include the step of predicting the life of the conveyor chain by substituting it.

The step of obtaining the average value of the impact energy includes dividing the vibration data obtained for every rotation period of the conveyor chain for each of the plurality of chain links, kurtosis obtained from the vibration data of each chain link, and root mean (RMS) square) and calculating the impact energy according to friction between each chain link and the sprocket based on the standard deviation, and the impact energy based on the impact energy calculated for each chain link in every rotation period of the conveyor chain It may include obtaining an average value.

The bucket elevator diagnosis method may further include updating the life expectancy prediction model through a regression analysis using an actual measured value obtained by actually measuring the degree of wear of the conveyor chain and the average value of the impact energy.

According to the embodiment, it is possible to quantitatively analyze the damage and lifespan of a chain in a bucket elevator operating with a large high-load facility, such as a molten iron manufacturing facility, so that it is possible to predict and prepare for a dangerous situation due to chain damage in the bucket elevator in advance. .

1 shows an example of a molten iron manufacturing facility to which a bucket elevator diagnostic system according to an embodiment of the present invention is applied.
2 shows an example of a bucket elevator to which a bucket elevator diagnosis system according to an embodiment of the present invention is applied.
3 shows a part of a conveyor chain constituting the bucket elevator of FIG. 2 .
FIG. 4 shows an example of a driving device for driving the bucket elevator of FIG. 2 .
5 schematically shows a bucket elevator diagnostic system according to an embodiment of the present invention.
6 illustrates a bucket elevator diagnosis method of a bucket elevator diagnosis system according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those of ordinary skill in the art to which the present invention pertains can easily implement them. The present invention may be embodied in several different forms and is not limited to the embodiments described herein.

In order to clearly describe the embodiment of the present invention, parts irrelevant to the description are omitted, and the same reference numerals are assigned to the same or similar elements throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. .

Hereinafter, a bucket elevator diagnostic system and method according to an embodiment will be described in detail with reference to necessary drawings.

1 shows an example of a molten irons manufacturing facility to which a bucket elevator diagnostic system according to an embodiment of the present invention is applied, and shows a facility for manufacturing molten iron by a FINEX method.

Referring to FIG. 1 , a molten iron manufacturing facility 1 includes a plurality of fluidized furnaces 20 (or fluidized furnaces) for manufacturing reduced iron by reducing fine ore-type iron ore (hereinafter, referred to as “spectroscopy”). It includes a reduction furnace (fluidized reduction furnace), a compacting device 22 for producing compacted material by pressing reduced iron, and a melting furnace 24 for producing molten iron by melting compacted reduced iron.

After the moisture stored in the hopper 10 is removed by the dryer 12 , it is transferred to the loading device 16 through the unloading device 14 , and into the flow path 20 by the loading device 16 . is loaded In the charging device 16, the flow path 20 flows the spectroscopy from the inside. The spectroscopy is reduced by contact with the high-temperature reducing gas supplied from the melting furnace 24 while sequentially passing through the flow furnace 20 arranged in multiple stages.

After the reduced iron discharged from the flow furnace 20 is compressed into a compacted material by the compacting device 22 , it is continuously charged into the melting furnace 24 . In addition, powdered ordinary coal (coal), which is a fuel, is continuously supplied to the melting furnace 24 , and oxygen is blown into the melting furnace 24 through a tuyere (not shown) formed on the outer wall of the melting furnace 24 . The coal supplied into the melting furnace 24 is combusted by reaction with oxygen to generate a high-temperature reducing gas. The reducing gas generated in this way is in contact with the compacted material while rising inside the melting furnace 24, and the compacted material that has received heat by contact with the high-temperature reducing gas is melted into molten iron. The reducing gas discharged from the melting furnace 24 is transferred to a cyclone (not shown) through the discharge pipe 30 connected to the gas outlet, and is supplied to the flow furnace 20 through the cyclone.

A bucket elevator may be used as the unloading device 14 for charging the spectroscopy into the flow path 20 in the molten iron manufacturing facility.

2 shows an example of a bucket elevator to which a bucket elevator diagnosis system according to an embodiment of the present invention is applied. In addition, FIG. 3 shows a part of a conveyor chain constituting the bucket elevator of FIG. 2 , and FIG. 4 shows an example of a driving device for driving the bucket elevator of FIG. 2 .

Referring to FIG. 2 , the bucket elevator 14 includes a conveyor chain 141 , a plurality of buckets 142 , a sprocket 143 , a driving device (see reference numeral 144 in FIG. 4 ), and a conveyor chain 141 . , a bucket 142 , a sprocket 143 , and a housing 140 accommodating the driving device in the internal space.

The plurality of buckets 142 are mounted to be spaced apart from each other by a predetermined interval on the conveyor chain 141, and load and transport the unloading object, that is, the spectrometer. The conveyor chain 141 rotates in association with the rotation of the sprocket 143 and moves the plurality of buckets 142 .

Referring to FIG. 3 , the conveyor chain 141 may include a plurality of inner links 210 and outer links 220 . A bucket 142 is attached to the outer link 220 , and the inner link 210 may connect the outer links 220 to each other. The inner link 210 and the outer link 220 may be coupled to each other by inserting pins 201 into the holes formed in the links 210 and 220 . Each pin 201 may have an outer surface surrounded by a bush 202 . In addition, the bush 202 may be wrapped around the outer surface by a rotatable roller (not shown).

The sprocket 143 is rotated by the driving device to rotate the conveyor chain 141 .

Referring to FIG. 4 , the driving device 144 includes a driving shaft 301 , at least one driving motor 302a , 302b , a plurality of bearings 303a , 303b , and supporting structures 304a and 304b for supporting them. do.

The driving shaft 301 is inserted and coupled to the center of the sprocket 143, and rotates by receiving driving force from at least one driving motor 302a, 302b. To this end, both ends of the drive shaft 301 are rotatably supported by bearings 303a and 303b. When the driving shaft 301 rotates by the driving force transmitted from the driving motors 302a and 302b, the sprocket 143 coupled to the outer circumferential surface of the driving shaft 301 also rotates, and thus the conveyor chain 141 also rotates.

As the conveyor chain 141 rotates, the inner diameter of the bush 202 and the outer diameter of the pin 201 inserted therein continuously cause friction, which causes the outer diameter of the pin 201 or the inner diameter of the bush 202 to be worn. may be damaged.

The bucket elevator 14 used to charge the spectroscopy into the flow path 20 is a large, high-load facility with a vertical height of approximately 60 m and an operating rate of 90% or more. In an environment where the bucket elevator operates as a large, high-load facility, such as in a molten iron manufacturing facility, damage to the chain of the bucket elevator may cause production loss, and in severe cases, a hazardous situation.

Therefore, in the embodiment of the present invention, a vibration signal generated by friction between the conveyor chain 141 and the sprocket 143 of the bucket elevator 14 is detected for stable operation of the bucket elevator 14, and the detected vibration signal It provides a bucket elevator diagnostic system that analyzes the damage diagnosis and life prediction of the conveyor chain 141.

5 schematically shows a bucket elevator diagnostic system according to an embodiment of the present invention.

Referring to FIG. 4 , the bucket elevator diagnostic system 400 according to an embodiment of the present invention may include a plurality of vibration sensors 401a and 401b , a rotational position sensor 402 , and a monitoring device 410 .

A plurality of vibration sensors (401a, 401b) are respectively coupled to the bearings (303a, 303b) coupled to both ends of the drive shaft (301), respectively, as shown in Fig. 4, the corresponding bearings (303a, 303b) It is possible to detect a vibration signal transmitted through the

The rotation sensor 402 is a sensor for detecting the rotation position of the conveyor chain 141 , and a magnetic sensor operating in a magnetoresistance type may be used. The magnetic sensor 402 may detect the rotational position of the conveyor chain 141 by detecting the position of the ferromagnetic material attached to the specific bucket 142 . That is, the bucket 142 to which the ferromagnetic material is attached repeatedly passes a position close to the magnetic sensor 402 due to the rotation of the conveyor chain 141, and the magnetic sensor 402 is the bucket 142 to which the ferromagnetic material is attached. Whenever it is close to , it is detected and a signal (hereinafter, referred to as a 'rotational position sensor') is output. This rotation position signal may be used to identify the rotation period of the conveyor chain 141 in the monitoring device 410 to be described later.

The vibration sensors 401a and 402b or the rotation sensor 402 may include a wireless communication function, and may transmit the detected vibration signal or rotational position signal to the monitoring device 410 in a wireless communication method.

Monitoring device 410, based on the vibration signals received from the vibration sensors (401a, 401b), each chain link constituting the conveyor chain 141 (reference numeral 220 in Fig. 3, or the inner link) (refer to 210)) and extracting an impact period, based on the extracted impact period, it is possible to detect whether each chain link is damaged. The monitoring device 410 estimates the impact energy (or friction energy) corresponding to each chain link constituting the conveyor chain 141 based on the vibration signals received from the vibration sensors 401a and 401b, and the estimated It is also possible to predict the life of each chain link based on the impact energy.

To this end, the monitoring device 410 may include a vibration data acquisition unit 411 , a failure diagnosis unit 412 , and a life expectancy prediction unit 413 .

The vibration data acquisition unit 411 may acquire vibration data corresponding to each of the vibration sensors 401a and 401b by sampling the vibration signals received from the vibration sensors 401a and 401b. When a vibration signal is received in the form of digital data from each of the vibration sensors 401a and 401b, the sampling process may be omitted.

The vibration data acquisition unit 411 also detects the rotation period of the conveyor chain 141 based on the rotation position signal received from the rotation sensor 402, and distinguishes the vibration data for each rotation order according to the detected rotation period. A trigger signal can be generated. That is, the vibration data acquisition unit 411 generates a trigger signal for every rotation period of the conveyor chain 141 based on the received rotation position signal, thereby diagnosing the failure in the failure diagnosis unit 412 and the life prediction unit 413 to be described later. It makes it easy to identify vibration data corresponding to one rotation period.

The failure diagnosis unit 412 analyzes the frequency characteristics of the vibration data acquired by the vibration data acquisition unit 411, extracts the shock cycle of the conveyor chain 141 as a characteristic factor, and based on this, the conveyor chain 141 It is possible to diagnose whether or not each chain link composing is damaged. To this end, the failure diagnosis unit 412 may include a filtering unit 501 , a representative value acquisition unit 502 , an impact period detection unit 503 , and a diagnosis unit 504 .

When the vibration data acquired through the vibration sensors 401a and 401b are input, the filtering unit 501 may remove a noise component from the vibration data through filtering. The vibration signal detected by the vibration sensors 401a and 401b includes a vibration component in a low frequency band caused by shaking of mechanical elements of the bucket elevator 14, a vibration component in a high frequency band caused by bearings, gear components, etc. may include Accordingly, the filtering unit 501 filters noise components other than vibration components generated by the impact caused by friction between the conveyor chain 141 and the sprocket 143 from the vibration data through a band pass filter. can do. The pass band of the band pass filter used herein may vary according to design specifications of the bucket elevator 14 . For example, the pass band of the band pass filter used in the filtering unit 501 may be a frequency band of 115 Hz to 340 Hz.

The filtering unit 501 may additionally perform pre-processing such as filtering through a low pass filter and absolute value conversion on vibration data from which a noise component has been removed by the band pass filter. Vibration data that has been pre-processed by the filtering unit 501 may be output to the representative value obtaining unit 502 .

When the vibration data preprocessed by the filtering unit 501 are received, the representative value obtaining unit 502 may obtain a representative value of the vibration data. For example, the representative value obtaining unit 502 may obtain representative vibration data representing the two vibration data by multiplying two vibration data obtained through different vibration sensors 401a and 401b. Also, for example, the representative value obtaining unit 502 may obtain representative vibration data representing the two vibration data by taking an average or maximum value between the two vibration data.

The representative vibration data obtained by the representative value obtaining unit 502 may be transmitted to the shock period detecting unit 503 in order to extract a characteristic factor (impact period).

The tension applied to the conveyor chain 141 may vary depending on its location due to a design deviation of the bucket elevator 14 , a concentration of light in the bucket 142 , and the like. For example, in the case where a drift phenomenon occurs while the light is loaded on the bucket 142, the tension applied to the left and right sides of the conveyor chain 141 based on the traveling direction of the single chain link may be different from each other. . Therefore, even with a single chain link, the friction energy with the sprocket 143 on the left side and the friction energy with the sprocket 143 on the right side may be different from each other, and thus the vibration output through the vibration sensors 401a and 401b It can cause deviations between the signals. In particular, when the tension is excessive, the friction with the sprocket 143 on the left or right side of the chain link is insignificant, so it may be difficult to distinguish between the peak signal and the noise signal generated due to friction. Therefore, in this embodiment, as described above, vibration data is obtained through two vibration sensors 401a and 401b disposed on both sides of the drive shaft 301, and then, representative vibration representing these vibration data is extracted when the subsequent characteristic factor is extracted. How to use data. However, the embodiment of the present invention is not limited thereto, and in another embodiment, the vibration sensor is disposed only on one side of the drive shaft 301, and characteristic factor extraction described later may be performed using vibration data obtained through this. have.

When the representative vibration data is input from the representative value obtaining unit 502 , the shock period detection unit 503 may detect the shock period for each chain link therefrom. That is, the impact period detector 503 may analyze the representative vibration data to detect peak values greater than or equal to a predetermined value, and may obtain an impact period corresponding to each chain link based on the occurrence time of each peak value. The peak values detected at this time correspond to the vibration component generated by friction between each chain link and the sprocket 143, and the impact period of each chain link is the point at which the peak value is generated by the previous chain link of the corresponding chain link. It can correspond to the time interval between the time point at which the peak value is generated by the corresponding chain link.

The impact cycle detection unit 503 detects the rotation cycle of the conveyor chain 141 based on the rotation position signal of the rotation sensor 402 in the process of detecting the impact cycle, and is predetermined based on the average impact cycle calculated therefrom. The shock cycle can be detected using only the peak values that occur within the range (approximately, ±15%). Here, the average impact period may be calculated by dividing one rotation period of the conveyor chain 141 by the number of chain links.

As described above, when the impact period of each chain link is detected by the impact period detection unit 503 , the diagnosis unit 504 may diagnose whether each chain link is damaged based thereon. 2, the pin 201 coupling the chain links 210 and 220 and the bush 202 into which the pin 201 is inserted continuously cause friction while the conveyor chain 141 rotates, Wear and tear may occur during this process. Wear of the inner diameter of the pin 201 or bush 202 loosens the coupling between the chain links 210 , 220 , and consequently changes the friction period between the chain links 210 , 220 and the sprocket 143 . Accordingly, when an impact period outside a predetermined range is detected based on the average impact period of the chain links constituting the conveyor chain 141 , the diagnosis unit 504 may diagnose that damage has occurred in the corresponding chain link. For example, the diagnosis unit 504 may detect an impact cycle exceeding +4% based on the average impact cycle as an abnormal signal, determine that damage has occurred in the corresponding chain link, and output a caution signal. Also, for example, when an impact cycle exceeding +5% based on the average impact cycle is detected, the diagnosis unit 504 determines that damage to the corresponding chain link is serious, and outputs a warning signal to warn of a dangerous situation. You may. Here, the reference range for determining the impact period as a normal signal or an abnormal signal may be changed according to the usage time or lifespan of the conveyor chain 141 .

The life prediction unit 413 analyzes the frequency characteristics of the vibration data obtained by the vibration data acquisition unit 411 and extracts the impact energy (or friction energy) for each chain link of the conveyor chain 141 as a characteristic factor, , it is possible to predict the lifespan of each chain link constituting the conveyor chain 141 based on this. To this end, the life prediction unit 413 may include a filtering unit 511 , a representative value acquisition unit 512 , an impact energy detection unit 513 , and a prediction unit 514 .

The filtering unit 511 may remove a noise component from the vibration data acquired through the vibration sensors 401a and 401b through the band pass filter. In the vibration data obtained through the vibration sensors 401a and 401b, a vibration component in a low frequency band generated due to shaking of mechanical elements of the bucket elevator 14, a vibration component in a high frequency band generated due to a bearing, a gear component, etc. etc. may be included. Unlike the failure diagnosis unit 412, which acquires an impact period by detecting an impact point at which the peak value occurs the greatest, the life prediction unit 413 has an impact energy ( or frictional energy). Accordingly, the pass band of the band pass filter included in the filtering unit 511 may be set differently from the pass band of the band pass filter included in the filtering unit 501 . For example, the pass band of the band pass filter included in the filtering unit 511 may be set to 1150 Hz to 4000 Hz.

The vibration data filtered by the filtering unit 511 may be output to the representative value obtaining unit 512 after additional pre-processing such as absolute value conversion.

The representative value acquisition unit 512 may obtain representative vibration data representing these vibration data when the two vibration data obtained through the vibration sensors 401a and 401b are pre-processed by the filtering unit 511 and then input. have. For example, the representative value obtaining unit 512 may obtain representative vibration data representing the two vibration data by multiplying the two input vibration data. Also, for example, the representative value obtaining unit 512 may obtain representative vibration data representing the two vibration data by taking an average or maximum value between the two input vibration data.

On the other hand, as discussed in the description of the failure diagnosis unit 412, in this embodiment, vibration data is detected through two vibration sensors 401a and 401b disposed on both sides of the drive shaft 301, and then obtained from Although the impact energy of each channel link is obtained using the representative vibration data, the embodiment of the present invention is not limited thereto. In another embodiment, the vibration sensor may be disposed on only one side of the drive shaft 301 , and the impact energy of each channel link may be obtained by using vibration data obtained through this.

When the representative vibration data is input from the representative value obtaining unit 512 , the impact energy detecting unit 513 may detect the impact energy for each chain link therefrom.

The impact energy detector 513 divides the representative vibration data into vibration data corresponding to each channel link in order to calculate the impact energy, ie, friction energy, for each chain link. In addition, kurtosis, root mean square (RMS), and standard deviation may be obtained by analyzing vibration data of each channel link, and an impact energy (friction energy) of each channel link may be calculated. For example, for the n-th channel link constituting the conveyor chain 141, Equation 1 below may calculate the impact energy (L _n ).

[Equation 1]

L _n = (kurtosis × standard deviation) ÷ RMS ²

The impact energy detection unit 513 acquires the impact energy of each chain link in the above-described manner for every rotation period of the conveyor chain 141, and uses the impact energy of each chain link obtained for a predetermined period to control the conveyor chain 141. It is possible to obtain an average value of the impact energy of the constituting channel links.

First, the impact energy detecting unit 513 may obtain an average impact energy value (S _m ) for all N chain links constituting the conveyor chain 141 as shown in Equation 2 below at every rotation period. .

[Equation 2]

S _m = (L ₁ + L ₂ + … + L _N )/N

The impact energy detection unit 513 also configures the conveyor chain 141 based on the average impact energy value (S _m ) obtained through Equation 2 above while the conveyor chain 141 rotates a preset number of times (M). The average value (P) of the impact energy of the channel links can be finally calculated as in Equation 3 below.

[Equation 3]

P = (S ₁ + S ₂ + … + S _M )/M

The period in which the impact energy is collected in the impact energy detection unit 513 to obtain the average impact energy P, that is, the number of revolutions of the conveyor chain 141 can be set based on the number of teeth of the sprocket 143 have.

When the average value P of the impact energy of the conveyor chain 141 for a predetermined period is obtained by the impact energy detection unit 513, the prediction unit 514 substitutes it into the life prediction model to predict the life of the conveyor chain 141. can Here, the life prediction model is an initial model determined according to the design specifications (size, weight, friction area, operating speed, etc.) of the bucket elevator 14, and thereafter, while the bucket elevator 14 is operated, it is to be updated by continuous learning. can That is, the prediction unit 514 performs regression analysis using an actual measured value obtained by actually measuring the degree of wear of the conveyor chain 141 and a lifespan factor (impact energy average value (P)) substituted into the lifespan prediction model for life prediction. Through this, the lifespan prediction model can be continuously updated.

The prediction unit 514 may periodically predict the lifespan of the conveyor chain 141 using the above-described method, and may graph the prediction result and display it through a display device (not shown). Accordingly, the manager may perform facility management of the conveyor chain 141 with reference to the life prediction graph provided by the prediction unit 514 .

The monitoring device 410 of the aforementioned bucket elevator diagnostic system 400 may be implemented by a processor implemented with one or more central processing units (CPUs) or other chipsets, microprocessors, and the like.

6 illustrates a bucket elevator diagnosis method of the bucket elevator diagnosis system 400 according to an embodiment of the present invention. The diagnostic method of FIG. 6 may be performed by the monitoring device 410 of the bucket elevator diagnostic system 400 described above with reference to FIG. 4 .

Referring to FIG. 6 , the monitoring device 410 of the bucket elevator diagnostic system 400 according to an embodiment of the present invention includes vibration sensors disposed at both ends of the drive shaft 301 for rotating the conveyor chain 141 . Vibration signals are continuously detected through steps 401a and 401b (S10).

In addition, the monitoring device 410 obtains vibration data to be used for detecting the characteristic factor by performing a pre-processing process on the vibration signals detected through the vibration sensors 401a and 401b ( S11 ).

For example, the monitoring device 410 may obtain vibration data corresponding to each of the vibration signals by sampling vibration signals detected through the vibration sensors 401a and 401b. Then, the monitoring device 410 removes noise components from the vibration data through band pass filtering, absolute value conversion, low-pass filtering, etc., and returns representative vibration data representing the vibration data from which the noise component has been removed to the conveyor chain 141 . ) can be obtained as vibration data used to detect the impact period.

Also, for example, the monitoring device 410 samples vibration signals detected through the vibration sensors 401a and 401b to obtain vibration data corresponding to each of the vibration signals, and includes them through a band pass filter. noise components can be removed. Then, the monitoring device 410 obtains the representative vibration data of the vibration data from which the noise components are removed, and converts it back to an absolute value to obtain the vibration data used to detect the impact energy of the conveyor chain 141 . .

Meanwhile, in this embodiment, as described above, vibration data is acquired through two vibration sensors 401a and 401b disposed on both sides of the drive shaft 301, and then one representative vibration data representing them is acquired in the pre-processing process. Thus, the method used for extracting the characteristic factor is used, but the embodiment of the present invention is not limited thereto. In another embodiment, the vibration sensor may be disposed on only one side of the driving shaft 301 , and only one vibration data may be obtained through this and used for extracting characteristic factors.

When vibration data to be used for characteristic factor extraction is obtained through the pre-processing of step S11, the monitoring device 410 analyzes it to obtain characteristic factors corresponding to the vibration characteristics of the conveyor chain 141 (S12).

In the step S12, the monitoring device 410 analyzes the vibration data obtained through the pre-processing of the step S11 to detect peak values above a predetermined value, and the conveyor chain 141 based on the occurrence time of each peak value. The impact period corresponding to each chain link constituting it can be obtained as a characteristic factor.

In addition, in the step S12, the monitoring device 410 divides the vibration data obtained through the pre-processing of the step S11 into vibration data corresponding to each channel link, the kurtosis obtained from the vibration data of each channel link, Based on the RMS and standard deviation, the impact energy of each channel link may be obtained as a characteristic factor.

As the characteristic factors, that is, the impact period and impact energy of each chain link are obtained through the step S12, the monitoring device 410 uses them to diagnose whether each chain link constituting the conveyor chain 141 has a failure, and (S13), the life of the conveyor chain 141 is predicted (S14).

In the step S13, the monitoring device 410 determines that damage has occurred in the corresponding channel link when an impact cycle out of a predetermined range set based on the average impact cycle of the chain links constituting the conveyor chain 141 is detected. can

In the step S14, the monitoring device 410 obtains an average value of the impact energy of the channel links constituting the conveyor chain 141 based on the impact energy of each chain link obtained for a predetermined period, and uses this as a preset life prediction model By substituting it, the lifespan of the conveyor chain 141 can be predicted.

The drawings and detailed description of the described invention referenced so far are merely exemplary of the present invention, which are only used for the purpose of explaining the present invention, and are used to limit the meaning or limit the scope of the present invention described in the claims. it is not Therefore, those of ordinary skill in the art can easily select from it and replace it. In addition, those skilled in the art may omit some of the components described herein without degrading performance or add components to improve performance. In addition, those skilled in the art may change the order of the method steps described herein according to the process environment or equipment. Accordingly, the scope of the present invention should be determined by the claims and their equivalents rather than the described embodiments.

14: Bucket Elevator
140: housing
141: conveyor chain
142: bucket
143: sprocket
144: drive device
201: pin
202: Bush
210, 220: chain link
301: drive shaft
302a, 302b: drive motor
303a, 303b: bearing
304a, 304b: support structure
400: bucket elevator diagnostic system
401a, 401b: vibration sensor
402: rotation sensor
410: monitoring device
411: vibration data acquisition unit
412: fault diagnosis unit
413: life prediction unit
501: filtering unit
502: representative value acquisition unit
503: shock cycle detection unit
504: diagnostic unit
511: filtering unit
512: representative value acquisition unit
513: impact energy detection unit
514: prediction unit

Claims (20)

A diagnostic system for a bucket elevator comprising a sprocket, a conveyor chain rotating in association with rotation of the sprocket, and a plurality of buckets attached to the conveyor chain, the system comprising:
at least one vibration sensor disposed on a drive shaft for rotating the sprocket, and
Analyze the vibration data obtained through the at least one vibration sensor to obtain an impact period of each of a plurality of chain links constituting the conveyor chain, and damage of each chain link based on the impact period of each of the plurality of chain links A monitoring device for diagnosing whether
The monitoring device analyzes the vibration data to detect peak values, and acquires the shock period based on the occurrence time of the peak values,
The monitoring device performs filtering to remove a noise component from the vibration data acquired through the at least one vibration sensor, and detects the peak values from the vibration data from which the noise component is removed. delete According to claim 1,
The monitoring device is configured to acquire the impact period based on peak values occurring within a first range based on an average impact period of the plurality of chain links among the peak values. 4. The method of claim 3,
Further comprising a rotation sensor for detecting the rotation position of the conveyor chain,
The monitoring device detects a rotation period of the conveyor chain through the rotation sensor, and detects the average impact period based on the number of the plurality of chain links and the rotation period. 4. The method of claim 3,
The monitoring device determines that the conveyor chain is damaged when an impact period exceeding a second range is detected based on the average impact period. delete According to claim 1,
The at least one vibration sensor includes first and second vibration sensors respectively disposed on bearings coupled to both ends of the drive shaft,
The monitoring device obtains first and second vibration data through the first and second vibration sensors, respectively, and obtains the peak values from the vibration data generated by multiplying the first and second vibration data. Elevator diagnostic system. According to claim 1,
The monitoring device analyzes the vibration data to obtain an average value of impact energy according to the collision with the sprocket for a predetermined period for the plurality of chain links, and substitutes the average value of the impact energy into a preset lifespan prediction model to Bucket elevator diagnostic system to predict the life of conveyor chains. 9. The method of claim 8,
The monitoring device is
The vibration data obtained for every rotation period of the conveyor chain is divided for each of the plurality of chain links, and each chain link is based on a kurtosis, a root mean square (RMS) and a standard deviation obtained from the vibration data of each chain link. A bucket elevator diagnostic system for calculating an impact energy according to friction between the and the sprocket, and obtaining the average value of the impact energy based on the impact energy calculated for each chain link for every rotation period of the conveyor chain. 10. The method of claim 9,
The monitoring device is configured to update the life expectancy model through regression analysis using an actual measured value obtained by actually measuring the degree of wear of the conveyor chain and the average value of the impact energy, a bucket elevator diagnostic system. A diagnostic method of a bucket elevator comprising a sprocket, a conveyor chain rotating in association with rotation of the sprocket, and a plurality of buckets attached to the conveyor chain, the method comprising:
acquiring vibration data through at least one vibration sensor disposed on a drive shaft that rotates the sprocket;
analyzing the vibration data obtained through the at least one vibration sensor to obtain an impact period of each of a plurality of chain links constituting the conveyor chain; and
diagnosing whether each chain link is damaged based on the impact period of each of the plurality of chain links;
The step of obtaining the shock cycle comprises:
performing filtering to remove a noise component from the vibration data acquired through the at least one vibration sensor;
detecting peak values from the vibration data from which the noise component has been removed, and
and acquiring the impact period based on the time of occurrence of the peak values. delete 12. The method of claim 11,
The peak values are peak values occurring within a first range based on an average impact period of the plurality of chain links. 14. The method of claim 13,
detecting a rotation period of the conveyor chain through a rotation sensor that detects a rotation position of the conveyor chain; and
The bucket elevator diagnostic method further comprising the step of detecting the average impact period based on the number of the plurality of chain links and the rotation period. 14. The method of claim 13,
The diagnosing step is
and determining that the conveyor chain is damaged when an impact period exceeding a second range is detected based on the average impact period. delete 12. The method of claim 11,
The step of acquiring the vibration data includes:
acquiring first and second vibration data, respectively, through first and second vibration sensors respectively disposed on bearings coupled to both ends of the drive shaft, and
and obtaining the vibration data by multiplying the first and second vibration data. 12. The method of claim 11,
analyzing the vibration data to obtain an average value of impact energy according to the collision with the sprocket for a predetermined period for the plurality of chain links; and
The bucket elevator diagnosis method further comprising the step of predicting the life of the conveyor chain by substituting the average value of the impact energy into a preset life prediction model. 19. The method of claim 18,
The step of obtaining the average value of the impact energy comprises:
dividing the vibration data acquired for every rotation period of the conveyor chain for each of the plurality of chain links;
Calculating impact energy according to friction between each chain link and the sprocket based on kurtosis, root mean square (RMS) and standard deviation obtained from vibration data of each chain link; and
and obtaining the average value of the impact energy based on the calculated impact energy for each chain link for every rotation period of the conveyor chain. 20. The method of claim 19,
Bucket elevator diagnosis method further comprising the step of updating the life prediction model through regression analysis using the measured value obtained by actually measuring the degree of wear of the conveyor chain and the average value of the impact energy.

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