CN113074924A - Abnormal acoustic diagnosis system and method for belt conveyor carrier roller - Google Patents
Abnormal acoustic diagnosis system and method for belt conveyor carrier roller Download PDFInfo
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- CN113074924A CN113074924A CN202110320834.0A CN202110320834A CN113074924A CN 113074924 A CN113074924 A CN 113074924A CN 202110320834 A CN202110320834 A CN 202110320834A CN 113074924 A CN113074924 A CN 113074924A
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- G01M13/00—Testing of machine parts
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- G01H—MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC OR INFRASONIC WAVES
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Abstract
The invention relates to an acoustic diagnosis system for abnormity of a carrier roller of a belt conveyor, which belongs to the technical field of acoustic application and comprises an inspection robot and a robot management platform, wherein the inspection robot inspects back and forth along the belt conveyor, and an acoustic diagnosis module, a processor module and a wireless communication module are arranged on the inspection robot; the acoustic diagnosis module is used for detecting the frequency and amplitude of the noise signal, forming a digital signal and sending the digital signal to the processor module; the processor module is used for calculating noise sharpness data according to the received digital signals, comparing the noise sharpness data with a sharpness threshold value, and sending an alarm signal if the noise sharpness data exceeds the sharpness threshold value; the alarm signal is sent to a base station arranged along the belt conveyor through the wireless communication module, and the base station is forwarded to the robot management platform; and the robot management platform sends out alarm information and records the alarm information.
Description
Technical Field
The invention belongs to the technical field of acoustic application, and relates to an acoustic diagnosis system and method for belt conveyor carrier roller abnormity.
Background
The belt conveyor has the characteristics of low operation cost, simple operation, high efficiency, long transport distance and the like, and is important bulk material transportation equipment. However, various accidents can occur and potential safety hazards exist in the operation process. Traditional long-range belt conveyor fault detection mainly relies on the manual work to patrol and examine, and work load is big and operational environment is dangerous. With the continuous improvement of communication and artificial intelligence technology, conditions are created for intelligent inspection, and the realization of intelligent inspection on a belt conveyor by utilizing inspection equipment to carry various sensors becomes an industrial research hotspot and is gradually popularized and applied.
The carrier rollers are important parts of the belt conveyor for bearing the rubber belt and materials conveyed on the rubber belt, and are arranged in a group at intervals of about 1.5 meters along the line, and one belt conveyor which is thousands of meters long has thousands of carrier rollers and is numerous. The roller fault mainly comes from the damage of the roller bearing, and the roller fault is mainly characterized by blocking in the early stage, namely the roller rotates unsmoothly along with the forward movement of the adhesive tape, rubs with the adhesive tape for a long time and generates abnormal sound at the same time. If the coal mine is not repaired all the time, local temperature rise is possibly too high, fire disasters can be caused when the coal and other still materials are conveyed, and gas explosion can be caused under the coal mine.
Because the bearing roller is numerous, can lead to the cost too high at sensors such as every group bearing roller installation temperature, consequently, carry on the adapter on the intelligence equipment of patrolling and examining, take non-contact mode real-time detection sound data, through the analysis to sound data, judge whether the bearing roller breaks down and be one of the important function that the intelligence was patrolled and examined the equipment.
Chinese patent CN205204106U proposes a belt conveyor carrier roller operation noise detection and damage prediction system, which adopts a method that when the amplitude of the actual noise spectrum curve exceeds the amplitude of the standard noise spectrum curve by 50%, a light fault early warning is sent out, and when the amplitude exceeds 70%, a heavy fault warning is sent out to diagnose the carrier roller fault. The dynamic research on the damage process of the carrier roller is not involved, the actual frequency spectrum curve amplitude is only set to be higher than two thresholds of 50% and 70% of the normal carrier roller (standard) frequency spectrum curve amplitude in a general mode, the frequency range where the amplitude is increased is not concerned, the condition that the actual noise loudness or sound pressure level is increased and the set threshold is exceeded can be understood as early warning or alarming, the criterion is not strict, and particularly early faults of the carrier roller cannot be judged.
Disclosure of Invention
In view of the above, the invention aims to provide an acoustic diagnosis system and an acoustic diagnosis method for roller abnormality of a belt conveyor, which are used for judging the roller fault condition of the belt conveyor by using an acoustic diagnosis technology and realizing online early warning and fault alarm of early roller faults.
In order to achieve the purpose, the invention provides the following technical scheme:
on one hand, the invention provides an acoustic diagnosis system for abnormity of a carrier roller of a belt conveyor, which comprises an inspection robot and a robot management platform, wherein the inspection robot inspects back and forth along the belt conveyor and is provided with an acoustic diagnosis module, a processor module and a wireless communication module; the acoustic diagnosis module is used for detecting the frequency and amplitude of the noise signal, forming a digital signal and sending the digital signal to the processor module; the processor module is used for calculating noise sharpness data according to the received digital signals, comparing the noise sharpness data with a sharpness threshold value, and sending an alarm signal if the noise sharpness data exceeds the sharpness threshold value; the alarm signal is sent to a base station arranged along the belt conveyor through the wireless communication module, and the base station is forwarded to the robot management platform; and the robot management platform sends out alarm information and records the alarm information.
Further, the acoustic diagnosis module comprises a sound pressure sensor and a sound encoder, wherein the sound pressure sensor converts the noise loudness signal into a voltage signal and sends the voltage signal to the sound encoder, and the sound encoder continuously extracts the frequency and the amplitude (loudness) of the noise signal to form sound waves represented by digital signals and sends the sound waves to the processor module.
Further, time information is contained in alarm information sent by the robot management platform, and the robot management platform calculates the position of the polling robot when sending the alarm through the time information so as to position the fault carrier roller.
Further, the processor module firstly performs FFT analysis on the noise signal to obtain a critical frequency band and a loudness spectrum, and then calculates noise sharpness data every 2 seconds according to the following formula:
where N' (Z) is the loudness spectrum over critical band Z, the integral of the loudness spectrum over the critical band is the loudness, g (Z) is the additional coefficient, Z is the critical band, and d (Z) is the critical band differential.
In another aspect, a method for acoustically diagnosing belt conveyor idler roller abnormalities comprises the following steps:
s1: the inspection robot moves back and forth along the belt conveyor for inspection, and noise signals of the carrier rollers are collected;
s2: converting the noise loudness signal into a voltage signal through a sound pressure sensor, sending the voltage signal into a sound coder, continuously extracting the frequency and amplitude (loudness) of the noise signal by the sound coder to form a sound wave represented by a digital signal, and sending the sound wave to a processor module;
s3: the processor carries out FFT analysis on the noise signal to obtain a critical frequency band and a loudness spectrum, noise sharpness data are calculated once every 2 seconds, if the sharpness exceeds a set threshold value, an alarm signal is sent to a base station arranged along the belt conveyor, and the alarm signal is forwarded to the robot management platform through the base station;
s4: the robot management platform sends alarm information to a human-computer interface after receiving the alarm signal and records the alarm information;
s5: and the robot management platform calculates the position of the fault carrier roller according to the time information recorded in the alarm information.
Further, the processor module calculates the noise sharpness data by:
where N' (Z) is the loudness spectrum over critical band Z, the integral of the loudness spectrum over the critical band is the loudness, g (Z) is the additional coefficient, Z is the critical band, and d (Z) is the critical band differential.
The invention has the beneficial effects that: research shows that the normal carrier roller noise frequency range is mainly below 4000Hz, wherein the amplitude below 500Hz is larger. The frequency range of noise emitted by the fault carrier roller is 0-7000 Hz, wherein the amplitude in the range of 4000-6500 Hz is obviously increased.
Idler failure is mostly idler bearing failure. The carrier roller can still rotate when the carrier roller bearing is in the early failure stage, only the rotating speed becomes low, sliding friction exists in part, and the frequency spectrum curve is not obviously different from that of a normal carrier roller. Along with the aggravation of the fault degree of the bearing, the rotating speed of the carrier roller is reduced more and more until the carrier roller stops completely, the friction force between the carrier roller and the adhesive tape is changed from rolling friction to sliding friction more and more, and in the process, the frequency range in which the amplitude of the frequency spectrum curve is increased remarkably moves more and more in the high-frequency direction until the frequency range is 4000-6500 Hz.
Therefore, in the prior art, the error of diagnosis by adopting a frequency spectrum curve is very large, the fault carrier roller can generate sharper noise during operation, the sharpness degree of the sharper noise is related to the severity degree of the fault, and the carrier roller fault state and the severity degree can be accurately reflected by detecting the sound sharpness degree of the carrier roller.
The invention also has the following beneficial effects:
1) the bearing roller fault can be diagnosed by using the sharpness index in the sound quality index, so that not only the bearing roller which cannot rotate but also the fault bearing roller which has a bearing fault but can rotate can be diagnosed.
2) The roller fault is detected and repaired in the early stage, so that the sliding friction between the rubber belt and the fault roller can be reduced, the service life of the rubber belt is prolonged, and the running safety of the belt conveyor is enhanced.
3) A sound pressure sensor is carried on the intelligent inspection equipment to carry out non-contact measurement, and the detection scheme is low in cost and high in reliability.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
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For the purposes of promoting a better understanding of the objects, aspects and advantages of the invention, reference will now be made to the following detailed description taken in conjunction with the accompanying drawings in which:
fig. 1 is a schematic structural diagram of an acoustic diagnosis system for roller abnormality of a belt conveyor according to the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention in a schematic way, and the features in the following embodiments and examples may be combined with each other without conflict.
Wherein the showings are for the purpose of illustrating the invention only and not for the purpose of limiting the same, and in which there is shown by way of illustration only and not in the drawings in which there is no intention to limit the invention thereto; to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numerals in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it should be understood that if there is an orientation or positional relationship indicated by terms such as "upper", "lower", "left", "right", "front", "rear", etc., based on the orientation or positional relationship shown in the drawings, it is only for convenience of description and simplification of description, but it is not an indication or suggestion that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes, and are not to be construed as limiting the present invention, and the specific meaning of the terms may be understood by those skilled in the art according to specific situations.
Research shows that the normal carrier roller noise frequency range is mainly below 4000Hz, wherein the amplitude below 500Hz is larger. The frequency range of noise emitted by the fault carrier roller is 0-7000 Hz, wherein the amplitude in the range of 4000-6500 Hz is obviously increased.
Idler failure is mostly idler bearing failure. The carrier roller can still rotate when the carrier roller bearing is in the early failure stage, only the rotating speed becomes low, sliding friction exists in part, and the frequency spectrum curve is not obviously different from that of a normal carrier roller. Along with the aggravation of the fault degree of the bearing, the rotating speed of the carrier roller is reduced more and more until the carrier roller stops completely, the friction force between the carrier roller and the adhesive tape is changed from rolling friction to sliding friction more and more, and in the process, the frequency range in which the amplitude of the frequency spectrum curve is increased remarkably moves more and more in the high-frequency direction until the frequency range is 4000-6500 Hz.
The popular explanation for the above is that a faulty idler will emit sharper noise in operation, the sharpness of which correlates to the severity of the fault. Based on the research result, the scheme provides that the acutance index in the sound quality index is adopted to diagnose the fault carrier roller.
The Sharpness (Sharpness) index describes the timbre characteristic in sound quality assessment, denoted S and in acum. For higher frequency sounds, the perceived sharpness is greater. At present, no standard method exists for calculating the sharpness, and the adopted calculation formula is as follows:
where N' (Z) is the loudness spectrum over critical band Z, the integral of the loudness spectrum over the critical band is the loudness, g (Z) is the additional coefficient, Z is the critical band, and d (Z) is the critical band differential.
As can be seen from the above formula, the sharpness is calculated based on a characteristic loudness curve, reflects the proportion of high-frequency components in sound, is influenced by loudness and frequency, and can accurately reflect the fault state and the fault severity of the carrier roller.
As shown in fig. 1, the acoustic diagnosis system for the roller abnormality of the belt conveyor is mounted on an inspection robot, and the inspection robot moves back and forth along the belt conveyor for inspection. The INV9206B is a capacitive sound pressure sensor, and the noise loudness is detected by detecting the capacitance value because the capacitance value is changed by the air pressure formed by sound waves. The sound pressure sensor converts a noise loudness signal into a voltage signal and sends the voltage signal to the sound encoder, an ACL892 continuously extracts the frequency and amplitude (loudness) of the noise signal to form a sound wave represented by a digital signal, the sound wave is sent to an SOM7569 CPU module in a serial communication mode, an application program running on the CPU module performs operations such as FFT analysis on the noise signal to obtain a critical frequency band and a loudness spectrum, noise sharpness data is calculated every 2 seconds according to the formula (1), and if the sharpness exceeds a set threshold, an alarm signal is sent out.
Alarm signal carries time information and sends for the wifi router with 10/100M ethernet signal, and the wifi router sends the communication basic station that the belt conveyor arranged along the line with wireless communication mode, and the basic station sends alarm information for robot management platform with wired communication mode again, and robot management platform sends alarm information and record through human-computer interface.
Because time information is contained in the alarm information, the robot management platform can calculate the position of the inspection robot when the inspection robot gives an alarm according to the time information, and therefore maintenance personnel can quickly find out a fault carrier roller for maintenance and replacement after the belt conveyor is stopped according to the alarm information.
Finally, the above embodiments are only intended to illustrate the technical solutions of the present invention and not to limit the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions, and all of them should be covered by the claims of the present invention.
Claims (6)
1. The utility model provides a belt conveyor bearing roller unusual acoustics diagnostic system which characterized in that: the system comprises an inspection robot and a robot management platform, wherein the inspection robot inspects back and forth along a belt conveyor, and an acoustic diagnosis module, a processor module and a wireless communication module are arranged on the inspection robot; the acoustic diagnosis module is used for detecting the frequency and amplitude of the noise signal, forming a digital signal and sending the digital signal to the processor module; the processor module is used for calculating noise sharpness data according to the received digital signals, comparing the noise sharpness data with a sharpness threshold value, and sending an alarm signal if the noise sharpness data exceeds the sharpness threshold value; the alarm signal is sent to a base station arranged along the belt conveyor through the wireless communication module, and the base station is forwarded to the robot management platform; and the robot management platform sends out alarm information and records the alarm information.
2. The belt conveyor idler roller anomaly acoustic diagnostic system of claim 1, wherein: the acoustic diagnosis module comprises a sound pressure sensor and a sound encoder, wherein the sound pressure sensor converts a noise loudness signal into a voltage signal and sends the voltage signal to the sound encoder, and the sound encoder continuously extracts the frequency and amplitude (loudness) of the noise signal to form sound waves represented by digital signals and sends the sound waves to the processor module.
3. The belt conveyor idler roller anomaly acoustic diagnostic system of claim 1, wherein: the robot management platform comprises time information in alarm information sent by the robot management platform, and the robot management platform calculates the position of the inspection robot when the inspection robot sends the alarm through the time information so as to position a fault carrier roller.
4. The belt conveyor idler roller anomaly acoustic diagnostic system of claim 1, wherein: the processor module firstly carries out FFT analysis on the noise signal to obtain a critical frequency band and a loudness spectrum, and then calculates noise sharpness data every 2 seconds according to the following formula:
where N' (Z) is the loudness spectrum over critical band Z, the integral of the loudness spectrum over the critical band is the loudness, g (Z) is the additional coefficient, Z is the critical band, and d (Z) is the critical band differential.
5. The abnormal acoustic diagnosis method for the belt conveyor carrier roller is characterized by comprising the following steps of: the method comprises the following steps:
s1: the inspection robot moves back and forth along the belt conveyor for inspection, and noise signals of the carrier rollers are collected;
s2: converting the noise loudness signal into a voltage signal through a sound pressure sensor, sending the voltage signal into a sound coder, continuously extracting the frequency and amplitude (loudness) of the noise signal by the sound coder to form a sound wave represented by a digital signal, and sending the sound wave to a processor module;
s3: the processor carries out FFT analysis on the noise signal to obtain a critical frequency band and a loudness spectrum, noise sharpness data are calculated once every 2 seconds, if the sharpness exceeds a set threshold value, an alarm signal is sent to a base station arranged along the belt conveyor, and the alarm signal is forwarded to the robot management platform through the base station;
s4: the robot management platform sends alarm information to a human-computer interface after receiving the alarm signal and records the alarm information;
s5: and the robot management platform calculates the position of the fault carrier roller according to the time information recorded in the alarm information.
6. The belt conveyor idler roller abnormality acoustic diagnosis method according to claim 5, characterized in that: the processor module calculates the noise sharpness data by:
where N' (Z) is the loudness spectrum over critical band Z, the integral of the loudness spectrum over the critical band is the loudness, g (Z) is the additional coefficient, Z is the critical band, and d (Z) is the critical band differential.
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Cited By (4)
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| CN114940355A (en) * | 2022-03-24 | 2022-08-26 | 中国矿业大学 | Acoustic signal inspection system of belt conveyor with sound-receiving array and its sound-receiving module |
| CN115096375A (en) * | 2022-08-22 | 2022-09-23 | 启东亦大通自动化设备有限公司 | Carrier roller running state monitoring method and device based on carrier roller carrying trolley detection |
| CN115753984A (en) * | 2022-11-04 | 2023-03-07 | 中煤科工集团重庆研究院有限公司 | A Method of Extracting Abnormal Features of Idler Based on Voiceprint Spectrum Separation |
| CN118004704A (en) * | 2024-04-10 | 2024-05-10 | 宁波联河光子技术有限公司 | DAS-based belt conveyor carrier roller fault monitoring method in complex sound field |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114940355A (en) * | 2022-03-24 | 2022-08-26 | 中国矿业大学 | Acoustic signal inspection system of belt conveyor with sound-receiving array and its sound-receiving module |
| CN115096375A (en) * | 2022-08-22 | 2022-09-23 | 启东亦大通自动化设备有限公司 | Carrier roller running state monitoring method and device based on carrier roller carrying trolley detection |
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| CN118004704A (en) * | 2024-04-10 | 2024-05-10 | 宁波联河光子技术有限公司 | DAS-based belt conveyor carrier roller fault monitoring method in complex sound field |
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Application publication date: 20210706 |