CN114733756B - Embedded sieve plate state monitoring device and monitoring method thereof - Google Patents
Embedded sieve plate state monitoring device and monitoring method thereof Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 20
- 238000012544 monitoring process Methods 0.000 title claims abstract description 17
- 238000012806 monitoring device Methods 0.000 title claims abstract description 16
- 238000012545 processing Methods 0.000 claims abstract description 28
- 238000004891 communication Methods 0.000 claims abstract description 18
- 230000001133 acceleration Effects 0.000 claims description 30
- 230000003044 adaptive effect Effects 0.000 claims description 20
- 238000004364 calculation method Methods 0.000 claims description 11
- 230000003595 spectral effect Effects 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 8
- 238000001514 detection method Methods 0.000 claims description 7
- QVFWZNCVPCJQOP-UHFFFAOYSA-N chloralodol Chemical compound CC(O)(C)CC(C)OC(O)C(Cl)(Cl)Cl QVFWZNCVPCJQOP-UHFFFAOYSA-N 0.000 claims description 3
- 230000005484 gravity Effects 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 238000013459 approach Methods 0.000 claims 1
- 230000005856 abnormality Effects 0.000 abstract 1
- 230000008447 perception Effects 0.000 abstract 1
- 230000001960 triggered effect Effects 0.000 description 7
- 238000007689 inspection Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000004140 cleaning Methods 0.000 description 2
- 230000006378 damage Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 208000027418 Wounds and injury Diseases 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000003292 glue Substances 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 229920002635 polyurethane Polymers 0.000 description 1
- 239000004814 polyurethane Substances 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07B—SEPARATING SOLIDS FROM SOLIDS BY SIEVING, SCREENING, SIFTING OR BY USING GAS CURRENTS; SEPARATING BY OTHER DRY METHODS APPLICABLE TO BULK MATERIAL, e.g. LOOSE ARTICLES FIT TO BE HANDLED LIKE BULK MATERIAL
- B07B1/00—Sieving, screening, sifting, or sorting solid materials using networks, gratings, grids, or the like
- B07B1/28—Moving screens not otherwise provided for, e.g. swinging, reciprocating, rocking, tilting or wobbling screens
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07B—SEPARATING SOLIDS FROM SOLIDS BY SIEVING, SCREENING, SIFTING OR BY USING GAS CURRENTS; SEPARATING BY OTHER DRY METHODS APPLICABLE TO BULK MATERIAL, e.g. LOOSE ARTICLES FIT TO BE HANDLED LIKE BULK MATERIAL
- B07B1/00—Sieving, screening, sifting, or sorting solid materials using networks, gratings, grids, or the like
- B07B1/42—Drive mechanisms, regulating or controlling devices, or balancing devices, specially adapted for screens
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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Abstract
The invention relates to the technical field of sieve plate monitoring, in particular to an embedded sieve plate state monitoring device and a monitoring method thereof. The embedded sieve plate state monitoring device comprises a power supply module for providing a power supply and a state sensing module, wherein the state sensing module is connected with a signal processing module, the signal processing module is connected with a background management system through a communication module, and the background management system is connected with sieve plate operation equipment and alarm equipment; the state perception module is used for collecting the operation state data of the sieve plate; the signal processing module is used for analyzing and processing the acquired sieve plate running state data and judging the fixed condition of the sieve plate; the background management system is used for sending data trace and related instructions; the communication module is used for realizing the communication between the signal processing module and the background management system. The embedded sieve plate state monitoring device and the monitoring method thereof can monitor the working state of the sieve plate in real time on line and timely alarm the abnormality of the sieve plate by matching with a background information management system.
Description
Technical Field
The invention relates to the technical field of sieve plate monitoring, in particular to an embedded sieve plate state monitoring device and a monitoring method thereof.
Background
At present, in the working process of a screening machine, a screen plate is influenced by vibration and material interaction, loosening and falling faults can occur, and once the screen plate falls, production is seriously influenced. Firstly, the sieve plate is required to be stopped immediately when falling off, and the existing stage has no high-efficiency processing scheme and mainly depends on manual cleaning; secondly, material accumulation can occur, which causes chute blockage and belt damage; thirdly, the cleaning work after the sieve plate falls off is easy to cause personal injury. Therefore, the device for monitoring the state of the sieve plate in real time has great practical significance.
At present, the failure detection of the sieve plate mainly depends on manual inspection, the manual inspection depends on subjective experience of personnel, strict failure judgment basis cannot be formed, and early failure hidden danger cannot be found under most conditions; secondly, manual inspection is not strong in real-time performance and only can be performed periodically, and fault removal is not timely enough; moreover, the manual inspection of the multilayer sieve plate is difficult to implement; finally, complete life cycle management of the sieve plate state cannot be established based on manual inspection, and the sieve plate replacement in the currently adopted fixed cycle has huge waste.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the embedded type sieve plate state monitoring device and the monitoring method thereof can be used for overcoming the defects of the prior art and monitoring the working state of the sieve plate on line in real time and timely alarming the abnormity of the sieve plate by matching with a background information management system.
The technical scheme adopted by the invention for solving the technical problem is as follows: the embedded sieve plate state monitoring device comprises a power supply module for providing a power supply and a state sensing module, wherein the state sensing module is connected with a signal processing module, the signal processing module is connected with a background management system through a communication module, and the background management system is connected with sieve plate operation equipment and alarm equipment;
the state sensing module is used for collecting sieve plate operation state data;
the signal processing module is used for analyzing and processing the acquired sieve plate operation state data and judging the fixed condition of the sieve plate;
the background management system is used for sending data trace and related instructions;
and the communication module is used for realizing the communication between the signal processing module and the background management system.
The state sensing module comprises an acceleration sensor and a temperature sensor, and the acceleration sensor and the temperature sensor are respectively connected with the signal processing module;
the screen plate peeling device further comprises a MEMS sensor used for detecting whether the screen plate is peeled off or not.
The signal processing module adopts a time domain threshold detection algorithm and frequency domain Power Spectral Density (PSD) analysis, and combines an adaptive filter algorithm to carry out adaptive evolution so as to judge the state of the sieve plate.
The communication module adopts the wireless connection of loRa wireless communication mode and backstage management system.
The monitoring method applied to the embedded sieve plate state monitoring device comprises the following steps:
the method comprises the following steps: signal acquisition;
step two: performing time domain threshold detection algorithm and frequency domain Power Spectral Density (PSD) analysis, performing adaptive evolution by combining with an adaptive filter algorithm, and judging whether a sieve plate is loosened;
step three: judging that the sieve plate falls off;
step four: and sending related data to the background management system.
In the first step, the acquired information comprises three-axis acceleration and temperature.
The second step comprises the following substeps:
1-1: computing time domain eigenvalues
The calculation formula is as follows:
1-2：
corresponding contrast threshold
The method is automatically obtained by adopting an adaptive filter, and the calculation formula is as follows:
wherein the content of the first and second substances,
is the Least-Mean-Square (Least-Mean-Square) calculated by the adaptive filter;
1-3: respectively carrying out integral operation on high/low frequency parts of the Wideband (WB) by taking 80 percent of the wideband as a boundary to obtain a ratio of the high/low frequency parts
The calculation formula is as follows:
In the step 1-2, if
>
If the screen plate is judged to have vibration deviating from the normal working state and fault hidden danger, an alarm is triggered, otherwise, the screen plate operates normally.
In said step 1-3, if
>
If the screen plate is abnormally increased due to high-frequency vibration, the screen plate is judged to be loosened, and an alarm is triggered.
In the third step, the shedding of the sieve plate is monitored through an MEMS sensor;
the sieve plate is fallen (namely the sieve plate does free fall movement), the acceleration of each shaft is zero, the absolute value of the acceleration approaching zero is set to be 3m/s and the free fall time threshold value
，
Wherein
Calculating according to the mounting height H of the sieve plate to obtain:
wherein g is the acceleration of gravity;
when the MEMS sensors detect that the three-axis acceleration is less than 3m/s and the duration time exceeds
If the sieve plate falls off, the falling alarm is triggered.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides an embedded sieve plate state monitoring device and a monitoring method thereof, which realize automatic monitoring, save manpower and reduce personal safety risks. Meanwhile, real-time state monitoring can be carried out, early hidden danger warning can be carried out, meanwhile, the machine can be stopped in time, and production accidents are avoided. Complete sieve plate life cycle management is established, and the sieve plate is replaced only when necessary, so that waste is avoided.
Drawings
FIG. 1 is a block diagram of the present invention.
Detailed Description
Embodiments of the present invention are further described below with reference to the accompanying drawings.
Examples
As shown in fig. 1, the embedded sieve plate state monitoring device comprises a power supply module for providing power, and further comprises a state sensing module, wherein the state sensing module is connected with a signal processing module, the signal processing module is connected with a background management system through a communication module, and the background management system is connected with sieve plate operation equipment and alarm equipment;
the state sensing module is used for collecting the running state data of the sieve plate;
the signal processing module is used for analyzing and processing the collected sieve plate running state data and judging the fixed condition of the sieve plate;
the background management system is used for sending data trace and related instructions;
the communication module is used for realizing the communication between the signal processing module and the background management system.
The state sensing module comprises an acceleration sensor and a temperature sensor, and the acceleration sensor and the temperature sensor are respectively connected with the signal processing module;
the screen plate peeling device further comprises a MEMS sensor used for detecting whether the screen plate is peeled off or not.
The signal processing module adopts a time domain threshold detection algorithm and frequency domain Power Spectral Density (PSD) analysis (namely, the PSD is a signal analysis method, and when a time sequence is analyzed, a time domain signal can be converted into a frequency domain by using the PSD, and the functional relation between variation/variance (energy) and frequency is visually observed), and the adaptive filter algorithm is combined to carry out adaptive evolution so as to judge the state of a sieve plate.
The communication module is in wireless connection with the background management system in a LoRa wireless communication mode.
When the device is installed, the device is installed on one side of the sieve plate in an embedded mode, namely, the device is encapsulated in polyurethane glue of the sieve plate in the production process of the sieve plate, and installation and fixation of the device are completed.
Example 2
The monitoring method applied to the embedded sieve plate state monitoring device in the embodiment 1 comprises the following steps:
the method comprises the following steps: signal acquisition; in the first step, the acquired information comprises three-axis acceleration and temperature.
Step two: performing time domain threshold detection algorithm and frequency domain Power Spectral Density (PSD) analysis, performing adaptive evolution by combining with an adaptive filter algorithm, and judging whether a sieve plate is loosened;
the second step comprises the following substeps:
1-1: computing time domain eigenvalues
The calculation formula is as follows:
1-2: time domain eigenvalues
Corresponding contrast threshold
The method is automatically obtained by adopting an adaptive filter, and the calculation formula is as follows:
wherein the content of the first and second substances,
is a Least-Mean-Square (Least-Mean-Square) algorithm.
1-3: the frequency domain Power Spectrum Density (PSD) can intuitively reflect the relation between the vibration amplitude and the frequency, the vibration frequency is in a low-frequency band in the normal work of the sieve plate, and the vibration power spectrum density of the sieve plate is obtained through PSD analysis. Respectively performing integral operation on the high/low frequency parts by taking the frequency bandwidth (WB) 80% as a boundary to obtain the ratio
The calculation formula is as follows:
Step three: judging that the sieve plate falls off; monitoring the falling of the sieve plate through an MEMS sensor;
if the sieve plate falls off (i.e. the sieve plate performs free-fall motion), the acceleration of each axis is zero, and due to sensor error and circuit interference, the absolute value of acceleration 3m/s which is close to zero needs to be set and the free-fall time threshold value
，
Wherein
Calculating according to the mounting height H of the sieve plate to obtain:
wherein g is gravity acceleration;
when the MEMS sensors detect that the triaxial accelerations are all smaller than 3m/s and the duration time exceeds
If the sieve plate falls off, the falling alarm is triggered.
Step four: and sending related data to a background management system.
Example 3
Based on the embodiment 1 and the embodiment 2
For example, effective value of acceleration of vibrating screen in actual operation
About 2.01g (g =9.8 m/s), instantaneous acceleration peak value has been restored during its normal operation
Being 2.8g (g =9.8 m/s), the time-domain feature value calculator according to the formula has been completed
Is 1.393, calculated by the least mean square algorithm
=1.775, Srp =1.42, where Rp (1.393)<Srp (0.8 × 1.775), the plant was operating normally.
Acquiring the power spectral density of the sieve plate by a power spectral density measuring instrument, and processing the power spectral density by a frequency band broadband (WB) 80% of the total band, and respectively performing integral operation on the high/low frequency parts to obtain the ratio thereof
=352.66, output value after LMS adaptive filter
=467.11。
（352.66）<
(0.8 × 467.11), the sieve plate is normal in working condition. All the above conclusions are consistent with the state of the field device.
In this embodiment, the height of the screen panel is 0.5 m, and the free fall time threshold STFF =0.102, that is, when the absolute values of the three-axis accelerations are all smaller than 3m/s and the duration time exceeds 0.102 seconds, it is determined that the screen panel sends a drop-out. The alarm is not triggered in the running process of the equipment, and no sieve plate falls off on site.
Claims (3)
1. An embedded sieve plate state monitoring device comprises a power supply module for providing a power supply, and is characterized by further comprising a state sensing module, wherein the state sensing module is connected with a signal processing module, the signal processing module is connected with a background management system through a communication module, and the background management system is connected with sieve plate operation equipment and alarm equipment;
the state sensing module is used for collecting sieve plate operation state data;
the signal processing module is used for analyzing and processing the collected sieve plate running state data and judging the fixed condition of the sieve plate;
the background management system is used for sending data trace and related instructions;
the communication module is used for realizing the communication between the signal processing module and the background management system;
the monitoring method of the embedded sieve plate state monitoring device comprises the following steps:
the method comprises the following steps: signal acquisition;
step two: performing time domain threshold detection algorithm and frequency domain power spectral density analysis, performing adaptive evolution by combining with an adaptive filter algorithm, and judging whether the sieve plate is loosened; the second step comprises the following substeps:
1-1: calculating a time domain characteristic value Rp, wherein the calculation formula is as follows:
1-2：
corresponding contrast threshold
The method is automatically obtained by adopting an adaptive filter, and the calculation formula is as follows:
wherein the content of the first and second substances,
is a least mean square algorithm;
1-3: respectively carrying out integral operation on high/low frequency parts of the broadband by taking 80% of the broadband as a boundary to obtain a ratio R of the high/low frequency parts HL The calculation formula is as follows:
R HL and a threshold value
Comparing, and judging whether the sieve plate is loosened; in said step 1-3, if R HL >S HL If the screen plate is abnormally increased due to high-frequency vibration, judging that the screen plate is loosened, and triggering an alarm;
step three: judging that the sieve plate falls off; in the third step, the shedding of the sieve plate is monitored through an MEMS sensor;
if the sieve plate falls off, the acceleration of each shaft is zero, the absolute value of the acceleration which approaches to zero is set to be 3m/S and the free falling time threshold value S TFF ，
Wherein S TFF Calculating according to the mounting height H of the sieve plate to obtain:
wherein g is gravity acceleration;
when MEMS sensors detect that the three-axis acceleration is smaller than 3m/S and the duration time exceeds S TFF Judging that the sieve plate falls off, and triggering a fall-off alarm;
step four: sending related data to a background management system;
the state sensing module comprises an acceleration sensor and a temperature sensor, and the acceleration sensor and the temperature sensor are respectively connected with the signal processing module;
the MEMS sensor is used for detecting whether the sieve plate falls off or not;
the signal processing module adopts a time domain threshold detection algorithm and frequency domain power spectral density analysis, and performs adaptive evolution by combining with an adaptive filter algorithm to judge the state of the sieve plate.
2. The embedded screen deck condition monitoring device of claim 1, wherein the communication module is wirelessly connected to a background management system in a LoRa wireless communication manner.
3. The embedded screen deck condition monitoring device of claim 1, wherein in step one, the collected information includes three-axis acceleration, temperature.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202562760U (en) * | 2012-05-02 | 2012-11-28 | 中国神华能源股份有限公司 | Vibrating screen on-line diagnosis device |
| CN203037288U (en) * | 2012-12-10 | 2013-07-03 | 山西潞安集团余吾煤业有限责任公司 | Vibration screen fault diagnosis device |
| WO2014136121A1 (en) * | 2013-03-07 | 2014-09-12 | Tega Industries Limited | Vibrating screen panel health monitoring system |
| CN204731013U (en) * | 2015-06-25 | 2015-10-28 | 中铁第四勘察设计院集团有限公司 | A kind of monitor and early warning system of suspension equipment looseness fault |
| CN107389323A (en) * | 2017-06-29 | 2017-11-24 | 西安建筑科技大学 | A kind of vibratory sieve remote fault diagnosis based on cloud computing and maintenance system and method |
| CN108554801A (en) * | 2018-04-19 | 2018-09-21 | 榆林学院 | A kind of de-mediated sieve plate falls off monitoring device |
| CN207923426U (en) * | 2017-12-26 | 2018-09-28 | 华侨大学 | A kind of vibrating screen failure monitoring system |
| CN110386530A (en) * | 2019-07-16 | 2019-10-29 | 浙江大学 | A kind of elevator monitoring systems and method towards fault diagnosis and safe early warning |
| CN111687041A (en) * | 2020-06-09 | 2020-09-22 | 河北招岳聚氨酯制品有限公司 | Intelligent sieve plate and screen monitoring system |
| CN211914565U (en) * | 2020-03-25 | 2020-11-13 | 山东科技大学 | Real-time fault detection system for vibrating screen |
| CN113996528A (en) * | 2021-11-01 | 2022-02-01 | 北京明月智联科技有限公司 | Multifunctional monitoring screen machine and monitoring system thereof |
| CN114279728A (en) * | 2021-12-07 | 2022-04-05 | 郑州大学 | Fault diagnosis method and system for vibrating screen body |
Family Cites Families (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE60045611D1 (en) * | 1999-12-21 | 2011-03-24 | Tektronix Inc | Frequency domain analysis system for a time domain meter |
| JP4924022B2 (en) * | 2006-12-27 | 2012-04-25 | Ｊｆｅスチール株式会社 | Vibrating sieve monitoring method and vibrating sieve |
| CN201616026U (en) * | 2010-03-12 | 2010-10-27 | 西安锦程振动科技有限责任公司 | Monitoring and maintaining system for vibrating screen |
| US8330610B2 (en) * | 2010-05-18 | 2012-12-11 | Polydeck Screen Corporation | System, method, and apparatus for detecting wear in a screening arrangement |
| JP6136048B2 (en) * | 2012-12-26 | 2017-05-31 | 国立研究開発法人水産研究・教育機構 | Reciprocating machine condition monitoring system, method and program |
| CN105478351B (en) * | 2016-01-14 | 2017-07-21 | 河海大学常州校区 | Real-time detection system and method for vibrating screen throughput |
| WO2019006506A1 (en) * | 2017-07-04 | 2019-01-10 | Commonwealth Scientific And Industrial Research Organisation | System and method for monitoring the condition of a vibrating screen |
| CN108152064A (en) * | 2017-12-26 | 2018-06-12 | 华侨大学 | A kind of vibrating screen fault signature extracting method and failure monitoring system |
| CN109277285A (en) * | 2018-01-26 | 2019-01-29 | 上海云统创申智能科技有限公司 | A kind of intelligent monitor system for vibrating screen |
| EP3659718B1 (en) * | 2018-11-29 | 2021-06-16 | ALLGAIER WERKE GmbH | Method and system for monitoring a filtering machine |
| CN111001566A (en) * | 2019-12-24 | 2020-04-14 | 天地（唐山）矿业科技有限公司 | Vibrating screen state monitoring device and vibrating screen |
| CN111366321A (en) * | 2020-03-25 | 2020-07-03 | 山东科技大学 | Real-time fault detection system and method for vibrating screen |
| CN111999087A (en) * | 2020-08-26 | 2020-11-27 | 西京学院 | Vibration screen online state monitoring method based on LabVIEW |
| CN215068580U (en) * | 2021-04-07 | 2021-12-07 | 山东博选矿物资源技术开发有限公司 | Anti-drop early warning sieve |
| CN214600323U (en) * | 2021-04-08 | 2021-11-05 | 伯特利(山东)工业设备有限公司 | Intelligent monitoring system for vibrating screen |
| CN113495517B (en) * | 2021-07-28 | 2024-04-09 | 云翔赛博(山东)数字技术有限公司 | Quick sensing and early warning method and system for falling-off of screen plate of screening machine |
| CN113776794B (en) * | 2021-08-13 | 2023-04-28 | 昆明理工大学 | Fault diagnosis method, device and system for embedded edge calculation |
-
2022
- 2022-06-10 CN CN202210649255.5A patent/CN114733756B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202562760U (en) * | 2012-05-02 | 2012-11-28 | 中国神华能源股份有限公司 | Vibrating screen on-line diagnosis device |
| CN203037288U (en) * | 2012-12-10 | 2013-07-03 | 山西潞安集团余吾煤业有限责任公司 | Vibration screen fault diagnosis device |
| WO2014136121A1 (en) * | 2013-03-07 | 2014-09-12 | Tega Industries Limited | Vibrating screen panel health monitoring system |
| CN204731013U (en) * | 2015-06-25 | 2015-10-28 | 中铁第四勘察设计院集团有限公司 | A kind of monitor and early warning system of suspension equipment looseness fault |
| CN107389323A (en) * | 2017-06-29 | 2017-11-24 | 西安建筑科技大学 | A kind of vibratory sieve remote fault diagnosis based on cloud computing and maintenance system and method |
| CN207923426U (en) * | 2017-12-26 | 2018-09-28 | 华侨大学 | A kind of vibrating screen failure monitoring system |
| CN108554801A (en) * | 2018-04-19 | 2018-09-21 | 榆林学院 | A kind of de-mediated sieve plate falls off monitoring device |
| CN110386530A (en) * | 2019-07-16 | 2019-10-29 | 浙江大学 | A kind of elevator monitoring systems and method towards fault diagnosis and safe early warning |
| CN211914565U (en) * | 2020-03-25 | 2020-11-13 | 山东科技大学 | Real-time fault detection system for vibrating screen |
| CN111687041A (en) * | 2020-06-09 | 2020-09-22 | 河北招岳聚氨酯制品有限公司 | Intelligent sieve plate and screen monitoring system |
| CN113996528A (en) * | 2021-11-01 | 2022-02-01 | 北京明月智联科技有限公司 | Multifunctional monitoring screen machine and monitoring system thereof |
| CN114279728A (en) * | 2021-12-07 | 2022-04-05 | 郑州大学 | Fault diagnosis method and system for vibrating screen body |
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