CN114509265A - Wireless power supply's intelligent bearing on-line monitoring device - Google Patents
Wireless power supply's intelligent bearing on-line monitoring device Download PDFInfo
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Abstract
The utility model provides a wireless power supply's intelligent bearing on-line monitoring device, belongs to bearing monitoring technology field. The wireless bearing health state evaluation device comprises a bearing body, a wireless sensing device, a wireless power supply device and a bearing online health state evaluation device, wherein the wireless sensing device and the wireless power supply device are arranged on the bearing body; the bearing online health state assessment device comprises a bearing multi-parameter monitoring controller and a bearing online health state assessment model, the bearing multi-parameter monitoring controller collects bearing body data monitored by the wireless sensing device in real time, the data are wirelessly transmitted to the cloud monitoring platform, the data are analyzed and processed through the bearing online health state assessment model, and bearing body faults are pre-judged in advance.
Description
Technical Field
The invention belongs to the technical field of bearing monitoring, and particularly relates to a wireless power supply intelligent bearing online monitoring device.
Background
The bearing is a core part of modern industry, and is widely applied to various fields of aerospace, high-speed rails, automobile hubs, large rotors, precision machine tools and the like. The reliability of the operation of the bearing directly determines the fault rate level of the equipment, so that the operation data of the vibration, the temperature and the like of the bearing are urgently needed to be monitored, and the possible faults are pre-judged in advance, so that the fault rate of the operation of the equipment is reduced.
With the rise of the intelligent diagnosis technology of equipment and the development of sensors, the purpose of prejudging in advance is achieved by integrating sensing devices with different purposes on the bearing and processing the data acquired by connection through a computer bearing health state evaluation model to find whether faults and cracks exist. However, the existing bearing health state evaluation model depends on signal understanding and bearing field knowledge, so that different types of faults need to extract different features, and the existing bearing health state evaluation model is only suitable for off-line diagnosis and cannot be used for on-line real-time diagnosis.
Therefore, a new solution is needed to solve this problem.
Disclosure of Invention
The invention mainly solves the technical problems in the prior art and provides a wireless power supply intelligent bearing online monitoring device.
The technical problem of the invention is mainly solved by the following technical scheme: a wireless power supply intelligent bearing online monitoring device comprises a bearing body, a wireless sensing device, a wireless power supply device and a bearing online health state evaluation device, wherein the wireless sensing device and the wireless power supply device are arranged on the bearing body, and the wireless power supply device is used for supplying power to the wireless sensing device and the bearing online health state evaluation device; the bearing online health state assessment device comprises a bearing multi-parameter monitoring controller and a bearing online health state assessment model, the bearing multi-parameter monitoring controller collects bearing body data monitored by the wireless sensing device in real time, wirelessly transmits the data to the cloud monitoring platform, and analyzes and processes the data through the bearing online health state assessment model to pre-judge bearing body faults in advance.
Preferably, the wireless sensing device comprises a shell, a cover plate and a sensor body, mounting holes are formed in two sides of the shell, the shell is fixed on a hub through a bolt at a wheel end after penetrating through the mounting holes and then connected with the hub in a threaded mode, the shell is provided with a containing cavity used for containing the sensor body, the cover plate is used for covering the containing cavity, and a sealing ring is arranged at the joint of the cover plate and the shell.
Preferably, the sensor body comprises a microcontroller, and a temperature sensor, a vibration acceleration sensor, a rotating speed sensor, a film force sensor, a lubricating oil quality detection sensor, a power supply module and a wireless communication module which are electrically connected with the microcontroller.
Preferably, the wireless communication module is in communication connection with the bearing multi-parameter monitoring controller through Lora or Bluetooth.
Preferably, the wireless power supply device comprises a rotating ring, a demagnetizer, a piezoelectric layer, a tuning terminal, a fixing ring and a vibration energy collector, wherein the tuning terminal and the demagnetizer are arranged on the fixing ring in an annular array mode, the tuning terminal and the demagnetizer are arranged at intervals, the rotating ring is arranged in the fixing ring and is coaxially arranged with the rotating ring, the piezoelectric layer is arranged on the rotating ring in an annular array mode, and the vibration energy collector is arranged on the rotating ring.
Preferably, the algorithm of the bearing online health state evaluation model comprises the following steps:
and 3, letting K = 0, wherein K is the number of the bearing signal data segments for network training, and expressing the new training bearing signal data of each K +1 block as follows:
here, the
The number of training samples in the K +1 bearing signal data set is obtained;
And 6, enabling K = K +1 and returning to the online learning stage calculation in the step 3.
Preferably, the bearing multi-parameter monitoring controller transmits data to the cloud monitoring platform through NB-LoT.
The invention has the following beneficial effects: the wireless power supply device is adopted to supply power to the wireless sensing device and the bearing online health state evaluation device, so that the real-time online monitoring effect is realized, monitoring personnel can determine the equipment maintenance time according to the analysis of the bearing online monitoring state evaluation model, the shutdown loss caused by the bearing fault is reduced, meanwhile, the power source of the wireless power supply device is from the self rotation of the bearing body, an external power source is not needed, the installation volume is simplified, and the intelligent bearing online monitoring device is convenient to install on the bearing body. According to the invention, the existing bearing health state evaluation algorithm is improved, so that the calculation process of the bearing online monitoring state evaluation model is quicker, and the algorithm performance is better.
Drawings
FIG. 1 is a schematic diagram of an embodiment of the present invention;
FIG. 2 is a schematic diagram of a wireless sensor device according to the present invention;
FIG. 3 is a schematic diagram of a wireless power supply apparatus according to the present invention;
FIG. 4 is a schematic flow chart of the on-line health status evaluation model of the bearing of the present invention.
In the figure: 1. a bearing body; 2. a wireless sensing device; 3. a bearing multi-parameter monitoring controller; 4. a housing; 5. a cover plate; 6. mounting holes; 7. an accommodating chamber; 8. a seal ring; 9. a rotating ring; 10. a demagnetizer; 11. a piezoelectric layer; 12. a tuning terminal; 13. a fixing ring; 14. a vibration energy harvester.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b): an intelligent bearing online monitoring device with wireless power supply is disclosed, as shown in fig. 1-3, and comprises a bearing body 1, a wireless sensing device 2, a wireless power supply device, and a bearing online health state assessment device, wherein the wireless sensing device 2 and the wireless power supply device are arranged on the bearing body 1, and the wireless power supply device is electrically connected with the wireless sensing device 2 and the bearing online health state assessment device and is used for supplying power to the wireless sensing device 2 and the bearing online health state assessment device; the bearing online health state assessment device comprises a bearing multi-parameter monitoring controller 3 and a bearing online health state assessment model, wherein the bearing multi-parameter monitoring controller 3 is installed on a bearing body 1, the bearing multi-parameter monitoring controller 3 collects data of the bearing body 1 monitored by a wireless sensor in real time and wirelessly transmits the data to a cloud monitoring platform, the data are analyzed and processed through the bearing online health state assessment model, and faults of the bearing body 1 are pre-judged in advance.
The sensor body comprises a microcontroller, and a temperature sensor, a vibration acceleration sensor, a rotating speed sensor, a film force sensor, a lubricating oil quality detection sensor, a power supply module and a wireless communication module which are electrically connected with the microcontroller. The sensor body is to the trouble that bearing inner race, bearing inner race and rolling element may take place, temperature, acceleration, speed, vibration, pressure, lubricated state, degree of wear and tear etc. of real-time supervision bearing body 1, and wireless communication module passes through Lora or bluetooth transmission with data transmission to bearing multi-parameter monitoring controller 3, and power module is used for microcontroller power supply, can adopt rechargeable battery.
Wireless power supply unit includes swivel becket 9, demagnetizer 10, piezoelectric layer 11, tuning terminal 12, solid fixed ring 13 and vibration energy collector 14, tuning terminal 12, demagnetizer 10 are the annular array and set up on solid fixed ring 13, just tuning terminal 12 sets up with the demagnetizer 10 interval, swivel becket 9 sets up in solid fixed ring 13, just gu fixed ring 13 sets up with swivel becket 9 is coaxial, piezoelectric layer 11 is the annular array and sets up and change in the rotation, vibration energy collector 14 sets up on the swivel becket 9.
When the piezoelectric vibration energy collector is used, the rotating ring 9 is installed on a bearing of the bearing body 1, the fixing ring 13 is installed on a bearing seat of the bearing body 1, when the bearing of the rotating shaft body rotates, the rotating ring 9 is driven to rotate, the piezoelectric layer 11 on the rotating ring 9 and the tuning terminal 12 of the annular array on the fixing ring 13 move relatively and generate energy, the tuning terminal 12 is a magnet, and the vibration energy collector 14 adopts the electromagnetic vibration energy collector 14 to collect and convert the generated energy into electric energy to be output and supply power.
The bearing multi-parameter monitoring controller 3 transmits collected data such as temperature, acceleration and vibration of the bearing body 1 to the cloud monitoring platform in real time through NB-LoT transmission, the online health state evaluation model of the bearing analyzes and processes the collected data to find whether faults and cracks exist, and cloud platform monitoring personnel determine equipment maintenance time according to analysis results to reduce shutdown loss caused by bearing faults.
In the existing bearing health state evaluation model (extreme learning machine model ELM),
given bearing signal acquisition sample
，
And
is provided with
A node
The activation function is
The mathematical model of SLFNs of (1) is:
wherein,
is a weight vector connecting the ith hidden node and the input node,
is a weight vector connecting the ith hidden node and the output node,
is the deviation of the ith hidden layer node;
with
SLFNs, activation functions, of individual hidden nodes
Capable of zero-error approximation to N training samples, present such that equation (2) holds
And
；
the above N equations can be written succinct:
wherein,
wherein H is called a hidden layer output matrix of the neural network; column i of H is the input
The output at the i-th hidden node.
As shown in FIG. 4, the bearing online health state assessment model (online continuous extreme learning model NOS-ELM) is an equation
Substitution into optimization model
The model has at least one optimized solution, which can reduce the computation complexity of solving the matrix inversion; secondly, adding a regular factor when calculating the output weight
And finally, adding subsequent online learning, wherein the purpose of processing is that the calculation process is faster, and the performance of the algorithm is better, and the method specifically comprises the following steps:
And 6, enabling K = K +1 and returning to the online learning stage calculation in the step 3.
In summary, the wireless power supply device is adopted to supply power to the wireless sensing device and the bearing online health state evaluation device, so that the real-time online monitoring effect is achieved, monitoring personnel can determine the equipment maintenance time according to the analysis of the bearing online monitoring state evaluation model, the shutdown loss caused by bearing faults is reduced, meanwhile, the power source of the wireless power supply device is from the self rotation of the bearing body, an external power source is not needed, the installation volume is simplified, and the intelligent bearing online monitoring device is convenient to install on the bearing body. According to the invention, the existing bearing health state evaluation algorithm is improved, so that the calculation process of the bearing online monitoring state evaluation model is quicker, and the algorithm performance is better.
Finally, it should be noted that the above embodiments are merely representative examples of the present invention. It is obvious that the invention is not limited to the above-described embodiments, but that many variations are possible. Any simple modification, equivalent change and modification made to the above embodiments in accordance with the technical spirit of the present invention should be considered to be within the scope of the present invention.
Claims (7)
1. The intelligent bearing online monitoring device with wireless power supply is characterized by comprising a bearing body, a wireless sensing device, a wireless power supply device and a bearing online health state evaluation device, wherein the wireless sensing device and the wireless power supply device are arranged on the bearing body; the bearing online health state assessment device comprises a bearing multi-parameter monitoring controller and a bearing online health state assessment model, wherein the bearing multi-parameter monitoring controller collects bearing body data monitored by a wireless sensing device in real time and wirelessly transmits the data to a cloud monitoring platform, the data are analyzed and processed through the bearing online health state assessment model, and bearing body faults are pre-judged in advance.
2. The wirelessly powered intelligent on-line bearing monitoring device as claimed in claim 1, wherein the wireless sensing device comprises a housing, a cover plate and a sensor body, mounting holes are formed in two sides of the housing, the housing is fixed on a hub by screwing the hub after a wheel end bolt passes through the mounting holes, the housing is provided with a containing cavity for containing the sensor body, the cover plate is used for sealing the containing cavity, and a sealing ring is arranged at the joint of the cover plate and the housing.
3. The wirelessly powered intelligent on-line bearing monitoring device as claimed in claim 2, wherein the sensor body comprises a microcontroller, and a temperature sensor, a vibration acceleration sensor, a rotation speed sensor, a film force sensor, a lubricating oil quality detection sensor, a power supply module, and a wireless communication module electrically connected to the microcontroller.
4. The on-line monitoring device for the wirelessly powered intelligent bearing of claim 3, wherein the wireless communication module is in communication connection with the bearing multi-parameter monitoring controller through Lora or Bluetooth.
5. The on-line monitoring device for the wirelessly powered intelligent bearing according to claim 1, wherein the wirelessly powered device comprises a rotating ring, a demagnetizer, a piezoelectric layer, a tuning terminal, a fixing ring and a vibration energy collector, the tuning terminal and the demagnetizer are arranged on the fixing ring in an annular array, the tuning terminal and the demagnetizer are arranged at intervals, the rotating ring is arranged in the fixing ring, the fixing ring and the rotating ring are coaxially arranged, the piezoelectric layer is arranged on the rotating ring in an annular array, and the vibration energy collector is arranged on the rotating ring.
6. The wirelessly powered intelligent bearing online monitoring device according to claim 1, wherein the algorithm of the bearing online health state evaluation model comprises the following steps:
step 1, randomly generating connection weight between input layer and hidden layer
And biasing of hidden layer neurons
Initializing a network; computing an initial hidden layer output matrix
；
Step 2, order
If, if
Then calculate the initial weight vector
(ii) a If it is not
Then calculate the initial weight vector
(ii) a Here, the
，
(ii) a If it is not
And is provided with
Solving two optimization models
And
an optimized solution can be obtained
、
(ii) a Here, the
，
，
G is a positive definite symmetric matrix；
And 3, letting K = 0 and K be the number of the bearing signal data segments of the network training, and expressing the new training bearing signal data of each K +1 block as
Here, the
The number of training samples in the K +1 bearing signal data set is obtained;
step 4, calculating a hidden layer output matrix of the K +1 training sample, and solving a formula as follows:
step 5, calculating output weight vector according to the previous step 1
；
And 6, enabling K = K +1 and returning to the online learning stage calculation in the step 3.
7. The wirelessly powered intelligent on-line bearing monitoring device as claimed in claim 1, wherein the bearing multi-parameter monitoring controller transmits data to the cloud monitoring platform via NB-LoT.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1682257A (en) * | 2002-09-09 | 2005-10-12 | Ntn株式会社 | Wireless sensor system and bearing device with wireless sensor |
| CN103973161A (en) * | 2014-04-25 | 2014-08-06 | 天津大学 | Rotation piezoelectric energy collecting device |
| CN106523523A (en) * | 2016-11-11 | 2017-03-22 | 长安大学 | Piezoelectric energy harvesting bearing used for rotating machines |
| CN109630542A (en) * | 2018-12-18 | 2019-04-16 | 上海交通大学 | A kind of built-in wireless sensor and the intelligent bearing with self-powered function |
| CN109858104A (en) * | 2019-01-10 | 2019-06-07 | 山东大学 | A kind of rolling bearing health evaluating and method for diagnosing faults and monitoring system |
| CN113074940A (en) * | 2021-03-18 | 2021-07-06 | 昆明理工大学 | Rolling bearing health state estimation system and method based on OS-ELM |
| CN214837878U (en) * | 2021-07-12 | 2021-11-23 | 中北大学 | Self-powered monitoring rolling bearing |
-
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- 2022-04-20 CN CN202210413281.8A patent/CN114509265A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1682257A (en) * | 2002-09-09 | 2005-10-12 | Ntn株式会社 | Wireless sensor system and bearing device with wireless sensor |
| CN103973161A (en) * | 2014-04-25 | 2014-08-06 | 天津大学 | Rotation piezoelectric energy collecting device |
| CN106523523A (en) * | 2016-11-11 | 2017-03-22 | 长安大学 | Piezoelectric energy harvesting bearing used for rotating machines |
| CN109630542A (en) * | 2018-12-18 | 2019-04-16 | 上海交通大学 | A kind of built-in wireless sensor and the intelligent bearing with self-powered function |
| CN109858104A (en) * | 2019-01-10 | 2019-06-07 | 山东大学 | A kind of rolling bearing health evaluating and method for diagnosing faults and monitoring system |
| CN113074940A (en) * | 2021-03-18 | 2021-07-06 | 昆明理工大学 | Rolling bearing health state estimation system and method based on OS-ELM |
| CN214837878U (en) * | 2021-07-12 | 2021-11-23 | 中北大学 | Self-powered monitoring rolling bearing |
Non-Patent Citations (1)
| Title |
|---|
| 陈建原 等: "基于在线连续极限学习机的图像分类改进算法", 《福州大学学报( 自然科学版)》 * |
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