CN214751669U - Big data processing equipment based on convolutional neural network model - Google Patents
Big data processing equipment based on convolutional neural network model Download PDFInfo
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- CN214751669U CN214751669U CN202120463161.XU CN202120463161U CN214751669U CN 214751669 U CN214751669 U CN 214751669U CN 202120463161 U CN202120463161 U CN 202120463161U CN 214751669 U CN214751669 U CN 214751669U
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- cabinet body
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- 238000012545 processing Methods 0.000 title claims abstract description 29
- 238000013527 convolutional neural network Methods 0.000 title claims description 19
- 239000000428 dust Substances 0.000 claims abstract description 17
- 229920000742 Cotton Polymers 0.000 claims abstract description 15
- 238000009423 ventilation Methods 0.000 claims abstract description 7
- 238000010521 absorption reaction Methods 0.000 claims abstract description 3
- 230000000694 effects Effects 0.000 claims description 11
- 238000009434 installation Methods 0.000 claims description 9
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 4
- 230000017525 heat dissipation Effects 0.000 abstract description 8
- 238000003062 neural network model Methods 0.000 abstract description 6
- 238000000034 method Methods 0.000 description 6
- 238000006073 displacement reaction Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 239000003575 carbonaceous material Substances 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 238000013519 translation Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000003139 buffering effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000004438 eyesight Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000011229 interlayer Substances 0.000 description 1
- 239000010410 layer Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000003014 reinforcing effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000016776 visual perception Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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Abstract
The utility model discloses a big data processing equipment based on convolution neural network model relates to network model technical field. The novel cabinet comprises a cabinet body, wherein a mounting box is fixedly arranged at the top of the cabinet body, ventilation openings are formed in the top and the bottom of the mounting box, a fan is fixedly arranged in the mounting box, ventilation holes are formed in two sides of the cabinet body, a dust cover is fixedly arranged on the inner wall of each ventilation hole, a cabinet door is movably arranged on the front of the cabinet body, and sound absorption cotton is fixedly arranged on the back of the cabinet door; the fixed rubber slab that is provided with in bottom of the cabinet body, the fixed buffer spring that is provided with in bottom of rubber slab, buffer spring's the fixed cover that is provided with in bottom. Through setting up the fan with the heat that the internal portion of cabinet gived off guide to external environment through the fan, and bleeder vent and dust cover can also prevent to get into the internal portion of cabinet after starting the fan when carrying out the heat dissipation to the internal portion of cabinet, strengthen the heat dissipation and the dustproof ability of equipment simultaneously, the life of extension equipment ensures equipment normal use.
Description
Technical Field
The utility model relates to a network model technical field specifically is a big data processing equipment based on convolutional neural network model.
Background
The convolutional neural network is a feedforward neural network which comprises convolutional calculation and has a deep structure, and is one of representative algorithms of deep learning. Convolutional neural networks have a characteristic learning ability, and can perform translation invariant classification on input information according to a hierarchical structure thereof, and are also called translation invariant artificial neural networks. After the twenty-first century, with the introduction of deep learning theory and the improvement of numerical computing equipment, convolutional neural networks have been rapidly developed and applied to the fields of computer vision, natural language processing, and the like. The convolutional neural network is constructed by imitating a visual perception mechanism of a living being, and can be used for supervised learning and unsupervised learning, and the parameter sharing of convolution kernels in hidden layers and the sparsity of interlayer connection enable the convolutional neural network to learn lattice characteristics such as pixels and audio with small calculation amount, have stable effect and have no additional characteristic engineering requirement on data.
At present, big data processing equipment based on convolutional neural network model uses the cabinet body to deposit processing equipment more, lead to the weight overweight of the cabinet body, be difficult for people's transport and removal, in the course of the work, these processing equipment still can give off a large amount of heats, and the heat-sinking capability of most of cabinets body itself is not strong, water cooling plant leads to equipment to break down again easily, and big data processing equipment noise and vibration easily appear, make people's operational environment receive the influence, so need one kind dispel the heat fast, dustproof fall make an uproar and be convenient for the big data processing equipment based on convolutional neural network model that removes.
SUMMERY OF THE UTILITY MODEL
The utility model provides a big data processing equipment based on convolution neural network model possesses fast, the dustproof advantage of making an uproar and being convenient for remove of dispelling the heat to solve the problem that general equipment heat-sinking capability is general, the noise is big and the transport is difficult.
For the purpose that realizes that this equipment heat dissipation is fast, dustproof fall make an uproar and be convenient for remove, the utility model provides a following technical scheme: a big data processing device based on a convolutional neural network model comprises a cabinet body, wherein an installation box is fixedly arranged at the top of the cabinet body, ventilation openings are formed in the top and the bottom of the installation box, a fan is fixedly arranged in the installation box, ventilation holes are formed in two sides of the cabinet body, a dust cover is fixedly arranged on the inner wall of each ventilation hole, a cabinet door is movably arranged on the front of the cabinet body, and sound absorption cotton is fixedly arranged on the back of the cabinet door;
the fixed rubber slab that is provided with in bottom of the cabinet body, the fixed buffer spring that is provided with in bottom of rubber slab, fixed cover that is provided with in bottom of buffer spring, logical groove has been seted up to the bottom of fixed cover, the inner wall activity that leads to the groove is provided with the universal wheel, the both sides at fixed cover top are all fixed and are provided with the carrying handle, the both sides of cabinet body bottom are all fixed and are provided with buckle structure.
As an optimized technical scheme of the utility model, the vent has been seted up at the top of the cabinet body, three vent all is located same perpendicular.
As an optimized technical scheme of the utility model, the shape size of bleeder vent agrees with each other with the shape size of dust cover, the material of dust cover is the active carbon material.
As an optimal technical scheme of the utility model, inhale the cotton shape of sound and be the type of returning, inhale the cotton outer wall activity of sound and set up the inner wall at the cabinet body.
As a preferred technical scheme of the utility model, the rubber slab is provided with fixed cover through the buffer spring activity, fixed cover is the fixed cover of rubber, the fixed bottom that sets up at the cabinet body in top of universal wheel, the bottom of fixed cover is run through and the bottom of fixed cover is extended to the bottom of universal wheel.
As an optimized technical scheme of the utility model, the cabinet body is provided with fixed cover through buckle structure is fixed, the outer wall of carrying handle is fixed and is provided with the sponge cover.
Compared with the prior art, the utility model provides a big data processing equipment based on convolution neural network model possesses following beneficial effect:
1. this big data processing equipment based on convolution neural network model, through setting up the fan and leading to external environment with the heat that the internal portion of cabinet gived off, and bleeder vent and dust cover can also prevent to get into the internal portion of cabinet after starting the fan when carrying out the heat dissipation to the internal portion of cabinet, strengthen the heat dissipation and the dustproof ability of equipment simultaneously, prolong the life of equipment, ensure equipment normal use.
2. This big data processing equipment based on convolution neural network model through setting up the sound cotton of inhaling of returning the type can reduce the produced noise of big data processing equipment during operation, and the vibration of the cabinet body can effectively be cushioned in the activity setting of rubber slab and fixed cover, and the universal wheel run through also can make things convenient for people to the displacement of the cabinet body and fix in addition, and the people of being convenient for remove the cabinet body.
Drawings
Fig. 1 is a schematic structural view of the present invention;
FIG. 2 is a rear view of the cabinet door structure of the present invention;
fig. 3 is a front sectional view of the fixing sleeve structure of the present invention.
In the figure: 1. a cabinet body; 2. installing a box; 3. a vent; 4. a fan; 5. air holes are formed; 6. a dust cover; 7. a cabinet door; 8. sound-absorbing cotton; 9. a rubber plate; 10. a buffer spring; 11. fixing a sleeve; 12. a through groove; 13. a universal wheel; 14. a carrying handle; 15. a buckle structure.
Detailed Description
The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments in the present invention, all other embodiments obtained by a person skilled in the art without creative work belong to the protection scope of the present invention.
Referring to fig. 1-3, the utility model discloses a big data processing device based on a convolutional neural network model, which comprises a cabinet body 1, wherein an installation box 2 is fixedly arranged at the top of the cabinet body 1, vent holes 3 are respectively arranged at the top and the bottom of the installation box 2, a fan 4 is fixedly arranged inside the installation box 2, vent holes 5 are respectively arranged at both sides of the cabinet body 1, a dust cover 6 is fixedly arranged on the inner wall of the vent hole 5, a cabinet door 7 is movably arranged at the front of the cabinet body 1, sound-absorbing cotton 8 is fixedly arranged at the back of the cabinet door 7, a rubber plate 9 is fixedly arranged at the bottom of the cabinet body 1, a buffer spring 10 is fixedly arranged at the bottom of the rubber plate 9, a fixed sleeve 11 is fixedly arranged at the bottom of the buffer spring 10, a through groove 12 is arranged at the bottom of the fixed sleeve 11, and a universal wheel 13 is movably arranged on the inner wall of the through groove 12, handles 14 are fixedly arranged on two sides of the top of the fixed sleeve 11, and fastening structures 15 are fixedly arranged on two sides of the bottom of the cabinet body 1.
Specifically, vent 3 has been seted up at the top of the cabinet body 1, three vent 3 all are located same perpendicular.
In this embodiment, utilize three vent 3 that are located same perpendicular to can ensure fan 4's normal use to lead the heat that the cabinet body 1 inside gived off to external environment through fan 4, the heat-sinking capability of reinforcing device, and the design of install bin 2 can ensure the normal operating of the cabinet body 1 inside, ensure that the big data processing equipment of convolutional neural network model can play a role.
Specifically, the shape and the size of the air holes 5 are matched with those of the dust cover 6, and the dust cover 6 is made of activated carbon.
In this embodiment, bleeder vent 5 and the dust cover 6 that the shape size agrees with each other can also prevent to get into 1 insidely of the cabinet body starting fan 4 back outside dust when carrying out the heat dissipation to 1 inside of the cabinet body, strengthen the heat dissipation and the dustproof ability of equipment simultaneously, prolong the life of equipment to the dust cover 6 of active carbon material can be convenient for people to change, maintains the dustproof ability of equipment.
Specifically, inhale the shape of sound cotton 8 and be the type of returning, inhale the outer wall activity of sound cotton 8 and set up the inner wall at the cabinet body 1.
In this embodiment, the sound of returning the type is cotton 8 sets up the gap of airtight cabinet body 1 and cabinet door 7 through the activity with cabinet body 1 inner wall, but also can reduce the produced noise of big data processing equipment during operation, and dustproof noise reduction effect is obvious.
Specifically, the rubber plate 9 is movably provided with a fixed sleeve 11 through a buffer spring 10, the fixed sleeve 11 is a rubber fixed sleeve, the top of the universal wheel 13 is fixedly arranged at the bottom of the cabinet body 1, and the bottom of the universal wheel 13 penetrates through the top of the fixed sleeve 11 and extends out of the bottom of the fixed sleeve 11.
In this embodiment, the vibration of the cabinet body 1 can be effectively buffered by the movable arrangement of the rubber plate 9 and the fixed sleeve 11, and the balance of the cabinet body 1 can be ensured by the fixed sleeve 11 of the rubber, so that the deviation phenomenon can not occur to the internal equipment, and the universal wheels 13 can also facilitate the displacement and fixation of the cabinet body 1 by people, thereby facilitating the movement of the cabinet body 1 by people.
Specifically, the cabinet body 1 is fixedly provided with a fixed sleeve 11 through a buckle structure 15, and the outer wall of the handle 14 is fixedly provided with a sponge sleeve.
In this embodiment, make buckle structure 15 can the stationary cabinet body 1 and fixed cover 11 through mentioning carrying handle 14 to contact the bottom of universal wheel 13 with ground, the people of being convenient for remove cabinet body 1, and after removing the completion, the accessible is relieved buckle structure 15 and is made fixed cover 11 carry out the whereabouts of perpendicular angle, thereby supplementary stationary cabinet body 1, make the equilibrium-keeping of cabinet body 1, and the setting of sponge cover can protect people's palm, is convenient for mention.
The utility model discloses a theory of operation and use flow: when in use, the fixed sleeve 11 is lifted by the carrying handle 14, so that the cabinet body 1 can be connected with the buckle structures 15 at two sides of the fixed sleeve 11, people can conveniently displace the cabinet body 1 by the universal wheels 13, after the displacement is completed, people can enable the universal wheels 13 to be arranged on the inner wall of the through groove 12 by removing the buckle structures 15, the fixed sleeve 11 is convenient to stabilize and keep the balance of the cabinet body 1, so that the data processing equipment inside the cabinet body 1 can be normally used, and when the big data processing equipment works, the fan 4 at the top of the cabinet body 1 can discharge the heat dissipated inside the cabinet body 1 to the outside of the cabinet body 1 through the vent 3, the air holes 5 at two sides of the cabinet body 1 can prevent external dust from entering the cabinet body 1 while dissipating heat, the dustproof heat dissipation capacity of the equipment is enhanced, and the sound-absorbing cotton 8 and the rubber plate 9 absorb the noise of the cabinet body 1, thereby creating a good working environment, at this time, the large data processing apparatus operates normally.
To sum up, this big data processing equipment based on convolution neural network model, through setting up the cotton 8 of inhaling of type of returning, can reduce the produced noise of big data processing equipment during operation, the vibration of the effective buffering cabinet body 1 of activity setting of rubber slab 9 and fixed cover 11, the universal wheel 13 run through also can make things convenient for people to the displacement of the cabinet body 1 with fixed in addition, the people of being convenient for remove the cabinet body 1.
It should be noted that, in this document, terms such as "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. The utility model provides a big data processing equipment based on convolutional neural network model, includes the cabinet body (1), its characterized in that: the cabinet is characterized in that an installation box (2) is fixedly arranged at the top of the cabinet body (1), ventilation openings (3) are formed in the top and the bottom of the installation box (2), a fan (4) is fixedly arranged inside the installation box (2), air holes (5) are formed in two sides of the cabinet body (1), a dust cover (6) is fixedly arranged on the inner wall of each air hole (5), a cabinet door (7) is movably arranged on the front side of the cabinet body (1), and sound absorption cotton (8) is fixedly arranged on the back side of the cabinet door (7);
the fixed rubber slab (9) that is provided with in bottom of the cabinet body (1), the fixed buffer spring (10) that is provided with in bottom of rubber slab (9), the fixed cover (11) that is provided with in bottom of buffer spring (10), logical groove (12) have been seted up to the bottom of fixed cover (11), the inner wall activity that leads to groove (12) is provided with universal wheel (13), the both sides at fixed cover (11) top are all fixed and are provided with carrying handle (14), the both sides of the cabinet body (1) bottom are all fixed and are provided with buckle structure (15).
2. The big data processing device based on the convolutional neural network model as claimed in claim 1, wherein: the top of the cabinet body (1) is provided with a vent (3), and the three vents (3) are all located on the same vertical plane.
3. The big data processing device based on the convolutional neural network model as claimed in claim 1, wherein: the shape and the size of the air holes (5) are matched with those of the dust cover (6), and the dust cover (6) is made of activated carbon.
4. The big data processing device based on the convolutional neural network model as claimed in claim 1, wherein: the shape of the sound-absorbing cotton (8) is a clip shape, and the outer wall of the sound-absorbing cotton (8) is movably arranged on the inner wall of the cabinet body (1).
5. The big data processing device based on the convolutional neural network model as claimed in claim 1, wherein: rubber slab (9) are provided with fixed cover (11) through buffer spring (10) activity, fixed cover (11) are the fixed cover of rubber, the fixed bottom that sets up at the cabinet body (1) in top of universal wheel (13), the bottom of universal wheel (13) runs through the top of fixed cover (11) and extends the bottom of fixed cover (11).
6. The big data processing device based on the convolutional neural network model as claimed in claim 1, wherein: the cabinet body (1) is fixedly provided with a fixed sleeve (11) through a buckle structure (15), and the outer wall of the lifting handle (14) is fixedly provided with a sponge sleeve.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202120463161.XU CN214751669U (en) | 2021-03-03 | 2021-03-03 | Big data processing equipment based on convolutional neural network model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202120463161.XU CN214751669U (en) | 2021-03-03 | 2021-03-03 | Big data processing equipment based on convolutional neural network model |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN214751669U true CN214751669U (en) | 2021-11-16 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202120463161.XU Expired - Fee Related CN214751669U (en) | 2021-03-03 | 2021-03-03 | Big data processing equipment based on convolutional neural network model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN214751669U (en) |
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2021
- 2021-03-03 CN CN202120463161.XU patent/CN214751669U/en not_active Expired - Fee Related
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| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20211116 |
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| CF01 | Termination of patent right due to non-payment of annual fee |