CN216112857U

CN216112857U - Quality safety early warning device based on convolutional neural network model

Info

Publication number: CN216112857U
Application number: CN202120465895.1U
Authority: CN
Inventors: 赵冉冉; 冯蕾; 廖景行
Original assignee: China National Institute of Standardization
Current assignee: China National Institute of Standardization
Priority date: 2021-03-03
Filing date: 2021-03-03
Publication date: 2022-03-22
Anticipated expiration: 2031-03-03

Abstract

The utility model discloses a quality safety early warning device based on a convolutional neural network model, and relates to the technical field of safety early warning. The device comprises a movable base, a height adjusting mechanism and a device body, wherein the height adjusting mechanism is fixedly mounted at the top of the movable base, and the device body is fixedly mounted at the top end of the height adjusting mechanism. This quality safety early warning device based on convolution neural network model, through setting up the removal base, utilize first motor to drive two driving gear synchronous rotations through the pivot, make the driving gear drive driven gear carry out elevating movement through fly leaf linkage contact floor, make two contact floor lift on with the bottom plate and finally hold in the palm off-ground, make the device follow portable mode and switch into the locate mode, make whole removal process adopt slidingtype displacement, thereby the process of needing the common transport of many staff has been avoided, the advantage of being convenient for to remove has been reached.

Description

Quality safety early warning device based on convolutional neural network model

Technical Field

The utility model relates to the technical field of safety early warning, in particular to a quality safety early warning device based on a 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".

Among the prior art, current quality safety precaution device is bulky for the device's removal is comparatively inconvenient, needs a plurality of staff to carry jointly, and in handling, because the condition of device slope appears easily in the personal physique difference, thereby causes falling of device and the condition that personnel's safety received certain threat.

SUMMERY OF THE UTILITY MODEL

Technical problem to be solved

Aiming at the defects of the prior art, the utility model provides a quality safety early warning device based on a convolutional neural network model, which has the advantage of convenient movement and solves the problem of inconvenient movement.

(II) technical scheme

In order to achieve the purpose of convenient movement, the utility model provides the following technical scheme: a quality safety early warning device based on a convolutional neural network model comprises a movable base, a height adjusting mechanism and a device body, wherein the height adjusting mechanism is fixedly installed at the top of the movable base, and the device body is fixedly installed at the top end of the height adjusting mechanism;

the movable base comprises a bottom plate, four universal wheels are arranged at the bottom of the bottom plate, a first motor and two driving boxes are fixedly mounted at the bottom of the bottom plate, a rotating shaft is fixedly mounted at an output shaft of the first motor, and the other end of the rotating shaft penetrates through the driving box in the middle and extends into the driving box at the rightmost side;

the pivot is located one section fixed surface cover in the drive box inside and has been connect the driving gear, the top meshing of driving gear has driven gear, driven gear's outside swing joint has the fly leaf, the both ends of fly leaf and the inner wall sliding connection of drive box, the bottom fixed mounting of fly leaf has the floor of touching, the bottom that touches the floor is located the below of drive box.

As a preferred technical scheme of the utility model, two sliding rods are fixedly mounted on the inner wall of the driving box, and two ends of the movable plate are respectively connected with the sliding rods in a sliding manner.

As a preferred technical scheme of the utility model, the height adjusting mechanism comprises a containing pipe, a second motor is fixedly installed inside the containing pipe, a rotary table is fixedly installed on an output shaft of the second motor, and a sliding sleeve is connected to the front side of the rotary table in a sliding manner.

As a preferred technical scheme, a transverse plate is fixedly mounted at the top end of the sliding sleeve, a connecting rod is fixedly mounted at the top end of the transverse plate, and the top end of the connecting rod extends to the upper part of the containing pipe and is fixedly mounted with a device body.

As a preferred technical scheme of the utility model, the two ends of the transverse plate are fixedly connected with pulleys, and the other ends of the pulleys are in sliding connection with the inner wall of the containing pipe.

(III) advantageous effects

Compared with the prior art, the utility model provides a quality safety early warning device based on a convolutional neural network model, which has the following beneficial effects:

1. this quality safety early warning device based on convolution neural network model, through setting up the removal base, utilize first motor to drive two driving gear synchronous rotations through the pivot, make the driving gear drive driven gear carry out elevating movement through fly leaf linkage contact floor, make two contact floor lift on with the bottom plate and finally hold in the palm off-ground, make the device follow portable mode and switch into the locate mode, make whole removal process adopt slidingtype displacement, thereby the process of needing the common transport of many staff has been avoided, the advantage of being convenient for to remove has been reached.

2. This quality safety early warning device based on convolution neural network model through setting up height adjustment mechanism, utilizes the second motor to drive the sliding sleeve through the carousel and carries out elevating movement for the sliding sleeve drives the device body through the diaphragm and carries out the altitude mixture control, makes the device body adjust according to user's individual height, makes staff's use more handy, thereby has improved the device's practicality.

Drawings

FIG. 1 is a schematic structural view of the present invention;

FIG. 2 is a front view of the floor structure of the present invention;

FIG. 3 is a side cross-sectional view of the drive pod construction of the present invention;

FIG. 4 is a front cross-sectional view of the receiving tube structure of the present invention.

In the figure: 1. moving the base; 2. a height adjustment mechanism; 3. a device body; 4. a base plate; 5. a first motor; 6. a drive cartridge; 7. a rotating shaft; 8. a driving gear; 9. a driven gear; 10. a movable plate; 11. a slide bar; 12. touching the floor; 13. receiving a tube; 14. a second motor; 15. a turntable; 16. a sliding sleeve; 17. a transverse plate; 18. a connecting rod.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1-4, the utility model discloses a quality safety early warning device based on a convolutional neural network model, which comprises a mobile base 1, a height adjusting mechanism 2 and a device body 3, wherein the top of the mobile base 1 is fixedly provided with the height adjusting mechanism 2, the top end of the height adjusting mechanism 2 is fixedly provided with the device body 3, the mobile base 1 comprises a bottom plate 4, the bottom of the bottom plate 4 is provided with four universal wheels, the bottom of the bottom plate 4 is fixedly provided with a first motor 5 and two driving boxes 6, an output shaft of the first motor 5 is fixedly provided with a rotating shaft 7, the other end of the rotating shaft 7 penetrates through the driving box 6 in the middle and extends to the inside of the rightmost driving box 6, a driving gear 8 is fixedly sleeved on the surface of a section of the rotating shaft 7 positioned in the driving box 6, the top end of the driving gear 8 is engaged with a driven gear 9, the outer side of the driven gear 9 is movably connected with a movable plate 10, two ends of the movable plate 10 are slidably connected with the inner wall of the driving box 6, two sliding rods 11 are fixedly mounted on the inner wall of the driving box 6, two ends of the movable plate 10 are respectively slidably connected with the sliding rods 11, a touch floor 12 is fixedly mounted at the bottom of the movable plate 10, the bottom of the touch floor 12 is positioned below the driving box 6, the movable base 1 is arranged, the first motor 5 is used for driving two driving gears 8 to synchronously rotate through a rotating shaft 7, the driving gears 8 are enabled to drive the driven gear 9 to be connected with the touch floor 12 through the movable plate 10 to move up and down, so that the two touch floors 12 lift the bottom plate 4 and finally support the bottom plate from the ground, the movable mode of the device is switched to the positioning mode, the whole moving process is enabled to adopt sliding displacement, and the process of carrying by multiple workers is avoided, the advantage of convenient movement is achieved.

Specifically, height adjusting mechanism 2 is including accomodating pipe 13, the inside fixed mounting who accomodates pipe 13 has second motor 14, the output shaft fixed mounting of second motor 14 has carousel 15, the front side sliding connection of carousel 15 has sliding sleeve 16, the top fixed mounting of sliding sleeve 16 has diaphragm 17, the equal fixedly connected with pulley in both ends of diaphragm 17, the other end of pulley and the inner wall sliding connection who accomodates pipe 13, the top fixed mounting of diaphragm 17 has connecting rod 18, the top of connecting rod 18 extends to the top and the fixed mounting who accomodates pipe 13 and has device body 3.

In this embodiment, through setting up height adjustment mechanism 2, utilize second motor 14 to drive sliding sleeve 16 through carousel 15 and carry out elevating movement for sliding sleeve 16 drives device body 3 through diaphragm 17 and carries out the altitude mixture control, makes device body 3 can adjust according to user's individual height, makes staff's use more handy, thereby has improved the device's practicality.

The working principle and the using process of the utility model are as follows:

when the device is used, the device is pushed to a proper position, the first motor 5 is started, the first motor 5 drives the rotating shaft 7 to rotate, the rotating shaft 7 drives the two driving gears 8 to rotate, the driving gears 8 rotate and drive the driven gears 9 to descend simultaneously, the driven gears 9 drive the movable plates 10 to move up and down, the movable plates 10 drive the movable contact floors 12 to finally contact with the ground, the two contact floors 12 lift the bottom plate 4 upwards and keep away from the ground, and four universal wheels at the bottom of the bottom plate 4 are supported off the ground, so that the device is switched to a positioning mode;

when the height of the device body 3 needs to be adjusted, the second motor 14 is started, so that the second motor 14 drives the rotary table 15 to rotate, the rotary table 15 is enabled to drive the sliding sleeve 16 to perform lifting motion, the sliding sleeve 16 drives the connecting rod 18 to lift through the transverse plate 17, and the connecting rod 18 is enabled to drive the device body 3 to perform height adjustment.

To sum up, the quality safety early warning device based on the convolutional neural network model has the advantages that by arranging the movable base 1, the first motor 5 is utilized to drive the two driving gears 8 to synchronously rotate through the rotating shaft 7, so that the driving gears 8 drive the driven gears 9 to be connected with the movable plate 10 to move up and down in a linkage manner, the two contact plates 12 lift the bottom plate 4 and finally support the bottom plate off the ground, the movable mode of the device is switched to the positioning mode, the whole moving process is promoted to adopt sliding displacement, the process of carrying multiple workers together is avoided, and the advantage of convenient movement is achieved; through setting up height adjusting mechanism 2, utilize second motor 14 to drive sliding sleeve 16 through carousel 15 and carry out elevating movement for sliding sleeve 16 drives device body 3 through diaphragm 17 and carries out height adjusting, makes device body 3 can adjust according to user's individual height, makes staff's use more handy, thereby has improved the device's practicality.

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 utility model, the scope of which is defined in the appended claims and their equivalents.

Claims

1. The utility model provides a quality safety early warning device based on convolution neural network model, includes mobile base (1), height control mechanism (2) and device body (3), its characterized in that: the top of the movable base (1) is fixedly provided with a height adjusting mechanism (2), and the top end of the height adjusting mechanism (2) is fixedly provided with a device body (3);

the movable base (1) comprises a bottom plate (4), four universal wheels are arranged at the bottom of the bottom plate (4), a first motor (5) and two driving boxes (6) are fixedly mounted at the bottom of the bottom plate (4), a rotating shaft (7) is fixedly mounted at an output shaft of the first motor (5), and the other end of the rotating shaft (7) penetrates through the driving box (6) in the middle and extends into the driving box (6) at the rightmost side;

the utility model discloses a drive box, including pivot (7), driving gear (8) have been cup jointed to the inside one section fixed surface of drive box (6) in pivot (7), the meshing of the top of driving gear (8) has driven gear (9), the outside swing joint of driven gear (9) has fly leaf (10), the both ends of fly leaf (10) and the inner wall sliding connection of drive box (6), the bottom fixed mounting of fly leaf (10) has and touches floor (12), the bottom that touches floor (12) is located the below of drive box (6).

2. The quality safety early warning device based on the convolutional neural network model as claimed in claim 1, wherein: the inner wall fixed mounting of drive box (6) has two slide bars (11), the both ends of fly leaf (10) respectively with slide bar (11) sliding connection.

3. The quality safety early warning device based on the convolutional neural network model as claimed in claim 1, wherein: height adjusting mechanism (2) are including accomodating pipe (13), the inside fixed mounting who accomodates pipe (13) has second motor (14), the output shaft fixed mounting of second motor (14) has carousel (15), the front side sliding connection of carousel (15) has sliding sleeve (16).

4. The quality safety early warning device based on the convolutional neural network model as claimed in claim 3, wherein: the top fixed mounting of sliding sleeve (16) has diaphragm (17), the top fixed mounting of diaphragm (17) has connecting rod (18), the top of connecting rod (18) extends to the top of accomodating pipe (13) and fixed mounting has device body (3).

5. The quality safety early warning device based on the convolutional neural network model as claimed in claim 4, wherein: the both ends of diaphragm (17) are equal fixedly connected with pulley, the other end of pulley and the inner wall sliding connection who accomodates pipe (13).