CN219656435U - Self-learning ultra-large refrigeration house temperature control device - Google Patents
Self-learning ultra-large refrigeration house temperature control device Download PDFInfo
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- CN219656435U CN219656435U CN202321394016.6U CN202321394016U CN219656435U CN 219656435 U CN219656435 U CN 219656435U CN 202321394016 U CN202321394016 U CN 202321394016U CN 219656435 U CN219656435 U CN 219656435U
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- 238000005057 refrigeration Methods 0.000 title claims abstract description 27
- 230000008859 change Effects 0.000 claims abstract description 10
- 230000017525 heat dissipation Effects 0.000 claims description 8
- 238000005728 strengthening Methods 0.000 claims description 6
- 229910000838 Al alloy Inorganic materials 0.000 claims description 2
- 238000011217 control strategy Methods 0.000 abstract description 13
- 230000033228 biological regulation Effects 0.000 abstract description 6
- 238000000034 method Methods 0.000 abstract description 5
- 230000008569 process Effects 0.000 abstract description 4
- 230000007613 environmental effect Effects 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 4
- 230000003014 reinforcing effect Effects 0.000 description 4
- 238000005265 energy consumption Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 1
- 229910052782 aluminium Inorganic materials 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- Devices That Are Associated With Refrigeration Equipment (AREA)
Abstract
The utility model provides a self-learning ultra-large type refrigeration house temperature control device, which relates to the technical field of refrigeration house temperature control devices and comprises a temperature control host, wherein a host cabinet door is hinged to the front side of the temperature control host, a cabinet door lock is arranged between the front side surface of the host cabinet door and the temperature control host, a control panel is embedded in the middle of the surface of the host cabinet door, radiating fins are arranged on the side surface of the host cabinet door, an indicator lamp, a main control knob and a control button are respectively embedded at two ends of the control panel on the front side of the host cabinet door, radiating strips are arranged at two inner sides of the temperature control host, element supports are arranged between the radiating strips at two sides, learning elements are clamped on the element supports, a continuous self-learning process is adopted, a temperature control strategy is optimized, the accuracy and the efficiency of temperature regulation are improved, thereby realizing the energy-saving aim, the temperature control strategy is automatically adjusted according to the real-time change of the inside and outside of the refrigeration house, and the stability and the consistency of the temperature inside the refrigeration house are kept according to different environments and demands.
Description
Technical Field
The utility model relates to the technical field of refrigeration house temperature control devices, in particular to a self-learning ultra-large refrigeration house temperature control device.
Background
The development background of the self-learning ultra-large type refrigeration house temperature control device is based on continuous pursuit and improvement of refrigeration house temperature control technology, a traditional refrigeration house temperature control device generally adopts a fixed control strategy, cannot adapt to changes of different environmental conditions and operation demands, causes energy consumption waste and inaccuracy of temperature control, automatically learns and adjusts the capacity of self-adaption, optimizes the temperature control strategy, improves the accuracy and energy efficiency of temperature control, and is an important technical problem to be considered in the existing ultra-large type refrigeration house.
Disclosure of Invention
The utility model aims to solve the defects in the prior art and provides a self-learning ultra-large type refrigeration house temperature control device.
In order to achieve the above purpose, the present utility model adopts the following technical scheme: the utility model provides a self-learning ultra-large refrigeration house temperature control device, includes the control by temperature change host computer, the front of control by temperature change host computer articulates there is the host computer cabinet door, be equipped with the cabinet lock between the front side of host computer cabinet door and the control by temperature change host computer, the gomphosis of host computer cabinet door surface middle part has control panel, the host computer cabinet door side is equipped with the fin, the host computer cabinet door openly has pilot lamp, master control knob and control button at control panel's both ends gomphosis respectively, the inside both sides of control by temperature change host computer are equipped with the radiating strip, both sides be equipped with the component support between the radiating strip, the component support block has study component.
Preferably, the vertical mirror symmetry in the back of control by temperature change host computer inner chamber is equipped with the strengthening rib, and the strengthening rib is made for square aluminium alloy to the joint position of strengthening rib front and component support adopts the bolt location.
Preferably, the surface of the heat dissipation strip is uniformly provided with notches, the edges of the notches are outwards offset by 15-30 degrees, and the heat dissipation strip and the end parts of the element support are positioned by adopting buckles.
Preferably, the control panel is built-in with a circuit board, the circuit board is provided with an AI learning chip, and the middle part of the control panel is provided with an LED display screen, and an explosion-proof film is attached to the outside of the display screen.
Preferably, the learning element comprises an AI learning chip and a signal transceiver, the AI learning chip and the signal transceiver are electrically connected with the control panel, and the learning element adopts rectangular module elements, and comprises a chip, a radiating fin and a fixing buckle matched with the element bracket.
Preferably, the indicator lamp, the main control knob and the control button are all electrically connected with the control panel, the indicator lamp is a three-color lamp, the main control knob is an electrodeless knob, and the control button is a spring button.
Advantageous effects
According to the utility model, a continuous self-learning process is adopted, a temperature control strategy is optimized, and the accuracy and efficiency of temperature regulation are improved, so that the energy-saving aim is fulfilled, the energy consumption cost is reduced, and the temperature control strategy can be automatically adjusted according to the real-time changes of the inside and the outside of the refrigeration house so as to adapt to different environments and requirements, and the stability and the consistency of the temperature in the refrigeration house are maintained;
according to the utility model, the temperature can be accurately controlled by adopting the analysis and optimization of the AI learning chip, more accurate temperature regulation is provided, the influence of temperature fluctuation on articles in the refrigerator is avoided, the device is provided with the control panel and the external interface, the remote monitoring and control function can be realized, the temperature of the refrigerator can be monitored and regulated by a user in a remote mode, and the convenience and the flexibility of operation are improved.
Drawings
FIG. 1 is an overall block diagram of the present utility model;
FIG. 2 is a schematic view of the internal structure of the present utility model;
FIG. 3 is a front view of the present utility model;
fig. 4 is an open top view of the present utility model.
Legend description:
1. a temperature control host; 2. a mainframe door; 3. a control button; 4. a cabinet door lock; 5. an indicator light; 6. a master control knob; 7. a heat sink; 8. a control panel; 9. reinforcing ribs; 10. a learning element; 11. a component holder; 12. and a heat radiation strip.
Detailed Description
In order that the manner in which the above recited features, objects and advantages of the present utility model are obtained, a more particular description of the utility model will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. Based on the examples in the embodiments, those skilled in the art can obtain other examples without making any inventive effort, which fall within the scope of the utility model.
Specific embodiments of the present utility model are described below with reference to the accompanying drawings.
First embodiment:
referring to fig. 1-4, a self-learning ultra-large refrigeration house temperature control device comprises a temperature control host 1, wherein reinforcing ribs 9 are arranged in mirror symmetry in the vertical direction on the back of the inner cavity of the temperature control host 1, the reinforcing ribs 9 are made of square aluminum profiles, the connection positions of the front surfaces of the reinforcing ribs 9 and an element bracket 11 are positioned by bolts, a host cabinet door 2 is hinged on the front surface of the temperature control host 1, a cabinet door lock 4 is arranged between the side surface of the front surface of the host cabinet door 2 and the temperature control host 1, a control panel 8 is embedded in the middle of the surface of the host cabinet door 2, a circuit board is arranged in the control panel 8, an AI learning chip is arranged on the circuit board, an LED display screen is arranged in the middle of the control panel 8, an explosion-proof film is adhered outside the display screen, a radiating fin 7 is arranged on the side surface of the host cabinet door 2, an indicator lamp 5, a main control knob 6 and a control button 3 are respectively embedded at two ends of the control panel 8, the pilot lamp 5, master control knob 6 and control button 3 are all with mutual electric connection between the control panel 8, and pilot lamp 5 is the trichromatic lamp, master control knob 6 is the electrodeless knob, control button 3 is the spring button, the inside both sides of control by temperature change host computer 1 are equipped with heat dissipation strip 12, the notch has evenly been seted up on the surface of heat dissipation strip 12, notch edge outside skew 15-30 degrees, and adopt buckle location between the tip of heat dissipation strip 12 and component support 11, be equipped with component support 11 between the heat dissipation strip 12 of both sides, component support 11 block has learning element 10, learning element 10 includes AI study chip and signal transceiver, AI study chip, mutual electric connection between signal transceiver and the control panel 8, and learning element 10 all adopts rectangular module component, including the chip, A heat sink 7 and a fixing clip cooperating with the component holder 11.
The control panel 8 in the temperature control host 1 is internally provided with an AI learning chip which has self-learning capability, the self-learning chip can analyze and learn the optimal temperature control strategy by monitoring and recording information such as temperature data, environmental conditions and system response of a refrigerator, so as to adapt to different environments and demands, the control panel 8 in the temperature control host 1 is provided with an LED display screen for displaying the temperature data and system states, a sensor is integrated in a circuit board of the control panel 8 and used for collecting the temperature data and other environmental parameters of the refrigerator in real time, the data are transmitted to the AI learning chip through a signal transceiver for analysis and processing, the AI learning chip continuously optimizes the temperature control strategy through a self-learning algorithm according to the collected data and preset targets, the AI learning chip can analyze the law of temperature change, adjust the control parameters and perform self-adjustment according to feedback of the system, the accuracy and efficiency of temperature control are gradually improved, the learning element 10 in the device comprises the AI learning chip and the signal transceiver, and the control panel 8 are mutually connected, the self-learning function is jointly realized, and the learning element 10 adopts a rectangular module element, and has fixed buckles and is convenient to install and replace.
The working procedure is as follows:
and (3) data acquisition: the sensor collects temperature data and environmental parameters of the refrigerator in real time and transmits the temperature data and the environmental parameters to the control panel 8;
and (3) data transmission: the control panel 8 transmits the acquired data to the AI learning chip through the signal transceiver;
self-learning algorithm analysis: the AI learning chip analyzes the collected data, runs a self-learning algorithm and continuously optimizes a temperature control strategy;
the control is performed: the control panel 8 controls the operation of the temperature control host 1 according to the optimal control strategy provided by the AI learning chip, and adjusts the temperature of the refrigeration house;
feedback and adjustment: the temperature data fed back by the system is transmitted back to the AI learning chip for evaluating the control effect, and the AI learning chip can adjust the learning strategy and continuously optimize the temperature control according to the feedback information;
the working principle of the self-learning ultra-large refrigeration house temperature control device is based on a self-learning algorithm of an AI learning chip, through continuous data acquisition, analysis and feedback, the device can adaptively adjust a temperature control strategy according to different environments and requirements, the self-learning chip utilizes the electrical connection between the learning element 10 and the control panel 8 to perform data transmission and algorithm operation, the temperature control process is continuously optimized, the accuracy and efficiency of temperature control are improved, and the whole system realizes automatic learning and adaptive temperature control through the cycle of monitoring, learning and feedback so as to meet the temperature regulation requirement of the ultra-large refrigeration house.
To sum up:
1. the continuous self-learning process is adopted, the temperature control strategy is optimized, and the accuracy and the efficiency of temperature regulation are improved, so that the energy-saving aim is fulfilled, the energy consumption cost is reduced, and the temperature control strategy can be automatically adjusted according to the real-time changes of the inside and the outside of the refrigeration house so as to adapt to different environments and requirements, and the stability and the consistency of the temperature in the refrigeration house are maintained;
2. adopt through AI study chip's analysis and optimization, the device can carry out accurate control to the temperature, provides more accurate temperature regulation, avoids the influence of temperature fluctuation to the article in the freezer, and the device is equipped with control panel 8 and external interface, can realize remote monitoring and control function, and the user can monitor and adjust the temperature of freezer through the remote mode, improves the convenience and the flexibility of operation.
In the present utility model, unless expressly stated or limited otherwise, a first feature "above" or "below" a second feature may include both the first and second features being in direct contact, as well as the first and second features not being in direct contact but being in contact with each other through additional features therebetween. Moreover, a first feature being "above," "over" and "on" a second feature includes the first feature being directly above and obliquely above the second feature, or simply indicating that the first feature is higher in level than the second feature. The first feature being "under", "below" and "beneath" the second feature includes the first feature being directly under and obliquely below the second feature, or simply means that the first feature is less level than the second feature.
The foregoing has shown and described the basic principles, principal features and advantages of the utility model. It will be understood by those skilled in the art that the present utility model is not limited to the above-described embodiments, and that the above-described embodiments and descriptions are only preferred embodiments of the present utility model, and are not intended to limit the utility model, and that various changes and modifications may be made therein without departing from the spirit and scope of the utility model as claimed. The scope of the utility model is defined by the appended claims and equivalents thereof.
Claims (6)
1. The utility model provides a self-learning ultra-large type freezer temperature control device, includes control by temperature change host computer (1), its characterized in that: the utility model discloses a temperature control cabinet, including control host computer (1), cabinet door (4) are equipped with between the front side of control host computer (1) and the front side of control host computer (2), the gomphosis of control host computer (2) surface middle part has control panel (8), host computer cabinet door (2) side is equipped with fin (7), the front both ends at control panel (8) gomphosis of host computer (2) have pilot lamp (5), master control knob (6) and control button (3) respectively, the inside both sides of control host computer (1) are equipped with heat dissipation strip (12), both sides be equipped with component support (11) between heat dissipation strip (12), component support (11) block has learning element (10).
2. The self-learning ultra-large refrigeration house temperature control device according to claim 1, wherein: the vertical mirror symmetry in the back of control by temperature change host computer (1) inner chamber is equipped with strengthening rib (9), and strengthening rib (9) are square aluminium alloy and make to the hookup location of strengthening rib (9) front and component support (11) adopts the bolt location.
3. The self-learning ultra-large refrigeration house temperature control device according to claim 1, wherein: the surface of the radiating strip (12) is uniformly provided with notches, the edges of the notches are outwards offset by 15-30 degrees, and the radiating strip (12) and the end part of the element bracket (11) are positioned by adopting a buckle.
4. The self-learning ultra-large refrigeration house temperature control device according to claim 1, wherein: the control panel (8) is internally provided with a circuit board, the circuit board is provided with an AI learning chip, the middle part of the control panel (8) is provided with an LED display screen, and an explosion-proof film is attached to the outside of the display screen.
5. The self-learning ultra-large refrigeration house temperature control device according to claim 1, wherein: the learning element (10) comprises an AI learning chip and a signal transceiver, the AI learning chip and the signal transceiver are electrically connected with the control panel (8), and the learning element (10) adopts rectangular module elements, and comprises a chip, a radiating fin (7) and a fixing buckle matched with the element bracket (11).
6. The self-learning ultra-large refrigeration house temperature control device according to claim 1, wherein: the indicating lamp (5), the main control knob (6) and the control button (3) are all electrically connected with the control panel (8), the indicating lamp (5) is a three-color lamp, the main control knob (6) is an electrodeless knob, and the control button (3) is a spring button.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202321394016.6U CN219656435U (en) | 2023-05-31 | 2023-05-31 | Self-learning ultra-large refrigeration house temperature control device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202321394016.6U CN219656435U (en) | 2023-05-31 | 2023-05-31 | Self-learning ultra-large refrigeration house temperature control device |
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| Publication Number | Publication Date |
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| CN219656435U true CN219656435U (en) | 2023-09-08 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202321394016.6U Active CN219656435U (en) | 2023-05-31 | 2023-05-31 | Self-learning ultra-large refrigeration house temperature control device |
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| Country | Link |
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| CN (1) | CN219656435U (en) |
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2023
- 2023-05-31 CN CN202321394016.6U patent/CN219656435U/en active Active
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