A monitoring device for load forecasting based on machine learning

Abstract

This utility model relates to the field of load forecasting technology, specifically disclosing a load forecasting monitoring device based on machine learning. It includes a lower casing, with a top hinge connecting the lower casing to an upper casing. A screen is installed inside the upper casing, and a connecting component is installed on the left side of the lower casing. A monitoring unit is fixedly connected inside the lower casing, with a control button and a display screen fixedly connected to the top of the monitoring unit. In use, the monitoring device uses a temperature detector to sense the internal temperature of the unit in real time, automatically triggering fan start / stop and adjusting the number of fans. When the temperature is too high, multiple fans are activated to enhance heat dissipation; when the temperature decreases, fewer fans are activated to save energy. This overcomes the limitations of traditional passive heat dissipation with a single heat sink, effectively preventing performance degradation and lifespan reduction in core components such as the CPU due to heat load accumulation, reducing circuit board aging and chip thermal damage risks, and decreasing equipment maintenance and replacement costs.

Description

Technical Field

[0001] This utility model relates to the field of load forecasting technology, specifically a monitoring device for load forecasting based on machine learning. Background Technology

[0002] Load forecasting is a crucial task in power systems. Accurately estimating electricity demand over a future period is essential for power companies and energy suppliers. It requires the rational planning of power generation, resource allocation, and grid operation to ensure that user demand is met and the power system remains stable. With societal development and the ever-increasing demand for electricity, load forecasting has become increasingly important. By accurately predicting future load demand through machines, power companies can rationally plan the input and output of power generation equipment to ensure that user electricity demand is met during peak periods. This also helps avoid power shortages or surpluses, improves energy efficiency, and reduces costs. Because load characteristic studies require the collection of comprehensive data, in addition to basic power data, environmental information monitoring data also needs to be collected. Existing devices or systems cannot meet the requirements for comprehensive data collection, and data transmission is also subject to the risk of instability.

[0003] In existing technologies, the CPU, the core computing unit inside the monitoring device, generates a large amount of heat load during high-frequency data processing. Traditional heat dissipation solutions mostly rely on a single heat sink, which cannot dissipate heat to the external environment in a timely manner. This poor heat dissipation directly leads to the continuous accumulation of heat inside the device, causing not only an abnormal increase in the surface temperature of the monitoring equipment, but also irreversible thermal damage to the internal precision electronic components, accelerating circuit board aging, shortening chip lifespan, and significantly increasing equipment maintenance and replacement costs. Furthermore, the device cannot dynamically adjust the heat dissipation intensity based on changes in the external ambient temperature and the real-time temperature rise inside the device. In high-temperature environments, the device cannot actively increase its heat dissipation power, exacerbating the risk of overheating. At low temperatures, the heat dissipation components still operate under high load, resulting in unnecessary energy waste. In addition, the device design does not adequately consider dust protection, allowing external dust particles to easily penetrate the device through the heat dissipation channels during operation, adhering to the circuit boards and heat dissipation components, further hindering heat conduction, creating a vicious cycle, and seriously threatening the long-term stable operation and reliability of the device. Therefore, we propose a monitoring device based on machine learning-based load prediction. Utility Model Content

[0004] The purpose of this invention is to provide a monitoring device for load forecasting based on machine learning, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, this utility model provides the following technical solution: a monitoring device for load prediction based on machine learning, comprising a lower shell, a top rotating shaft connecting the lower shell to an upper shell, a screen installed inside the upper shell, a connecting component installed on the left side of the lower shell, a monitoring body fixedly connected inside the lower shell, a control button installed on the top of the monitoring body, a display screen fixedly connected to the top of the monitoring body, a control component on the top of the monitoring body, a mounting frame fixedly connected to the right side of the lower shell, multiple fans fixedly connected inside the mounting frame, a baffle plate connected to the inside of the mounting frame via a rotating shaft, a filter plate installed inside the baffle plate, a locking block fixedly connected to the outside of the baffle plate, an installation groove on the outside of the locking block, a locking slot on the outside of the mounting frame, a sliding groove inside the mounting frame, a spring 1 installed inside the sliding groove, a limit rod slidably connected inside the spring 1, a second baffle plate fixedly connected inside the mounting frame, and two pushing components fixedly connected inside the mounting frame.

[0006] The connecting component is externally fixedly connected to a connecting plate, and multiple connecting ports are installed on the outside of the connecting plate.

[0007] A temperature detector is fixedly connected to the top of the control component, and two buttons are set on the top of the control component.

[0008] The mounting frame is rotatably connected to a first connecting block, which is rotatably connected to a rotating shaft. The rotating shaft is rotatably connected to a second connecting block, and the bottom of the second connecting block is rotatably connected to the top of the first baffle.

[0009] The jacking assembly has a sliding rod inside, and a spring is sleeved on the outside of the sliding rod.

[0010] One side of the second spring is fixedly connected to the outside of the slide rod, and the other side of the second spring is fixedly connected to the outside of the jacking assembly.

[0011] The card block is externally slidably connected inside the card slot, and the outside of the card block is in contact with the outside of the limit rod.

[0012] This utility model has at least the following beneficial effects:

[0013] In use, this invention utilizes a monitoring device that senses the internal temperature of the machine in real time via a temperature detector. It automatically triggers fan start / stop and adjusts the number of fans in operation. When the temperature is too high, multiple fans are activated to enhance heat dissipation; when the temperature decreases, fewer fans are used to save energy. This overcomes the limitations of traditional passive cooling with a single heatsink, effectively preventing performance degradation and lifespan reduction in core components such as the CPU due to heat load accumulation. It also reduces the aging rate of circuit boards and the risk of thermal damage to chips, decreasing equipment maintenance and replacement costs. Furthermore, it ensures stable operation in high-frequency data processing scenarios. External air enters the machine after being filtered for dust and impurities, preventing dust adhesion from interfering with heat dissipation and damaging electronic components, thus forming a virtuous cycle of heat dissipation. When removing the filter plate, push the limit rod downwards to compress spring one, and the push assembly, together with spring two and the slide rod, will pop open baffle one. The filter plate can be quickly removed for cleaning or replacement without tools, making the operation convenient and efficient. It ensures the continuous effectiveness of the dustproof function and extends the service life of the internal components of the equipment. The monitoring object can be quickly connected through the connection port, and the parameter settings can be completed by operating the control button and display screen. The monitoring results are displayed on the screen in real time. The operation interface is user-friendly and intuitive. Combined with machine learning algorithms for in-depth analysis of load data, it can achieve more accurate prediction and monitoring, providing users with reliable data support. At the same time, the intelligent heat dissipation and dustproof design provide a stable hardware environment for high-precision monitoring, ensuring the accuracy of data acquisition and processing. Attached Figure Description

[0014] Figure 1 This is a schematic diagram of the structure of this utility model;

[0015] Figure 2 This is a schematic diagram of the connecting component structure of this utility model;

[0016] Figure 3 This is a schematic diagram of the structure of the baffle of this utility model;

[0017] Figure 4 This is a schematic diagram of the top-moving component structure of this utility model;

[0018] Figure 5 This is a schematic diagram of the mounting frame of this utility model;

[0019] Figure 6 This utility model Figure 5 Enlarged view of point A in the middle;

[0020] In the diagram: 1. Lower casing; 101. Upper casing; 102. Screen; 2. Connecting assembly; 201. Connecting plate; 202. Connecting port; 3. Monitoring unit; 301. Control button; 302. Display screen; 4. Control assembly; 401. Temperature detector; 402. Button; 5. Mounting frame; 501. Fan; 502. Baffle 1; 503. Filter plate; 504. Locking block; 505. Mounting slot; 506. Locking slot; 507. Slide groove; 508. Spring 1; 509. Limiting rod; 5010. Connecting block 1; 5011. Rotating shaft; 5012. Connecting block 2; 5013. Baffle 2; 6. Pushing assembly; 601. Spring 2; 602. Slide rod. Detailed Implementation

[0021] The technical solutions of the present utility model will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of the present utility model, and not all embodiments. Based on the embodiments of the present utility model, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of the present utility model.

[0022] Example 1

[0023] Please see Figures 1 to 6This utility model provides a technical solution: a monitoring device for load prediction based on machine learning, including a lower shell 1, a top rotating shaft connecting the lower shell 1 to an upper shell 101, a screen 102 installed inside the upper shell 101, a connecting component 2 installed on the left side of the lower shell 1, a monitoring body 3 fixedly connected inside the lower shell 1, a control button 301 installed on the top of the monitoring body 3, a display screen 302 fixedly connected to the top of the monitoring body 3, a control component 4 set on the top of the monitoring body 3, a mounting frame 5 fixedly connected to the right side of the lower shell 1, multiple fans 501 fixedly connected inside the mounting frame 5, a baffle 502 connected to the inside of the mounting frame 5, a filter plate 503 set inside the baffle 502, a locking block 504 fixedly connected to the outside of the baffle 502, an installation groove 505 opened on the outside of the locking block 504, a locking groove 506 opened on the outside of the mounting frame 5, and an opening inside the mounting frame 5. The device includes a slide groove 507, inside which is a spring 508. A limit rod 509 is slidably connected inside the spring 508. A baffle 5013 is fixedly connected inside the mounting frame 5, and two actuating components 6 are also fixedly connected inside the mounting frame 5. When the temperature detector 401 detects a temperature rise, it feeds the temperature data back to the monitoring unit 3. The monitoring unit 3 then controls the fan 501 inside the mounting frame 5 to start. After the fan 501 starts, it draws outside air into the lower casing 1 of the unit through the open baffle 502, cooling the monitoring unit 3. During the airflow process, the air passes through the filter plate 503 inside the baffle 502, filtering out dust and impurities to protect the electronic components inside the monitoring unit 3. As the cooling process continues, when the temperature drops to a certain level, the temperature detector 401 sends a signal, and the monitoring unit 3 controls the reduction of the number of fans 501 that are turned on to reduce resource waste.

[0024] The connection component 2 is externally fixedly connected to a connection plate 201, and multiple connection ports 202 are installed on the outside of the connection plate 201. The connection component 2 is installed on the left side of the lower shell 1 of the body and is the interface component for connecting the monitoring device with the external monitoring object. Data transmission and connection with the monitoring object are realized through its external connection ports 202.

[0025] A temperature detector 401 is fixedly connected to the top of the control component 4, and two buttons 402 are provided on the top of the control component 4. The temperature detector 401 is fixedly connected to the top of the control component 4 and is used to detect the temperature inside the lower shell 1 of the machine body in real time and feed the temperature data back to the monitoring body 3 so as to control the start and number of fans 501 according to the temperature.

[0026] The mounting frame 5 is rotatably connected to a connecting block 5010, which is rotatably connected to a rotating shaft 5011. The rotating shaft 5011 is rotatably connected to a connecting block 5012, the bottom of which is rotatably connected to the top of a baffle 502. The connecting block 5010 is rotatably connected inside the mounting frame 5 and is rotatably connected to the rotating shaft 5011. It is used to connect the rotating shaft 5011 and the mounting frame 5, providing rotational support for the rotating shaft 5011. At the same time, when the baffle 502 is opened, it limits the opening angle of the baffle 502 by cooperating with the rotating shaft 5011 and the connecting block 5012.

[0027] The jacking assembly 6 has a sliding rod 602 inside, and a second spring 601 is sleeved on the outside of the sliding rod 602. One side of the second spring 601 is fixedly connected to the outside of the sliding rod 602, and the other side of the second spring 601 is fixedly connected to the outside of the jacking assembly 6. The jacking assembly 6 is fixedly connected inside the mounting frame 5 and is the power component for opening the first baffle 502. The sliding rod 602 is slidably connected inside, and the second spring 601 is set outside. Through the cooperation of the second spring 601 and the sliding rod 602, the jacking of the first baffle 502 is realized.

[0028] The locking block 504 is externally slidably connected inside the locking slot 506, and the outside of the locking block 504 is in contact with the outside of the limiting rod 509. The locking block 504 is fixedly connected to the outside of the baffle 502 and is used to cooperate with the locking slot 506 on the mounting frame 5 to fix the baffle 502. An installation groove 505 is provided on the outside, which cooperates with the limiting rod 509 to control the opening and closing of the baffle 502.

[0029] The working principle of this utility model is as follows: When using the load monitoring device, firstly connect the object to be monitored through the connection port 202 outside the connection component 2, then open the upper shell 101 of the machine body, and set the parameters through the control button 301 and the display screen 302. After monitoring through the monitoring body 3, the monitoring results are presented through the screen 102. Then, when the monitoring body 3 is running and monitoring, the temperature inside the lower shell 1 of the machine body is detected by the temperature detector 401, which causes the fan 501 inside the mounting frame 5 to start. The fan 501 brings the outside air into the lower shell 1 of the machine body through the baffle 502 to blow and dissipate heat from the monitoring body 3. Then, when the outside air enters, it will filter the dust and impurities in the air through the filter plate 503 to prevent the dust and impurities from damaging the monitoring body 3 inside the lower shell 1 of the machine body.

[0030] Then, when it is necessary to replace the filter plate 503 inside the mounting frame 5, simply push the limiting rod 509 down, so that the limiting rod 509 presses the spring 508 down, so that the pushing component 6 pushes the baffle 502, and then the baffle 502 pops open, and then the filter plate 503 can be taken out for cleaning or replacement. At the same time, the temperature detector 401 monitors the internal temperature of the lower shell 1 in real time. If the temperature is too high, multiple fans 501 will be started. If the temperature is low, the number of fans 501 will be reduced to reduce the waste of resources.

[0031] Example 2

[0032] Please see Figures 4 to 5 In this second embodiment, the other structures remain unchanged. The difference from the first embodiment is that when the push assembly 6, together with the second spring 601 and the slide rod 602, pushes the first baffle 502 open, the first baffle 502 will be pulled and connected by the first connecting block 5010 and the rotating shaft 5011 and the second connecting block 5012 to prevent the first baffle 502 from opening too wide.

[0033] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0034] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A monitoring device for load prediction based on machine learning, comprising a lower shell, characterized in that: The lower casing of the unit is connected to the upper casing via a top pivot. A screen is installed inside the upper casing. A connecting component is installed on the left side of the lower casing. A monitoring unit is fixedly connected inside the lower casing. A control button is installed on the top of the monitoring unit. A display screen is fixedly connected to the top of the monitoring unit. A control component is located on the top of the monitoring unit. A mounting frame is fixedly connected to the right side of the lower casing. Multiple fans are fixedly connected inside the mounting frame. A baffle is connected to the mounting frame via a pivot. A filter plate is installed inside the baffle. A locking block is fixedly connected to the outside of the baffle. An installation groove is opened on the outside of the locking block. A locking slot is opened on the outside of the mounting frame. A sliding groove is opened inside the mounting frame. A spring is installed inside the sliding groove. A limit rod is slidably connected inside the spring. A second baffle is fixedly connected inside the mounting frame. Two pushing components are fixedly connected inside the mounting frame.

2. The monitoring device for load forecasting based on machine learning according to claim 1, characterized in that: The connecting component is externally fixedly connected to a connecting plate, and multiple connecting ports are installed on the outside of the connecting plate.

3. The monitoring device for load forecasting based on machine learning according to claim 1, characterized in that: A temperature detector is fixedly connected to the top of the control component, and two buttons are provided on the top of the control component.

4. The monitoring device for load forecasting based on machine learning according to claim 1, characterized in that: The mounting frame is rotatably connected to a first connecting block, which is rotatably connected to a rotating shaft. The rotating shaft is rotatably connected to a second connecting block, whose bottom is rotatably connected to the top of a first baffle.

5. The monitoring device for load forecasting based on machine learning according to claim 1, characterized in that: The jacking assembly has a sliding rod inside, and a spring is sleeved on the outside of the sliding rod.

6. The monitoring device for load forecasting based on machine learning according to claim 5, characterized in that: One side of the second spring is fixedly connected to the outside of the slide rod, and the other side of the second spring is fixedly connected to the outside of the jacking assembly.

7. The monitoring device for load forecasting based on machine learning according to claim 1, characterized in that: The card block is externally slidably connected to the inside of the card slot, and the outside of the card block is in contact with the outside of the limiting rod.

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