Method for obtaining electric energy from wireless ionosphere by super artificial intelligence robotic panda

Abstract

The invention discloses a method for acquiring electric energy from a wireless ionosphere by a super artificial intelligence machine panda, and belongs to the technical field of artificial intelligence and energy acquisition, which comprises the following steps of: receiving electromagnetic waves of the wireless ionosphere by adopting an antenna with a specific structure and parameters; according to the invention, a stable and continuous energy source is provided for the super artificial intelligence robotic panda through electric energy in the wireless ionosphere, so that the super artificial intelligence robotic panda is not limited by limited storage and supply uncertainty of traditional energy; weak energy in the wireless ionosphere can be efficiently converted into available electric energy, the energy utilization efficiency is greatly improved, energy waste is reduced, the super artificial intelligence machine panda can run at full power through stable and sufficient energy supply, the strong computing and processing capacity of the super artificial intelligence machine panda is fully played, the intelligent level and the working efficiency are improved, and the application prospect is wide. And powerful support is provided for more complex tasks and applications.

Description

Technical Field

[0001] The present invention belongs to the technical field of artificial intelligence and energy acquisition, and specifically refers to a method for a super artificial intelligence machine panda to obtain electrical energy from a radio ionosphere. Background Art

[0002] In the current era of booming artificial intelligence, energy supply has become a key factor restricting its further development. Traditional energy sources, such as fossil fuels and nuclear energy, not only face the dilemma of limited resources, but also bring serious environmental pollution problems. At the same time, the radio ionosphere contains abundant electrical energy, but existing technical means are difficult to convert it into practical electrical energy on a large scale and efficiently to meet the growing energy demand;

[0003] However, there are still some defects in the existing super artificial intelligence machine panda obtaining electricity from the radio ionosphere. The existing super artificial intelligence machine panda obtaining electricity from the radio ionosphere lacks the problem of long-term stable energy supply. Therefore, a method for a super artificial intelligence machine panda to obtain electricity from the radio ionosphere is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a method for a super artificial intelligence robot panda to obtain electrical energy from the radio ionosphere to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for a super artificial intelligence robot panda to obtain electric energy from a radio ionosphere, comprising the following steps:

[0006] S1. Using antennas with specific structures and parameters to receive electromagnetic waves from the radio ionosphere;

[0007] S2, convert the received AC electromagnetic waves into DC electrical energy through an efficient rectifier;

[0008] S3, filtering the DC power through a filter to remove clutter and interference;

[0009] S4. Based on the optimized energy conversion algorithm, the working parameters of the energy harvesting device are adjusted in real time to adapt to radio signals of different strengths and frequencies;

[0010] S5. Through the intelligent control and management system, dynamically adjust the energy collection and use strategy according to the energy demand and collection situation of the super artificial intelligence machine panda;

[0011] S6. Use high-performance batteries or supercapacitors to store the acquired electrical energy and achieve stable energy release through control strategies.

[0012] Wherein, the S1 adopts an antenna with specific structure and parameters to receive electromagnetic waves from the radio ionosphere; the antenna is a wide-band, high-gain array antenna used to capture electromagnetic waves of multiple frequencies.

[0013] The antenna adopts a wide-band, high-gain antenna design, which can effectively capture electromagnetic waves of various frequencies widely distributed in the radio ionosphere. The antenna is composed of multiple array units to increase the receiving area and signal strength.

[0014] Wherein, S2 converts the received AC electromagnetic waves into DC electric energy through a high-efficiency rectifier; the rectifier is a Schottky diode rectifier with low on-resistance and high reverse breakdown voltage.

[0015] The rectifier uses a high-efficiency Schottky diode rectifier, which can quickly convert the AC electromagnetic waves received by the antenna into DC power. The rectifier has a low on-resistance and a high reverse breakdown voltage to ensure efficient rectification effect and stable working performance.

[0016] Wherein, the S3 filters the DC power through a filter to remove clutter and interference; the filter is an LC filter, which is used to remove clutter and interference signals in the DC power.

[0017] The filter adopts a high-performance LC filter to remove clutter and interference signals in the rectified DC power to ensure the purity of the output power.

[0018] These components work together. The antenna is responsible for receiving electromagnetic waves from the radio ionosphere, the rectifier converts the AC signal into DC, and the filter purifies the DC power, thereby achieving effective collection of radio ionosphere energy.

[0019] Among them, S4, based on the optimized energy conversion algorithm, adjusts the working parameters of the energy collection device in real time to adapt to radio signals of different intensities and frequencies; the energy conversion algorithm is based on deep learning and adaptive control theory to analyze the characteristics of radio signals in real time and adjust the working parameters of the energy collection device.

[0020] The algorithm is based on deep learning and adaptive control theory, and can analyze the frequency, intensity, phase and other characteristics of the received radio signal in real time; by constantly adjusting the working parameters of the rectifier and filter, the energy conversion process is always kept in the optimal state. For example, when a high-intensity low-frequency signal is received, the algorithm will automatically reduce the on-resistance of the rectifier and increase the value of the filter capacitor to achieve higher energy conversion efficiency; while for high-frequency and low-intensity signals, the opposite adjustment strategy is adopted;

[0021] Among them, S5, through the intelligent control and management system, dynamically adjusts the energy collection and use strategy according to the energy demand and collection situation of the super artificial intelligence machine panda; the intelligent control and management system monitors the energy demand of the super artificial intelligence machine panda and the working status of the collection device in real time, and performs self-monitoring, fault diagnosis and optimization operation.

[0022] The intelligent control system of the super artificial intelligence robot panda integrates advanced sensors and data analysis modules, which can monitor the energy demand of the robot panda and the working status of the collection device in real time;

[0023] When the energy demand is high and the collected energy is insufficient, the system will automatically adjust the working mode of the robot panda to reduce the energy consumption of non-critical tasks; at the same time, the energy collection device will be optimized, such as adjusting the direction and angle of the antenna to obtain a stronger signal;

[0024] The self-monitoring function provides early warning of faults by real-time monitoring of voltage, current, temperature and other parameters of key components. The fault diagnosis module can quickly locate faulty components and provide corresponding repair suggestions. In terms of optimized operation, the system will continuously optimize energy collection and use strategies based on historical data and real-time conditions to improve overall energy efficiency.

[0025] Among them, the S6 uses a high-performance battery or supercapacitor to store the acquired electrical energy and realizes stable energy release through a control strategy; the battery is a lithium-ion battery, and the supercapacitor can be quickly charged and discharged.

[0026] The battery uses a high-performance lithium-ion battery or a supercapacitor as an energy storage unit. Lithium-ion batteries have high energy density and can store a large amount of electrical energy for a long time; supercapacitors have the characteristics of fast charging and discharging, and are suitable for dealing with sudden high energy demands.

[0027] Among them, S6, the energy release control strategy can intelligently adjust the discharge current and voltage according to the real-time energy consumption demand of the super artificial intelligence machine panda and the remaining power of the battery / supercapacitor.

[0028] The energy release control strategy is based on the real-time energy consumption demand of the robot and the remaining power of the battery / supercapacitor. The system will intelligently adjust the discharge current and voltage to ensure stable power output. For example, when the robot performs complex computing tasks, the discharge current will be increased to meet the instantaneous high energy consumption demand; while in standby mode, the discharge current will be reduced to extend the battery life.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. The present invention provides a stable and continuous energy source for the super artificial intelligence robot panda through the electric energy in the radio ionosphere, so that it is no longer restricted by the limited reserves and supply uncertainty of traditional energy;

[0031] 2. The present invention can efficiently convert the weak energy in the radio ionosphere into usable electrical energy through a well-designed energy collection device and an optimized conversion algorithm, greatly improving energy utilization efficiency and reducing energy waste;

[0032] 3. The present invention enables the super artificial intelligence machine panda to run at full power through a stable and sufficient energy supply, giving full play to its powerful computing and processing capabilities, improving its intelligence level and work efficiency, and providing strong support for more complex tasks and applications;

[0033] 4. The present invention does not produce any harmful substances or greenhouse gas emissions during the entire energy acquisition and conversion process, has no negative impact on the environment, and is fully in line with the green concept of sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 The present invention is a flowchart of a method for a super artificial intelligence machine panda to obtain electrical energy from the radio ionosphere. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Example

[0037] See also Figure 1 As shown, the present invention provides a technical solution: comprising the following steps:

[0038] S1. Using antennas with specific structures and parameters to receive electromagnetic waves from the radio ionosphere;

[0039] S2, convert the received AC electromagnetic waves into DC electrical energy through an efficient rectifier;

[0040] S3, filtering the DC power through a filter to remove clutter and interference;

[0041] S4. Based on the optimized energy conversion algorithm, the working parameters of the energy harvesting device are adjusted in real time to adapt to radio signals of different strengths and frequencies;

[0042] S5. Through the intelligent control and management system, dynamically adjust the energy collection and use strategy according to the energy demand and collection situation of the super artificial intelligence machine panda;

[0043] S6. Use high-performance batteries or supercapacitors to store the acquired electrical energy and achieve stable energy release through control strategies.

[0044] Wherein, the S1 adopts an antenna with specific structure and parameters to receive electromagnetic waves from the radio ionosphere; the antenna is a wide-band, high-gain array antenna used to capture electromagnetic waves of multiple frequencies.

[0045] The antenna adopts a wide-band, high-gain antenna design, which can effectively capture electromagnetic waves of various frequencies widely distributed in the radio ionosphere. The antenna is composed of multiple array units to increase the receiving area and signal strength.

[0046] Wherein, S2 converts the received AC electromagnetic waves into DC electric energy through a high-efficiency rectifier; the rectifier is a Schottky diode rectifier with low on-resistance and high reverse breakdown voltage.

[0047] The rectifier uses a high-efficiency Schottky diode rectifier, which can quickly convert the AC electromagnetic waves received by the antenna into DC power. The rectifier has a low on-resistance and a high reverse breakdown voltage to ensure efficient rectification effect and stable working performance.

[0048] Wherein, the S3 filters the DC power through a filter to remove clutter and interference; the filter is an LC filter, which is used to remove clutter and interference signals in the DC power.

[0049] The filter adopts a high-performance LC filter to remove clutter and interference signals in the rectified DC power to ensure the purity of the output power.

[0050] These components work together. The antenna is responsible for receiving electromagnetic waves from the radio ionosphere, the rectifier converts the AC signal into DC, and the filter purifies the DC power, thereby achieving effective collection of radio ionosphere energy.

[0051] Among them, S4, based on the optimized energy conversion algorithm, adjusts the working parameters of the energy collection device in real time to adapt to radio signals of different intensities and frequencies; the energy conversion algorithm is based on deep learning and adaptive control theory to analyze the characteristics of radio signals in real time and adjust the working parameters of the energy collection device.

[0052] The algorithm is based on deep learning and adaptive control theory, and can analyze the frequency, strength, phase and other characteristics of the received radio signal in real time; by constantly adjusting the operating parameters of the rectifier and filter, the energy conversion process is always kept in the optimal state. For example, when a high-intensity low-frequency signal is received, the algorithm will automatically reduce the on-resistance of the rectifier and increase the value of the filter capacitor to achieve higher energy conversion efficiency; while for high-frequency and low-intensity signals, the opposite adjustment strategy is adopted;

[0053] Among them, S5, through the intelligent control and management system, dynamically adjusts the energy collection and use strategy according to the energy demand and collection situation of the super artificial intelligence machine panda; the intelligent control and management system monitors the energy demand of the super artificial intelligence machine panda and the working status of the collection device in real time, and performs self-monitoring, fault diagnosis and optimization operation.

[0054] The intelligent control system of the super artificial intelligence robot panda integrates advanced sensors and data analysis modules, which can monitor the energy demand of the robot panda and the working status of the collection device in real time;

[0055] When the energy demand is high and the collected energy is insufficient, the system will automatically adjust the working mode of the robot panda to reduce the energy consumption of non-critical tasks; at the same time, the energy collection device will be optimized, such as adjusting the direction and angle of the antenna to obtain a stronger signal;

[0056] The self-monitoring function provides early warning of faults by real-time monitoring of voltage, current, temperature and other parameters of key components. The fault diagnosis module can quickly locate faulty components and provide corresponding repair suggestions. In terms of optimized operation, the system will continuously optimize energy collection and use strategies based on historical data and real-time conditions to improve overall energy efficiency.

[0057] Among them, the S6 uses a high-performance battery or supercapacitor to store the acquired electrical energy and realizes stable energy release through a control strategy; the battery is a lithium-ion battery, and the supercapacitor can be quickly charged and discharged.

[0058] The battery uses a high-performance lithium-ion battery or a supercapacitor as an energy storage unit. Lithium-ion batteries have high energy density and can store a large amount of electrical energy for a long time; supercapacitors have the characteristics of fast charging and discharging, and are suitable for dealing with sudden high energy demands.

[0059] Among them, S6, the energy release control strategy can intelligently adjust the discharge current and voltage according to the real-time energy consumption demand of the super artificial intelligence machine panda and the remaining power of the battery / supercapacitor.

[0060] The energy release control strategy is based on the real-time energy consumption demand of the robot and the remaining power of the battery / supercapacitor. The system will intelligently adjust the discharge current and voltage to ensure stable power output. For example, when the robot performs complex computing tasks, the discharge current will be increased to meet the instantaneous high energy consumption demand; while in standby mode, the discharge current will be reduced to extend the battery life.

[0061] S1. Device installation:

[0062] The installation of the device includes the installation of antennas, rectifiers and filters. Antenna: Choose an open, unobstructed location and install the antenna array at a high place to ensure that it can receive radio signals from all directions well. During installation, the angle and direction of the antenna need to be precisely adjusted to align with the main energy source of the radio ionosphere.

[0063] Installation of rectifier and filter: Install the rectifier and filter close to the antenna to reduce the loss during signal transmission. Pay attention to electromagnetic shielding and heat dissipation during installation to ensure stable operation of the components.

[0064] S2. Debugging:

[0065] Adjustment, signal detection and calibration after installation: After installation, start the system for initial debugging. Use professional testing equipment to detect the strength and frequency of the received radio signal, and fine-tune the angle and direction of the antenna to obtain the best reception effect;

[0066] Energy conversion efficiency test: Perform performance tests on rectifiers and filters, and adjust operating parameters to optimize their energy conversion efficiency. At the same time, verify and optimize the energy conversion algorithm to ensure that it can accurately adapt to different signal conditions.

[0067] S3. Run:

[0068] Real-time monitoring and data recording: During the operation of the system, key parameters such as the working status of the energy harvesting device, energy conversion efficiency, battery / supercapacitor power, etc. are continuously monitored and the data is recorded in real time.

[0069] Adaptive adjustment: Based on real-time monitoring data, the intelligent control system automatically adjusts energy collection and use strategies. For example, when the radio signal strength changes, the antenna gain and rectifier parameters are adjusted in time; when the energy consumption demand of the robot panda changes, the energy release rate is dynamically adjusted.

[0070] S4. Maintenance:

[0071] Regular inspection: Regularly conduct a comprehensive inspection of the energy harvesting device, including the connection status of the antenna, the working performance of the rectifier and filter, the health of the battery / supercapacitor, etc.

[0072] Parts replacement: For aged or damaged parts, timely replacement and repair are carried out. At the same time, the device is upgraded and improved in a timely manner according to technological development and actual operation results.

[0073] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0074] The present invention and its embodiments are described above, and such description is not restrictive. The drawings show only one embodiment of the present invention, and the actual structure is not limited thereto. In short, if ordinary technicians in the field are inspired by it, without departing from the purpose of the invention, they can design a structure and embodiment similar to the technical solution without creativity, which should belong to the protection scope of the present invention.

Claims

1. A method for a super artificial intelligence machine panda to obtain electrical energy from the radio ionosphere, characterized in that: The following steps are involved: S1. Using antennas with specific structures and parameters to receive electromagnetic waves from the radio ionosphere; S2, convert the received AC electromagnetic waves into DC electrical energy through an efficient rectifier; S3, filtering the DC power through a filter to remove clutter and interference; S4. Based on the optimized energy conversion algorithm, the working parameters of the energy harvesting device are adjusted in real time to adapt to radio signals of different strengths and frequencies; S5. Through the intelligent control and management system, dynamically adjust the energy collection and use strategy according to the energy demand and collection situation of the super artificial intelligence machine panda; S6. Use high-performance batteries or supercapacitors to store the acquired electrical energy and achieve stable energy release through control strategies.

2. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: The S1 adopts an antenna with specific structure and parameters to receive electromagnetic waves from the radio ionosphere; the antenna is a wide-band, high-gain array antenna used to capture electromagnetic waves of multiple frequencies.

3. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: The S2 converts the received AC electromagnetic waves into DC electric energy through a high-efficiency rectifier; the rectifier is a Schottky diode rectifier with low on-resistance and high reverse breakdown voltage.

4. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: The S3 filters the DC power through a filter to remove clutter and interference; the filter is an LC filter, which is used to remove clutter and interference signals in the DC power.

5. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: S4, based on the optimized energy conversion algorithm, adjusts the working parameters of the energy harvesting device in real time to adapt to radio signals of different strengths and frequencies; The energy conversion algorithm is based on deep learning and adaptive control theory to analyze the characteristics of radio signals in real time and adjust the working parameters of the energy harvesting device.

6. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: The S5 dynamically adjusts the energy collection and use strategy according to the energy demand and collection situation of the super artificial intelligence machine panda through the intelligent control and management system; the intelligent control and management system monitors the energy demand of the super artificial intelligence machine panda and the working status of the collection device in real time, and performs self-monitoring, fault diagnosis and optimization operation.

7. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: The S6 uses a high-performance battery or supercapacitor to store the acquired electrical energy and realizes stable energy release through a control strategy; the battery is a lithium-ion battery, and the supercapacitor can be quickly charged and discharged.

8. The method for obtaining electric energy from the radio ionosphere by a super artificial intelligence machine panda according to claim 1, characterized in that: The S6, energy release control strategy can intelligently adjust the discharge current and voltage according to the real-time energy consumption demand of the super artificial intelligence machine panda and the remaining power of the battery / supercapacitor.

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