Display cabinet control system and control method thereof

Abstract

The application discloses a display cabinet control system, comprising: a light module for providing a light source in the display cabinet; a light brightness detection module for detecting the light brightness in the display cabinet; a temperature adjustment module for adjusting the temperature in the display cabinet; a temperature detection module for detecting the temperature in the display cabinet; a humidity adjustment module for adjusting the humidity in the display cabinet; and a humidity detection module for adjusting the humidity in the display cabinet. The application can improve the deficiencies of the prior art and improve the joint control precision of the light, temperature and humidity in the display cabinet.

Description

Technical Field

[0001] This invention relates to the field of automatic control technology, and in particular to a display cabinet control system and its control method. Background Technology

[0002] To protect valuable exhibits, they need to be placed in display cases. The lighting, temperature, and humidity inside these cases need to be automatically controlled according to the exhibits' display requirements. The lighting, temperature, and humidity inside the display cases are interconnected, and existing automatic control systems lack sufficient precision in controlling these three interrelated parameters. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a display cabinet control system and control method, which can overcome the shortcomings of the prior art and improve the accuracy of joint control of light and temperature and humidity inside the display cabinet.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows.

[0005] A display case control system, comprising,

[0006] The lighting module is used to provide illumination to the inside of the display case;

[0007] The illumination detection module is used to detect the illumination level inside the display case;

[0008] Temperature control module, used to regulate the temperature inside the display case;

[0009] Temperature detection module, used to detect the temperature inside the display case;

[0010] Humidity control module, used to regulate the humidity inside the display case;

[0011] A humidity detection module is used to regulate the humidity inside the display case;

[0012] The control module is used to issue adjustment and control commands.

[0013] A control method for the above-mentioned display cabinet control system includes the following steps:

[0014] A. The illumination module provides light to the display case, the temperature regulation module regulates the temperature inside the display case, and the humidity regulation module regulates the humidity inside the display case; the illumination detection module detects the illumination inside the display case, the temperature detection module detects the temperature inside the display case, and the humidity detection module regulates the humidity inside the display case.

[0015] B. The control module normalizes the detection data from the illumination detection module, temperature detection module, and humidity detection module, and then establishes the correlation between the three sets of normalized detection data.

[0016] C. Based on the correlation, the three detection variables of light intensity, temperature and humidity are transformed into a single variable;

[0017] D. Use a single variable input genetic algorithm model to predict variables, then adjust the single variable according to the prediction results, and then map the adjustment amount of the single variable to the adjustment amounts of light intensity, temperature and humidity.

[0018] Preferably, step D, which involves using a single variable input to the genetic algorithm model for variable prediction, includes the following steps:

[0019] D1. Establish the objective function and constraints;

[0020] D2. Set the population size, number of generations, crossover probability, and mutation probability;

[0021] D3. Calculate the fitness of each individual in the population and select individuals with fitness higher than a preset threshold as genetic individuals;

[0022] D4. Use the crossover operator to perform crossover operations on genetic individuals;

[0023] D5. Use mutation operators to perform mutation operations on genetic individuals;

[0024] D6. Calculate the fitness of each individual in the new population. If there is an individual with fitness exceeding the optimal fitness, stop the calculation and take the above individual as the output. If the number of iterations exceeds the set threshold, select the individual with the highest fitness in the population as the output. Otherwise, go to step D3.

[0025] Preferably, the crossover operator is a nonlinear crossover operator.

[0026] Preferably, genetic individuals undergo at least one of crossover and mutation operations, and the proportion of genetic individuals that undergo both crossover and mutation operations is 20-30% of all genetic individuals.

[0027] Preferably, mapping the adjustment amount of a single variable to the adjustment amounts of light intensity, temperature, and humidity includes the following steps:

[0028] Weights are assigned based on the deviations of the current light intensity, temperature, and humidity from preset values. The weights are proportional to the deviations. Then, the adjustment amount of a single variable is mapped to the adjustment amount of light intensity, temperature, and humidity based on the correlation. Finally, the light intensity, temperature, and humidity are fine-tuned based on the deviations of the adjusted light intensity, temperature, and humidity from the preset values. The fine-tuning magnitude is proportional to the corresponding weight.

[0029] The beneficial effects of adopting the above technical solution are as follows: This invention solves the problem of poor accuracy in multivariate control in the prior art by converting light intensity, temperature and humidity into single variables for predictive control. Attached Figure Description

[0030] Figure 1 This is a schematic diagram of a specific embodiment of the present invention. Detailed Implementation

[0031] Reference Figure 1 One specific embodiment of the present invention includes,

[0032] Lighting module 1 is used to provide an illumination source inside the display case;

[0033] Light intensity detection module 2 is used to detect the light intensity inside the display case;

[0034] Temperature regulation module 3 is used to regulate the temperature inside the display case;

[0035] Temperature detection module 4 is used to detect the temperature inside the display case;

[0036] Humidity control module 5 is used to regulate the humidity inside the display case;

[0037] Humidity detection module 6 is used to adjust the humidity inside the display case;

[0038] Control module 7 is used to issue adjustment control commands.

[0039] A control method for the above-mentioned display cabinet control system includes the following steps:

[0040] A. Illumination module 1 provides an illumination source to the display case; temperature regulation module 3 regulates the temperature inside the display case; humidity regulation module 5 regulates the humidity inside the display case; illumination detection module 2 detects the illumination inside the display case; temperature detection module 4 detects the temperature inside the display case; humidity detection module 6 regulates the humidity inside the display case.

[0041] B. The control module 7 normalizes the detection data from the light intensity detection module 2, temperature detection module 4, and humidity detection module 6, and then establishes the correlation between the three sets of normalized detection data.

[0042] C. Based on the correlation, the three detection variables of light intensity, temperature and humidity are transformed into a single variable;

[0043] D. Use a single variable input genetic algorithm model to predict variables, then adjust the single variable according to the prediction results, and then map the adjustment amount of the single variable to the adjustment amounts of light intensity, temperature and humidity.

[0044] Step D, using a single variable input genetic algorithm model for variable prediction, includes the following steps:

[0045] D1. Establish the objective function and constraints;

[0046] D2. Set the population size, number of generations, crossover probability, and mutation probability;

[0047] D3. Calculate the fitness of each individual in the population and select individuals with fitness higher than a preset threshold as genetic individuals;

[0048] D4. Use the crossover operator to perform crossover operations on genetic individuals;

[0049] D5. Use mutation operators to perform mutation operations on genetic individuals;

[0050] D6. Calculate the fitness of each individual in the new population. If there is an individual with fitness exceeding the optimal fitness, stop the calculation and take the above individual as the output. If the number of iterations exceeds the set threshold, select the individual with the highest fitness in the population as the output. Otherwise, go to step D3.

[0051] The crossover operator is a nonlinear crossover operator.

[0052] Genetic individuals must undergo at least one of the operations of crossover and mutation, and the proportion of genetic individuals that undergo both crossover and mutation is 20-30% of all genetic individuals.

[0053] Mapping the adjustment amount of a single variable to the adjustment amounts of light intensity, temperature, and humidity includes the following steps:

[0054] Weights are assigned based on the deviations of the current light intensity, temperature, and humidity from preset values. The weights are proportional to the deviations. Then, the adjustment amount of a single variable is mapped to the adjustment amount of light intensity, temperature, and humidity based on the correlation. Finally, the light intensity, temperature, and humidity are fine-tuned based on the deviations of the adjusted light intensity, temperature, and humidity from the preset values. The fine-tuning magnitude is proportional to the corresponding weight.

[0055] In the description of this invention, it should be understood that the terms "longitudinal", "lateral", "up", "down", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this invention, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0056] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A display case control method, characterized in that... Includes the following steps: A. Illumination module (1) provides illumination light source to the display case; temperature adjustment module (3) adjusts the temperature inside the display case; humidity adjustment module (5) adjusts the humidity inside the display case; illumination detection module (2) detects the illumination inside the display case; temperature detection module (4) detects the temperature inside the display case; humidity detection module (6) detects the humidity inside the display case. B. The control module (7) normalizes the detection data of the light intensity detection module (2), temperature detection module (4) and humidity detection module (6), and then establishes the correlation between the three sets of normalized detection data. C. Based on the correlation, the three detection variables of light intensity, temperature and humidity are transformed into a single variable; D. Use a single variable input genetic algorithm model to predict variables, then adjust the single variable according to the prediction results, and then map the adjustment amount of the single variable to the adjustment amounts of light intensity, temperature and humidity. Mapping the adjustment amount of a single variable to the adjustment amounts of light intensity, temperature, and humidity includes the following steps: Weights are assigned based on the deviations of the current light intensity, temperature, and humidity from preset values. The weights are proportional to the deviations. Then, the adjustment amount of a single variable is mapped to the adjustment amount of light intensity, temperature, and humidity based on the correlation. Finally, the light intensity, temperature, and humidity are fine-tuned based on the deviations of the adjusted light intensity, temperature, and humidity from the preset values. The fine-tuning magnitude is proportional to the corresponding weight.

2. The display case control method according to claim 1, characterized in that: Step D, using a single variable input genetic algorithm model for variable prediction, includes the following steps: D1. Establish the objective function and constraints; D2. Set the population size, number of generations, crossover probability, and mutation probability; D3. Calculate the fitness of each individual in the population and select individuals with fitness higher than a preset threshold as genetic individuals; D4. Use the crossover operator to perform crossover operations on genetic individuals; D5. Use mutation operators to perform mutation operations on genetic individuals; D6. Calculate the fitness of each individual in the new population. If there is an individual with fitness exceeding the optimal fitness, stop the calculation and take the above individual as the output. If the number of iterations exceeds the set threshold, select the individual with the highest fitness in the population as the output. Otherwise, go to step D3.

3. The display case control method according to claim 2, characterized in that: The crossover operator is a nonlinear crossover operator.

4. The display case control method according to claim 3, characterized in that: Genetic individuals must undergo at least one of the operations of crossover and mutation, and the proportion of genetic individuals that undergo both crossover and mutation is 20-30% of all genetic individuals.

Images