A data processing control method and device based on a power cabinet and a storage medium

Abstract

The application discloses a data processing control method and device based on a power cabinet and a storage medium, the method comprising: obtaining a plurality of sampling data every preset time, and calculating a first sampling value of a current time period; comparing the first sampling value with a second sampling value of a previous time period to obtain a maximum difference value of the first sampling value and the second sampling value; if the maximum difference value is greater than a first threshold value, deleting the first sampling value and taking the second sampling value as the first sampling value of the current time period; according to a preset iteration parameter, performing optimization processing on a final first sampling value through iteration limit value to obtain an optimal output value, so as to control operation of a wind curtain machine of the power cabinet according to the optimal output value, reduce errors of output temperature and humidity values through data optimization processing on temperature and humidity measurement values of the power cabinet, and realize precise control of the dehumidification device wind curtain machine of the power cabinet to prevent formation of condensation in the power cabinet.

Description

Technical Field

[0001] This invention relates to the field of power equipment technology, and in particular to a data processing and control method, device and storage medium based on a power cabinet. Background Technology

[0002] In the intelligent control process for temperature control of outdoor power cabinets, temperature and humidity data are collected directly using temperature and humidity sensors to detect the temperature and humidity inside the power cabinet and in the environment. Without data optimization, the detected values ​​are directly fed back to the controller for feedback control of the air curtain device. Due to sensor inaccuracies and some large errors, the currently detected values ​​have significant deviations. These errors may cause malfunctions in starting or stopping the air curtain, making it impossible to accurately control the temperature and humidity of the power cabinet. Summary of the Invention

[0003] This invention provides a data processing and control method, device, and storage medium based on a power cabinet. By optimizing the temperature and humidity measurement values ​​of the power cabinet, the error of the output temperature and humidity values ​​is reduced, thereby achieving precise control of the dehumidification device air curtain machine of the power cabinet to prevent the formation of condensation in the power cabinet.

[0004] To optimize the processing of temperature and humidity measurements from a power cabinet and reduce errors in the output temperature and humidity values, this invention provides a data processing and control method based on a power cabinet, comprising: acquiring several sampled data points at preset intervals and calculating a first sampled value for the current time period; comparing the first sampled value with a second sampled value from the previous time period to obtain the maximum difference between the first sampled value and the second sampled value; if the maximum difference is greater than a first threshold, deleting the first sampled value and using the second sampled value as the first sampled value for the current time period;

[0005] Based on preset iteration parameters, the final first sampled value is optimized by iterating the maximum limit value to obtain the optimal output value, and the operation of the air curtain machine of the power cabinet is controlled according to the optimal output value.

[0006] As a preferred solution, several consecutive sampled data points over a period of time may contain redundant values ​​due to gross errors and environmental influences. Compared to classical statistical data, this invention removes data with significant errors caused by equipment factors from several consecutive sampled data points over a period of time, and optimizes the sampled values ​​using an iterative limit method. This eliminates the influence of factors such as equipment errors, making the sampled output values ​​as close to the actual values ​​as possible, and it is computationally simpler than optimization methods such as Gaussian filtering. Based on the optimized output values, environmental parameters such as temperature and humidity thresholds are judged to control the start-up, shutdown, and operating status of the air curtain machine in the power cabinet. This invention uses more accurate optimized data to improve the accuracy of threshold judgment and optimize the control effect for the operation of the air curtain machine in the power cabinet.

[0007] As a preferred approach, a number of sample data points are acquired at preset time intervals, and the first sample value for the current time period is calculated, specifically as follows:

[0008] N first sampling data points of the environmental parameter acquisition device of the power cabinet are acquired at preset time intervals; the environmental parameter acquisition device of the power cabinet is either a temperature sensor or a humidity sensor.

[0009] Set N sampled data into a first queue of length N. After obtaining a current sampled data, delete the first sampled data in the first queue, shift the remaining N-1 sampled data in the queue forward one position in sequence, and insert the current sampled data into the end of the first queue until N first sampled data within the preset time period are put into the queue.

[0010] Calculate the first sample value for the current time period:

[0011]

[0012] Where y(n) is the first sampled value in the current time period, x(n) is the current sampled data, and N is the queue length.

[0013] As a preferred embodiment, the present invention calculates a first sample value for the current time period by taking several consecutive sampled data, which can eliminate the influence of factors such as equipment error, so that the sampled output value is closest to the actual value, and the calculation is simpler than optimization methods such as Gaussian filtering.

[0014] As a preferred embodiment, the first sampled value is compared with the second sampled value from the previous time period to obtain the maximum difference between the first sampled value and the second sampled value, specifically as follows:

[0015] Based on the dispersion of the N data in the queue of the previous time period, the first sampled value y(n) is compared with the second sampled value y(n-1) of the previous time period to determine the maximum difference ε;

[0016] in,

[0017] As a preferred embodiment, the present invention calculates a first sample value for the current time period from a series of consecutive sampled data, and compares the sampled values ​​of adjacent time periods to determine whether the sampled value of the current time period is valid. This can eliminate the influence of factors such as equipment errors, making the sampled output value closest to the actual value, and is simpler in terms of computation than optimization methods such as Gaussian filtering.

[0018] As a preferred embodiment, if the maximum difference is greater than the first threshold, the first sampled value is deleted, and the second sampled value is used as the first sampled value for the current time period, specifically:

[0019] If the maximum difference is greater than the first threshold U, then the first sampled value is deleted, and the second sampled value is used as the first sampled value for the current time period; where, ε is the average of n sampled values; ε is the maximum difference.

[0020] As a preferred embodiment, the present invention determines whether the sampled value of the current time period is valid by comparing the sampled values ​​of adjacent time periods. If the sampled value exceeds the maximum deviation range, the latest sampled value is considered to be an illegal value and should be deleted. The previous sampled value is used to replace the current sampled value, thereby reducing the error of the sampled value caused by factors such as equipment, so that the sampled output value is closest to the actual value, and the calculation is simpler than optimization methods such as Gaussian filtering.

[0021] As a preferred embodiment, if the maximum difference is greater than a first threshold, the first sampled value is deleted, and the second sampled value is used as the first sampled value for the current time period, further comprising:

[0022] If the maximum difference is not greater than the first threshold U, then the first sampled value is retained.

[0023] As a preferred embodiment, the present invention determines whether the sampled value of the current time period is valid by comparing the sampled values ​​of adjacent time periods. If the sampled value is not greater than the maximum deviation range, the latest sampled value is considered to be valid data and added to the queue. This reduces the error of the sampled value caused by factors such as equipment, so that the sampled output value is closest to the actual value, and the calculation is simpler than optimization methods such as Gaussian filtering.

[0024] As a preferred approach, based on preset iteration parameters, the final first sampled value is optimized by iterating through the minimum and maximum values ​​to obtain the optimal output value, specifically as follows:

[0025]

[0026]

[0027] in, Let Y be the iteration parameter, Y be the optimal output value, and σ be the si gmod function.

[0028] As a preferred embodiment, the present invention uses the amplitude limiting filter method to iteratively optimize the recursive algorithm to minimize the deviation between the output value and the actual value, reduce the error of the sampled value caused by factors such as equipment, make the sampled output value closest to the actual value, and has a simpler computational load than optimization methods such as Gaussian filtering.

[0029] Accordingly, the present invention also provides a data processing and control device based on a power cabinet, comprising: a sampling module, an error processing module, and an optimization module;

[0030] The sampling module is used to acquire a number of sample data at preset time intervals and calculate the first sample value for the current time period.

[0031] The error processing module is used to compare the first sampled value with the second sampled value of the previous time period to obtain the maximum difference between the first sampled value and the second sampled value; if the maximum difference is greater than a first threshold, the first sampled value is deleted and the second sampled value is used as the first sampled value of the current time period.

[0032] The optimization module is used to optimize the final first sampled value by iterating the maximum value according to preset iteration parameters to obtain the optimal output value, so as to control the operation of the air curtain machine of the power cabinet according to the optimal output value.

[0033] As a preferred solution, several consecutive sampled data points over a period of time may contain redundant values ​​due to gross errors and environmental influences. Compared to classical statistical data, this invention uses a sampling module that processes several consecutive sampled data points over a period of time. An error processing module removes data with significant errors caused by equipment factors, and an optimization module uses an iterative limit method to optimize the sampled values. This eliminates the influence of equipment errors and other factors, making the sampled output value as close to the actual value as possible, and it is computationally simpler than optimization methods such as Gaussian filtering. Based on the optimized output value, environmental parameters, such as temperature and humidity thresholds, are judged to control the start-up, shutdown, and operating status of the air curtain machine in the power cabinet. This invention uses more precise optimized data to improve the accuracy of threshold judgment and optimize the control effect.

[0034] As a preferred embodiment, the error processing module includes: a comparison unit and a processing unit;

[0035] The comparison unit is used to compare the first sampled value y(n) with the second sampled value y(n-1) of the previous time period based on the dispersion of the N data points in the queue of the previous time period, and to determine the maximum difference ε; wherein,

[0036] The processing unit is configured to delete the first sampled value and use the second sampled value as the first sampled value for the current time period if the maximum difference is greater than a first threshold U; wherein, ε is the average of n sampled values; ε is the maximum difference; if the maximum difference is greater than the first threshold U, then the first sampled value is retained.

[0037] As a preferred embodiment, the comparison unit of the present invention determines whether the sampled value of the current time period is valid by comparing the sampled values ​​of adjacent time periods. If the sampled value is not greater than the maximum deviation range, the processing unit considers the latest sampled value to be valid data and adds it to the queue, thereby reducing the error of the sampled value caused by factors such as equipment, so that the sampled output value is closest to the actual value, and the computation is simpler than optimization methods such as Gaussian filtering.

[0038] As a preferred option, the optimization module includes: an iterative optimization unit;

[0039] The iterative optimization unit is used to optimize the final first sampled value by iterating through the minimum and maximum values ​​according to preset iterative parameters.

[0040]

[0041] To obtain the optimal output value:

[0042] in, Let Y be the iteration parameter, Y be the optimal output value, and σ be the si gmod function.

[0043] As a preferred embodiment, the iterative optimization unit of this invention uses the amplitude limiting filtering method to iteratively optimize the recursive algorithm to minimize the deviation between the output value and the actual value, reduce the error of the sampled value caused by factors such as equipment, make the sampled output value closest to the actual value, and has a simpler computational load than optimization methods such as Gaussian filtering.

[0044] Accordingly, the present invention also provides a computer-readable storage medium, the computer-readable storage medium including a stored computer program; wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform a data processing control method based on a power cabinet as described in the present invention. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating an embodiment of a data processing and control method based on a power cabinet provided by the present invention;

[0046] Figure 2 This is a schematic diagram of an embodiment of a data processing and control device based on a power cabinet provided by the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] Example 1

[0049] Please refer to Figure 1 The present invention provides a data processing and control method based on a power cabinet, comprising steps S101-S104:

[0050] Step S101: Acquire a number of sample data at preset time intervals and calculate the first sample value for the current time period.

[0051] In this embodiment, the power cabinet includes a temperature sensor and a humidity sensor, a data processor, a controller, and an air curtain machine. A data processing and control method based on the power cabinet is applied to the data processor, which acquires temperature and humidity values ​​collected by the temperature and humidity sensors at preset intervals, performs optimization processing on each value, and feeds back the optimal output value to the controller. The controller controls the opening, closing, and operation status of the air curtain machine based on the optimal output values ​​of the temperature and humidity, thereby achieving feedback control of the air curtain machine to prevent condensation from forming inside the power cabinet.

[0052] In this embodiment, N first sampling data points of the environmental parameter acquisition device of the power cabinet are acquired at preset time intervals; the environmental parameter acquisition device of the power cabinet is either a temperature sensor or a humidity sensor.

[0053] Set N sampled data into a first queue of length N. After obtaining a current sampled data, delete the first sampled data in the first queue, shift the remaining N-1 sampled data in the queue forward one position in sequence, and insert the current sampled data into the end of the first queue until N first sampled data within the preset time period are put into the queue.

[0054] Calculate the first sample value for the current time period:

[0055]

[0056] Where y(n) is the first sampled value in the current time period, x(n) is the current sampled data, and N is the queue length.

[0057] Step S102: Compare the first sampled value with the second sampled value of the previous time period to obtain the maximum difference between the first sampled value and the second sampled value.

[0058] In this embodiment, the moving average filter is optimized by the amplitude limiting filter method to determine the change amplitude of the measured signal, thereby eliminating sharp impulse interference in the slowly changing signal and effectively overcoming pulse interference caused by random factors. Based on the dispersion of the N data in the queue of the previous time period, the first sampled value y(n) is compared with the second sampled value y(n-1) of the previous time period to determine the maximum difference ε.

[0059] in,

[0060] Step S103: If the maximum difference is greater than the first threshold, the first sampled value is deleted and the second sampled value is used as the first sampled value for the current time period.

[0061] In this embodiment, if the maximum difference is greater than the first threshold U, the first sampled value is deleted, and the second sampled value is used as the first sampled value for the current time period; wherein, ε is the average of n sampled values; ε is the maximum difference.

[0062] In this embodiment, if the maximum difference is not greater than the first threshold U, the first sampled value is retained.

[0063] In this embodiment, if the maximum difference is greater than the first threshold U, the first sample value is determined to be an illegal value and deleted, and the second sample value of the previous time period is used as the first sample value of the current time period.

[0064] Step S104: Based on the preset iteration parameters, optimize the final first sampled value by iterating the maximum limit value to obtain the optimal output value, so as to control the operation of the air curtain machine of the power cabinet according to the optimal output value.

[0065] In this embodiment,

[0066] in, Let Y be the iteration parameter, Y be the optimal output value, and σ be the si gmod function.

[0067] Implementing the embodiments of the present invention has the following effects:

[0068] Over a period of time, several consecutive sampled data points may contain redundant values ​​due to gross errors and environmental influences. Compared to classical statistical methods, this invention removes data with significant errors caused by equipment factors from several consecutive sampled data points over a period of time. It then optimizes the sampled values ​​using an iterative limit method, eliminating the influence of equipment errors and other factors, resulting in sampled output values ​​that are closest to the actual values. Furthermore, this method is computationally simpler than optimization methods such as Gaussian filtering. Based on the optimized output values, environmental parameters, such as temperature and humidity thresholds, are judged to control the start-up, shutdown, and operating status of the air curtain machine in the power cabinet. This invention uses more precise optimized data to improve the accuracy of threshold judgment and optimize control performance.

[0069] Example 2

[0070] Please refer to Figure 2 The present invention provides a data processing and control device based on a power cabinet, comprising: a sampling module 201, an error processing module 202, and an optimization module 203;

[0071] The sampling module 201 is used to acquire a number of sampling data at preset time intervals and calculate the first sampling value of the current time period;

[0072] The error processing module 202 is used to compare the first sampled value with the second sampled value of the previous time period to obtain the maximum difference between the first sampled value and the second sampled value; if the maximum difference is greater than a first threshold, the first sampled value is deleted and the second sampled value is used as the first sampled value of the current time period.

[0073] The optimization module 203 is used to optimize the final first sampled value by iterating the maximum value according to the preset iteration parameters to obtain the optimal output value, so as to control the operation of the air curtain machine of the power cabinet according to the optimal output value.

[0074] Error processing module 202 includes: a comparison unit and a processing unit;

[0075] The comparison unit is used to compare the first sampled value y(n) with the second sampled value y(n-1) of the previous time period based on the dispersion of the N data points in the queue of the previous time period, and to determine the maximum difference ε; wherein,

[0076] The processing unit is configured to delete the first sampled value and use the second sampled value as the first sampled value for the current time period if the maximum difference is greater than a first threshold U; wherein, ε is the average of n sampled values; ε is the maximum difference; if the maximum difference is greater than the first threshold U, then the first sampled value is retained.

[0077] Optimization module 203 includes: an iterative optimization unit;

[0078] The iterative optimization unit is used to optimize the final first sampled value by iterating through the minimum and maximum values ​​according to preset iterative parameters.

[0079]

[0080] To obtain the optimal output value:

[0081] in, Let Y be the iteration parameter, Y be the optimal output value, and σ be the si gmod function.

[0082] The aforementioned data processing and control device based on a power cabinet can implement the data processing and control method based on a power cabinet as described in the above method embodiments. The options in the above method embodiments are also applicable to this embodiment, and will not be detailed here. The remaining content of this application's embodiments can be referred to the content of the above method embodiments, and will not be repeated in this embodiment.

[0083] Implementing the embodiments of the present invention has the following effects:

[0084] Over a period of time, several consecutive sampled data points may contain redundant values ​​due to gross errors and environmental influences. Compared to classical statistical methods, this invention uses a sampling module that processes consecutive sampled data over a period of time. An error processing module removes data with significant errors caused by equipment factors, and an optimization module uses an iterative limit method to optimize the sampled values. This eliminates the influence of equipment errors and other factors, making the sampled output values ​​as close to the actual values ​​as possible, and is computationally simpler than optimization methods such as Gaussian filtering. Based on the optimized output values, environmental parameters, such as temperature and humidity thresholds, are judged to control the start-up, shutdown, and operating status of the air curtain machine in the power cabinet. This invention uses more precise optimized data to improve the accuracy of threshold judgment and optimize the control effect.

[0085] Example 3

[0086] Accordingly, the present invention also provides a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the data processing control method based on the power cabinet as described in any of the above embodiments.

[0087] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0088] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0089] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0090] The memory can be used to store the computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the mobile terminal, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart memory card (SMC), secure digital card (SD), flash memory card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0091] Wherein, if the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when the computer program is executed by a processor, it can implement the steps of the various method embodiments described above. Wherein, the computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0092] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A data processing and control method based on a power cabinet, characterized in that, include: Acquire a number of sample data at preset time intervals and calculate the first sample value for the current time period; The first sampled value is compared with the second sampled value of the previous time period to obtain the maximum difference between the first sampled value and the second sampled value; if the maximum difference is greater than a first threshold, the first sampled value is deleted and the second sampled value is used as the first sampled value of the current time period. Specifically, acquiring a number of sample data points at preset time intervals and calculating the first sample value for the current time period involves: N first sampling data points of the environmental parameter acquisition device of the power cabinet are acquired at preset time intervals; the environmental parameter acquisition device of the power cabinet is either a temperature sensor or a humidity sensor. Set N sampled data into a first queue of length N. After obtaining a current sampled data, delete the first sampled data in the first queue, shift the remaining N-1 sampled data in the queue forward one position in sequence, and insert the current sampled data into the end of the first queue until N first sampled data within the preset time period are put into the queue. Calculate the first sample value for the current time period: Where y(n) is the first sampled value in the current time period, x(n) is the current sampled data, and N is the queue length; Based on preset iteration parameters, the final first sampled value is optimized by iterating through the limit value to obtain the optimal output value, specifically: in, Let Y be the iteration parameter, Y be the optimal output value, and σ be the sigmoid function. It is the average of n sampled values; The air curtain machine of the power cabinet is controlled to operate according to the optimal output value.

2. The data processing and control method based on a power cabinet as described in claim 1, characterized in that, If the maximum difference is greater than the first threshold, the first sampled value is deleted, and the second sampled value is used as the first sampled value for the current time period. Specifically: If the maximum difference is greater than the first threshold U, then the first sampled value is deleted, and the second sampled value is used as the first sampled value for the current time period; where, ε is the average of n sampled values; ε is the maximum difference.

3. The data processing and control method based on a power cabinet as described in claim 2, characterized in that, The step of deleting the first sampled value and using the second sampled value as the first sampled value for the current time period if the maximum difference is greater than the first threshold also includes: If the maximum difference is not greater than the first threshold U, then the first sampled value is retained.

4. A data processing and control device based on a power cabinet, characterized in that, include: Sampling module, error processing module, and optimization module; The sampling module is used to acquire a number of sample data points at preset time intervals and calculate the first sample value for the current time interval; specifically, acquiring a number of sample data points at preset time intervals and calculating the first sample value for the current time interval involves: N first sampling data points of the environmental parameter acquisition device of the power cabinet are acquired at preset time intervals; the environmental parameter acquisition device of the power cabinet is either a temperature sensor or a humidity sensor. Set N sampled data into a first queue of length N. After obtaining a current sampled data, delete the first sampled data in the first queue, shift the remaining N-1 sampled data in the queue forward one position in sequence, and insert the current sampled data into the end of the first queue until N first sampled data within the preset time period are put into the queue. Calculate the first sample value for the current time period: Where y(n) is the first sampled value in the current time period, x(n) is the current sampled data, and N is the queue length; The error processing module is used to compare the first sampled value with the second sampled value of the previous time period to obtain the maximum difference between the first sampled value and the second sampled value; if the maximum difference is greater than a first threshold, the first sampled value is deleted and the second sampled value is used as the first sampled value of the current time period. The optimization module is used to optimize the final first sampled value by iterating the maximum value according to preset iteration parameters to obtain the optimal output value, so as to control the operation of the air curtain machine of the power cabinet according to the optimal output value. The optimization module includes: an iterative optimization unit; The iterative optimization unit is used to optimize the final first sampled value by iterating through the minimum and maximum values ​​according to preset iterative parameters. To obtain the optimal output value: in, Let Y be the iteration parameter, Y be the optimal output value, and σ be the sigmoid function. It is the average of n sampled values.

5. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program; wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform a data processing control method based on a power cabinet as described in any one of claims 1 to 3.

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