A communication machine room temperature and humidity control method and system based on DCS

Abstract

This invention provides a DCS-based method and system for temperature and humidity control in communication equipment rooms, belonging to the field of temperature and humidity control technology. The method includes: collecting various types of data and classifying the communication equipment room data pairs to obtain equipment function data; analyzing data transmission volume to obtain data change trends and predicting time-period transmission changes by combining external factor data; analyzing the impact of data transmission volume on communication equipment room data to obtain equipment temperature change data and formulating an initial temperature and humidity control strategy by combining external factor data; adjusting the initial temperature and humidity control strategy according to time-period transmission changes to obtain a temperature and humidity control strategy, and executing the temperature and humidity control strategy through the DCS. This invention, through real-time analysis of time-period transmission changes and equipment temperature changes, adjusts the temperature and humidity control strategy in a timely manner, enabling the strategy to adapt to changes in different time periods and better ensuring the stable operation of the communication equipment room.

Description

Technical Field

[0001] This invention relates to the field of temperature and humidity control technology, and in particular to a method and system for temperature and humidity control in a communication equipment room based on DCS. Background Technology

[0002] Communication equipment rooms are the core hubs for data transmission, storage, and processing, and their temperature and humidity environment directly affects the operational stability and lifespan of equipment. With the popularization of 5G and cloud computing technologies, equipment in equipment rooms is being deployed at high density, resulting in a surge in heat generation. Core equipment (such as servers and switches) is sensitive to temperature and humidity—temperatures exceeding 27°C or humidity deviating from 40%-60%RH can easily lead to data delays and equipment downtime. Therefore, precise temperature and humidity control is crucial for the operation and maintenance of equipment rooms.

[0003] Current mainstream control methods rely on DCS systems, which collect environmental data through sensors and coordinate with equipment such as air conditioners and humidifiers for regulation. However, they have significant drawbacks: they ignore the amount of data transmitted and the impact of external factors on equipment temperature, resulting in a disconnect between regulation and actual needs and insufficient accuracy.

[0004] Equipment heat generation is strongly correlated with transmission volume—the higher the transmission volume handled by a server, the greater the load on core components, and the more significant the heat generation; similarly, an increase in the forwarding volume of a switch port will cause the chip temperature to rise rapidly. However, existing strategies only passively respond to changes in ambient temperature and humidity, without analyzing transmission volume trends, and therefore cannot predict the increase in heat generation. For example, during major e-commerce promotions, transmission volume may increase by more than 50% in a short period, and equipment heat generation will increase accordingly. Existing strategies only initiate cooling after the temperature rises, resulting in a 2-5 minute lag, which can easily lead to short-term overheating.

[0005] The temperature and humidity of the data center are also affected by the natural environment (high summer temperatures reduce air conditioning efficiency by 15%-20%, and the plum rain season causes humidity to exceed the standard), business scheduling (sudden business increases equipment load), and maintenance activities (opening server racks for maintenance causes local temperature increases of 3-5℃). However, current technology treats external factors as "uncontrollable interference" and only uses fixed thresholds for regulation. For example, in summer, air conditioning parameters from spring and autumn are still used, resulting in higher temperatures in the core area; in winter, humidification strategies are not adjusted in conjunction with the dry environment, which easily leads to static electricity.

[0006] Furthermore, the strategy lacks dynamic adaptability. Because it does not take into account fluctuations in transmission volume and changes in external factors, the control mode is fixed—insufficient cooling capacity during peak hours and excessive control during off-peak hours, resulting in wasted energy.

[0007] In summary, there is an urgent need to invent a DCS-based method and system for controlling the temperature and humidity of communication equipment rooms to solve the above problems. Summary of the Invention

[0008] This invention provides a method and system for controlling temperature and humidity in a communication equipment room based on DCS, which solves the shortcomings of existing technologies that ignore the influence of data transmission volume and external factors on equipment temperature, resulting in inaccurate temperature and humidity control.

[0009] On one hand, the present invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS, comprising:

[0010] Data transmission volume, communication equipment data, and external factor data are collected. The communication equipment data is then classified to obtain equipment function data.

[0011] The data transmission volume is analyzed using the fractal method based on the transmission characteristics to obtain the data change trend, and the data change trend is predicted by combining external factor data to obtain the transmission change over time.

[0012] By analyzing the impact of data transmission volume on the data of communication equipment room, we obtained equipment temperature change data and formulated an initial temperature and humidity control strategy based on external factor data.

[0013] The initial temperature and humidity control strategy is adjusted based on the time-period transmission changes to obtain the temperature and humidity control strategy, which is then executed through the DCS.

[0014] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The steps for classifying and obtaining equipment functional data include:

[0015] Classification criteria are defined based on the physical attributes, functional attributes, and operational characteristics of the equipment, and equipment processing data is obtained by preprocessing the equipment data in the communication equipment room.

[0016] Based on classification criteria, the data processed by the equipment is divided into a hierarchical structure, consisting of a first level and a second level.

[0017] Extract the key parameters reflecting the functional characteristics of each level and correlate them with the physical location to obtain the device functional data.

[0018] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The steps for analyzing data change trends include:

[0019] Transform data from different sources and in different formats into a unified structure and standardize the data to obtain the processed data.

[0020] The transmission volume statistical features, transmission volume periodic features, and transmission volume mutation features are extracted from the transmission volume processing data as key transmission volume features.

[0021] Based on the key characteristics of transmission volume, fractal analysis is used to extract fractal features, judge the trend characteristics of transmission volume, and generate trend curves based on the principle of self-similarity to obtain the data change trend.

[0022] This invention provides a method for temperature and humidity control in a communication equipment room based on a DCS (Distributed Control System). The step of extracting fractal features includes:

[0023] The effective time window for fractal analysis is determined based on the statistical characteristics of transmission volume, and multiple periodic segments are obtained by segmenting according to the periodic characteristics of transmission volume.

[0024] The sliding R / S method is used to calculate the periodic fractal parameters of each periodic segment, and the fractal dimension is calculated for the periodic segments with drastic fluctuations to achieve complexity matching.

[0025] Based on the characteristics of transmission volume mutations, the effective time window is divided into multiple mutation stages, and the corresponding mutation fractal parameters are calculated.

[0026] Periodic fractal parameters and abrupt fractal parameters are classified and integrated according to key characteristics of transmission volume to form fractal features.

[0027] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The steps for predicting transmission changes over a time period include:

[0028] Based on fractal characteristics, the transmission volume trend defects for a future preset time period are generated as the initial baseline.

[0029] External factor data are categorized into natural environment, business scheduling, and operation and maintenance to obtain multiple influencing factors. A regression model is then constructed with the change in transmission volume to calculate the influence weight of different influencing factors.

[0030] The correction amount of influencing factors to the initial baseline is calculated from the perspectives of both persistence and suddenness.

[0031] Based on the interaction between different influencing factors, a coupling coefficient is introduced to adjust the correction amount to obtain the total correction amount, and the time period transmission variation is calculated in combination with the initial baseline.

[0032] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The formula for calculating the time-period transmission variation is expressed as follows:

[0033]

[0034]

[0035] In the formula, This is the total correction amount. It is a change in transmission over time. It is the coupling coefficient. It is the product of the single-factor correction values ​​of the i-th and j-th factors.

[0036] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The steps for obtaining equipment temperature change data include:

[0037] Align the data transmission volume with the data of the communication equipment room, and establish a correspondence between the equipment and the equipment from which the transmission volume originates.

[0038] The correlation between transmission volume and temperature for each device is calculated based on the device correspondence, and the temperature response delay is obtained through cross-correlation analysis. The basic impact characteristics are obtained by aggregating according to the device type.

[0039] The transmission quantity and temperature are analyzed in segments to identify nonlinear relationships and extract nonlinear influence characteristics.

[0040] Based on the influence patterns of basic and nonlinear influence characteristics on equipment temperature, and combined with the amount of data transmitted, equipment temperature change data is obtained.

[0041] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The steps for formulating an initial temperature and humidity control strategy include:

[0042] Extract the safe temperature range for different types of equipment from the equipment temperature change data, and formulate temperature and humidity adjustment targets according to the functional equipment area.

[0043] The impact of external factors on temperature and humidity is categorized into three types: temperature interference, humidity interference, and indirect impact, and the direction of correction is determined accordingly.

[0044] Based on the temperature and humidity adjustment targets and correction directions, and combined with the execution devices that can be called by the DCS system, adjustment methods are formulated from three aspects: temperature control, humidity control, and coordinated regulation. The initial temperature and humidity regulation strategy is obtained by prioritizing the methods according to energy consumption and accuracy.

[0045] This invention provides a method for controlling temperature and humidity in a communication equipment room based on a DCS (Distributed Control System). The steps for adjusting the temperature and humidity control strategy include:

[0046] Based on the time-period transmission change, the equipment temperature increment at different time periods is calculated to determine the basis for strategy adjustment, and conflict analysis is performed with the initial temperature and humidity control strategy to obtain demand control.

[0047] To address the demand regulation needs of different time periods, a list of adaptation gaps is obtained by recording the deficiencies of the initial temperature and humidity regulation strategies for each time period.

[0048] Based on the list of adaptation gaps and the controllable resources of the DCS system, temperature and humidity control strategies are obtained by adjusting the timing of control, equipment parameters, and collaborative logic.

[0049] On the other hand, the present invention provides a DCS-based temperature and humidity control system for communication equipment rooms, comprising:

[0050] The data classification module is used to collect data transmission volume, communication equipment data, and external factor data, and classify the communication equipment data to obtain equipment function data.

[0051] The data transmission trend prediction module is used to analyze the data transmission volume based on the fractal method of data transmission characteristics to obtain the data change trend, and combine it with external factor data to predict the data change trend and obtain the time period transmission change.

[0052] The initial temperature and humidity control strategy module is used to analyze the impact of data transmission volume on the data of communication equipment room to obtain equipment temperature change data, and to formulate an initial temperature and humidity control strategy in combination with external factor data.

[0053] The time-period temperature control execution module is used to adjust the initial temperature and humidity control strategy according to the time-period transmission changes to obtain the temperature and humidity control strategy, and execute the temperature and humidity control strategy through DCS.

[0054] This invention provides a DCS-based method and system for temperature and humidity control in communication equipment rooms. By defining classification standards based on physical attributes, functional attributes, and operational characteristics, it preprocesses and hierarchically divides equipment data, extracts key parameters and correlates them with physical locations, thereby classifying equipment functional data. This solves the problem of the wide range of data sources and diverse formats in communication equipment rooms, making effective integration and classification difficult. It achieves standardization and structuring of equipment data, facilitating subsequent analysis and management. Furthermore, it converts data transmission volume into a unified structure and performs standardization processing, extracting statistical, periodic, and abrupt change characteristics. Fractal analysis is used to extract fractal features, generating trend curves for analysis, accurately identifying the changing trends of data transmission volume and providing a basis for subsequent temperature and humidity control. It also considers the comprehensive influence of external factors, dynamically adjusting temperature and humidity control strategies to adapt to changes in the communication equipment room environment, improving the system's adaptability and reliability. Finally, it employs complex methods such as fractal analysis, combined with the automated execution capabilities of the DCS system, enhancing the intelligence level of the communication equipment room temperature and humidity control system and reducing manual intervention. This invention improves the accuracy of temperature and humidity control, enhances the system's applicability and intelligence, and ensures the safe operation of communication equipment room equipment. Attached Figure Description

[0055] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0056] Figure 1This is one of the flowcharts illustrating a DCS-based method for controlling temperature and humidity in a communication equipment room, as provided in an embodiment of the present invention.

[0057] Figure 2 This is a second schematic flowchart of a DCS-based method for controlling temperature and humidity in a communication equipment room, provided by an embodiment of the present invention.

[0058] Figure 3 This is the third flowchart of a DCS-based method for controlling temperature and humidity in a communication equipment room, provided in an embodiment of the present invention.

[0059] Figure 4 This is a flowchart illustrating a DCS-based temperature and humidity control system for a communication equipment room, as provided in an embodiment of the present invention. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0061] The following is combined with Figures 1-4 This invention describes a DCS-based method and system for controlling temperature and humidity in a communication equipment room.

[0062] like Figure 1 As shown in the figure, an embodiment of the present invention provides a method for controlling the temperature and humidity of a communication equipment room based on a DCS, comprising:

[0063] Data transmission volume, communication equipment data, and external factor data are collected. The communication equipment data is then classified to obtain equipment function data.

[0064] The data packet volume and bandwidth utilization of each device port are collected in real time through the communication interfaces of the network equipment in the communication room as data transmission volume, with a sampling interval of 5-10 seconds. The physical location information, function type information, rated power, and heat dissipation parameters of the equipment within the room are collected as equipment function distribution data. External environmental data, service scheduling data, and operation and maintenance arrangement data are obtained through the DCS system access to external systems as external factor data. Natural environmental data includes outdoor temperature and humidity, and seasonal variation data. Service scheduling data includes peak user access times and planned service expansion information. Operation and maintenance arrangement data includes equipment maintenance plans and new equipment installation times.

[0065] The steps to obtain device function data through classification include:

[0066] Classification criteria are defined based on the physical attributes, functional attributes, and operational characteristics of the equipment, and equipment processing data is obtained by preprocessing the equipment data in the communication equipment room.

[0067] Physical attribute dimensions include device model (e.g., Huawei S6720 switch), manufacturer, physical dimensions (length × width × height), installation location (rack number + unit, e.g., A1-15U), and device number (unique identifier, e.g., SRV-001).

[0068] Functional attribute dimensions include the network layer (core layer / aggregation layer / access layer), the type of service undertaken (cloud computing / data storage / network forwarding / power supply guarantee), and the description of core functions (such as "responsible for real-time calculation of user data" and "providing uninterrupted power supply").

[0069] Operating characteristics include rated power (e.g., 500W), maximum heat dissipation power (e.g., 450W), operating temperature range (10-35℃), energy consumption curve under typical load, and connection relationship with other devices (e.g., "connected to port 1 of switch SW-002").

[0070] Preprocessing steps may include removing invalid data (such as null values, obvious erroneous values, such as power = -100W) and duplicate data (such as duplicate entries from the same device).

[0071] Convert data from different sources into a structured format (such as CSV or database table). For example, unify the "installation location" to the "rack number-U position" format (such as "B3-08U").

[0072] For missing key information (such as the heat dissipation power of some older equipment), supplement it by consulting the manufacturer's manual or estimating the parameters of the same model of equipment.

[0073] Based on classification criteria, the data processed by the equipment is divided into a hierarchical structure, consisting of a first level and a second level.

[0074] The first level is divided into four categories based on core functions: data processing equipment, data transmission equipment, data storage equipment, and auxiliary support equipment. The second level includes: data processing equipment, further subdivided into core servers, edge computing servers, and data relay servers; data transmission equipment, subdivided into core switches, aggregation switches, access switches, and routers; data storage equipment, subdivided into disk arrays, storage servers, and tape libraries; and auxiliary support equipment, subdivided into UPS power supplies, power distribution cabinets, and air conditioning control modules.

[0075] Extract the key parameters reflecting the functional characteristics of each level and correlate them with the physical location to obtain the device functional data.

[0076] For data processing devices: extract information such as "number of CPU cores", "memory capacity", "maximum number of concurrent tasks", and "heat dissipation power under full load".

[0077] For data transmission devices: extract information such as "number of ports", "maximum bandwidth", "packet forwarding rate", and "temperature sensitivity under high load" (e.g., how many degrees Celsius the temperature rises for every 10% increase in bandwidth).

[0078] For auxiliary support equipment: extract "power supply capacity", "adjustment accuracy" (such as the temperature control error of air conditioner ±0.5℃) and "fault response time", etc.

[0079] The data transmission volume is analyzed using the fractal method based on the transmission characteristics to obtain the data change trend, and the data change trend is predicted by combining external factor data to obtain the transmission change over time.

[0080] like Figure 2 As shown, the steps to analyze and obtain data change trends include:

[0081] Transform data from different sources and in different formats into a unified structure and standardize the data to obtain the processed data.

[0082] The transmission volume statistical features, transmission volume periodic features, and transmission volume mutation features are extracted from the transmission volume processing data as key transmission volume features.

[0083] Transmission volume statistics characteristics: Calculate the mean, peak, valley and variance of transmission volume within a fixed time window (such as 1 hour or 1 day) to identify "normal fluctuation range" (such as daily transmission volume is mostly between 100-500Mbps, variance <50) and "abnormal fluctuation point" (such as peak suddenly reaching 1000Mbps).

[0084] Transmission volume cyclical characteristics: By comparing data within a sliding window (e.g., comparing the same time period on weekdays and weekends), cyclical patterns in transmission volume can be identified, including: Daily cycle: For example, peak hours are from 9:00 AM to 6:00 PM daily, with a low point from 2:00 AM to 6:00 AM. Weekly cycle: For example, weekday transmission volume is 1.5 times that of weekends. Seasonal cycle: For example, transmission volume during major e-commerce promotion months (November) is 30% higher than usual.

[0085] Transmission volume mutation characteristics: Mark the point of abrupt change in transmission volume (such as a sudden increase in transmission volume from 300Mbps to 800Mbps and lasting for more than 30 minutes at a certain moment), and record the cause by associating it with external events (such as business system launch or traffic attack).

[0086] Based on key characteristics of transmission volume, fractal analysis is used to extract fractal features, determine the trend characteristics of transmission volume, and generate trend curves based on the principle of self-similarity for analysis to obtain data change trends. Data change trends can be categorized as: trend type (rising / falling / stable), period length, fluctuation range, and main influencing factors (such as peak traffic, equipment load), etc.

[0087] like Figure 3 As shown, the steps for extracting fractal features include:

[0088] The effective time window for fractal analysis is determined based on the statistical characteristics of transmission volume, and multiple periodic segments are obtained by segmenting according to the periodic characteristics of transmission volume.

[0089] The sliding R / S method is used to calculate the periodic fractal parameters of each periodic segment, and the fractal dimension is calculated for the periodic segments with drastic fluctuations to achieve complexity matching.

[0090] The periodic data is divided into overlapping subsequences according to the sliding window length, and the range and standard deviation are calculated. The ratio of the range to the standard deviation is used as the rescaled range. The average rescaled range for all window lengths is calculated, and the slope of the logarithmic fit is used as the periodic fractal parameter, expressed by the formula:

[0091]

[0092] In the formula, It is the average rescaled range. It is a constant. It is a periodic fractal parameter. It is the window length.

[0093] The steps for calculating the fractal dimension and performing complexity matching may include: in the time-transfer two-dimensional plane, using a side length of... The minimum number of square boxes required to cover the data curve is recorded. .

[0094] Change The fractal dimension is obtained by logarithmic fitting, and the formula is expressed as:

[0095]

[0096] In the formula, It is a constant. The absolute value of the fitted slope is the fractal dimension.

[0097] Based on the characteristics of transmission volume mutations, the effective time window is divided into multiple mutation stages, and the corresponding mutation fractal parameters are calculated.

[0098] Periodic fractal parameters and abrupt fractal parameters are classified and integrated according to key characteristics of transmission volume to form fractal features.

[0099] The steps for predicting time-period transmission changes include:

[0100] Based on fractal characteristics, the transmission volume trend defects for a future preset time period are generated as the initial baseline.

[0101] External factor data are categorized into natural environment, business scheduling, and operation and maintenance to obtain multiple influencing factors. A regression model is then constructed with the change in transmission volume to calculate the influence weight of different influencing factors.

[0102] The correction amount of influencing factors to the initial baseline is calculated from two aspects: persistence and suddenness. The formula is expressed as:

[0103]

[0104]

[0105] In the formula, It is a correction amount. It is the initial baseline. It affects the weight. It is the first Each influencing factor at time The value of , It is an indicator function. It is the first The moment the impact of a sudden factor begins. It is the first The moment when the impact of a sudden factor ends.

[0106] Based on the interaction between different influencing factors, a coupling coefficient is introduced to adjust the correction amount to obtain the total correction amount. This is then combined with the initial baseline to calculate the time-period transmission variation, expressed by the following formula:

[0107]

[0108]

[0109] In the formula, This is the total correction amount. It is a change in transmission over time. It is the coupling coefficient. It is the product of the single-factor correction values ​​of the i-th and j-th factors.

[0110] By analyzing the impact of data transmission volume on the data of communication equipment room, we obtained equipment temperature change data and formulated an initial temperature and humidity control strategy based on external factor data.

[0111] The steps to obtain equipment temperature change data include:

[0112] Align the data transmission volume with the data of the communication equipment room, and establish a correspondence between the equipment and the equipment from which the transmission volume originates.

[0113] The correlation between transmission volume and temperature for each device is calculated based on the device correspondence, and the temperature response delay is obtained through cross-correlation analysis. The basic impact characteristics are obtained by aggregating according to the device type.

[0114] The transmission quantity and temperature are analyzed in segments to identify nonlinear relationships and extract nonlinear influence characteristics.

[0115] Based on the influence patterns of basic and nonlinear influence characteristics on equipment temperature, and combined with the amount of data transmitted, equipment temperature change data is obtained.

[0116] Device temperature change data can include: a list of single device temperature changes: device ID, corresponding transmission volume change, and temperature change amount.

[0117] Regional temperature change curves: Display the temperature change trend for future periods by functional area (e.g., "Core server area is expected to rise by 5℃ from 10:00 to 12:00").

[0118] Sensitive Equipment List: Mark the equipment that is most sensitive to changes in transmission volume, and designate it as the key target for temperature control.

[0119] The steps for developing an initial temperature and humidity control strategy include:

[0120] Extract the safe temperature range for different types of equipment from the equipment temperature change data, and formulate temperature and humidity adjustment targets according to the functional equipment area.

[0121] The impact of external factors on temperature and humidity is categorized into three types: temperature interference, humidity interference, and indirect impact, and the direction of correction is determined accordingly.

[0122] Based on the temperature and humidity adjustment targets and correction directions, and combined with the execution devices that can be called by the DCS system, adjustment methods are formulated from three aspects: temperature control, humidity control, and coordinated regulation. The initial temperature and humidity regulation strategy is obtained by prioritizing the methods according to energy consumption and accuracy.

[0123] Temperature control methods: Precision air conditioning: The core area (high heat generation) uses "inverter cooling + zoned air supply", supporting temperature adjustment accuracy of ±0.5℃. The general area uses "fixed frequency cooling + unified air supply", with an adjustment accuracy of ±1℃.

[0124] Hot air return optimization: A guide vane is installed at the rear of the core area cabinet to direct hot air directly to the air conditioner return air vent, reducing heat diffusion (suitable for areas with fast heating rates).

[0125] Backup air conditioning linkage: When the load rate of the main air conditioner is >80% (such as during high temperatures in summer), the DCS automatically starts the backup air conditioner to share the cooling pressure.

[0126] Humidity control methods: Humidifier: The core area uses "ultrasonic humidification" (humidity adjustment accuracy ±3%RH), and the general area uses "electrode humidification" (accuracy ±5%RH).

[0127] Dehumidifier: During the rainy season, the DCS works in conjunction with the dehumidifier and air conditioner. The air conditioner lowers the air supply temperature (to accelerate water vapor condensation), and the dehumidifier simultaneously removes moisture.

[0128] Fresh air control: In dry winter, the DCS controls the opening of the fresh air valve (20%-30%) to introduce outdoor humid air (which needs to be pre-treated for temperature and humidity) to replenish the humidity of the computer room.

[0129] Coordinated control measures: Temperature and humidity linkage: When the temperature in the core area is close to the warning threshold (25℃) and the humidity is high (58%RH), the DCS will prioritize starting the air conditioning for cooling (while dehumidifying) to avoid temperature fluctuations caused by dehumidification alone.

[0130] Pre-regulation for specific time periods: One hour before business peak (e.g., if an e-commerce promotion starts at 9:00, pre-regulation is initiated at 8:00), the DCS lowers the core area temperature to the lower limit of the corrected ideal range (e.g., 20.5℃) in advance to reserve buffer space for temperature rise.

[0131] The initial temperature and humidity control strategy is adjusted based on the time-period transmission changes to obtain the temperature and humidity control strategy, which is then executed through the DCS.

[0132] The steps to adjust the temperature and humidity control strategy include:

[0133] Based on the time-period transmission change, the equipment temperature increment at different time periods is calculated to determine the basis for strategy adjustment, and conflict analysis is performed with the initial temperature and humidity control strategy to obtain demand control.

[0134] To address the demand regulation needs of different time periods, a list of adaptation gaps is obtained by recording the deficiencies of the initial temperature and humidity regulation strategies for each time period.

[0135] Based on the list of adaptation gaps and the controllable resources of the DCS system, temperature and humidity control strategies are obtained by adjusting the timing of control, equipment parameters, and collaborative logic.

[0136] High fever / high risk period: advance control + enhanced regulation timing adjustment (advance pre-cooling): start pre-cooling 1-2 hours before peak transmission volume to reserve temperature buffer space.

[0137] Equipment parameter adjustment (enhanced cooling capacity): Air conditioning parameters: During the pre-cooling phase, air conditioners #1 and #2 in the core area operate at full power (100%), and the supply air temperature is reduced from 14℃ to 12℃. During peak transmission periods (10:00-12:00), maintain full power. If the temperature still exceeds 25℃, start emergency mobile air conditioner #3 (connected to DCS monitoring).

[0138] Fans / Air Guide Plates: During the pre-cooling stage, the angle of the cabinet air guide plate is adjusted to 60° (maximum hot air guidance), and the emergency exhaust fan is started 1 hour in advance (80% speed).

[0139] Coordinated Logic Adjustment (Temperature and Humidity Linkage): Pre-cooling may cause a decrease in humidity (e.g., temperature drops from 20.5℃ to 16.5℃, humidity drops from 50% to 42%). The humidifier needs to be turned on simultaneously (at 20% power) to maintain humidity between 45% and 55% to avoid static electricity risks. During peak transmission periods, if humidity is <45%, the humidifier power should be increased to 30%.

[0140] During normal heating periods: Fine-tuning parameters + maintaining stable equipment parameters: No need for advance control, only when the transmission volume begins to increase, increase the power of the No. 1 air conditioner in the core area from 50% to 60%, and maintain the air supply temperature at 14℃ to avoid small temperature fluctuations.

[0141] Monitoring interval optimization: shortened from the usual 10 minutes / time to 5 minutes / time to ensure timely capture of temperature changes. If the temperature increase exceeds the prediction (e.g., the actual temperature reaches 2℃), the power will be increased to 70%.

[0142] Special scenarios (e.g., sudden drop in transmission volume): Avoid over-regulation. If a sudden drop in transmission volume is predicted for a certain period (e.g., from 800Mbps to 400Mbps after 12:00, and the temperature increment from 5℃ to 2℃), the strategy needs to be adjusted to avoid excessively low temperatures: 30 minutes before the transmission volume begins to drop, gradually reduce the air conditioner power (from 100% to 60%), and increase the supply air temperature from 12℃ to 14℃. After the temperature drops below 22℃, turn off air conditioner #2, and reduce the power of air conditioner #1 back to 50% to maintain the initial ideal temperature range.

[0143] like Figure 4 As shown, based on the same general inventive concept, this invention also protects a DCS-based temperature and humidity control system for communication equipment rooms, the control system comprising:

[0144] The data classification module is used to collect data transmission volume, communication equipment data, and external factor data, and classify the communication equipment data to obtain equipment function data.

[0145] The data transmission trend prediction module is used to analyze the data transmission volume based on the fractal method of data transmission characteristics to obtain the data change trend, and combine it with external factor data to predict the data change trend and obtain the time period transmission change.

[0146] The initial temperature and humidity control strategy module is used to analyze the impact of data transmission volume on the data of communication equipment room to obtain equipment temperature change data, and to formulate an initial temperature and humidity control strategy in combination with external factor data.

[0147] The time-period temperature control execution module is used to adjust the initial temperature and humidity control strategy according to the time-period transmission changes to obtain the temperature and humidity control strategy, and execute the temperature and humidity control strategy through DCS.

[0148] This embodiment provides a DCS-based method and system for temperature and humidity control in communication equipment rooms. By effectively classifying, preprocessing, and standardizing the data and transmission volume of the communication equipment room equipment, the data becomes more standardized and orderly, improving data processing efficiency and quality, and providing a reliable data foundation for subsequent analysis and decision-making. Using fractal analysis to analyze the transmission volume enables more accurate judgment of data change trends, providing strong support for predicting transmission changes over time periods and helping to prepare in advance. By analyzing the impact of data transmission volume on equipment temperature, an initial temperature and humidity control strategy is formulated and adjusted according to transmission changes over time periods, achieving more precise temperature and humidity control to meet the temperature and humidity requirements of the communication equipment room equipment and ensure its normal operation. When formulating the initial temperature and humidity control strategy, energy consumption and accuracy are considered, and priority is set for methods. When adjusting the strategy, the controllable resources of the DCS system are combined, which can improve energy utilization efficiency and control accuracy while ensuring control effectiveness and reducing operating costs. Through real-time analysis of transmission changes and equipment temperature changes over time periods, the temperature and humidity control strategy is adjusted in a timely manner, enabling the strategy to adapt to changes in different time periods, enhancing the adaptability and flexibility of the strategy, and better ensuring the stable operation of the communication equipment room.

[0149] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling temperature and humidity in a communication equipment room based on DCS, characterized in that, include: Data transmission volume, communication equipment room data, and external factor data are collected, and the communication equipment room data is classified to obtain equipment function data; The data transmission volume is analyzed using the fractal method of transmission characteristics to obtain the data change trend, and the data change trend is predicted by combining the external factor data to obtain the time period transmission change. The steps for analyzing and obtaining the trend of the data change include: Transform data from different sources and in different formats into a unified structure and standardize the data to obtain the data to be processed. The transmission volume statistical features, transmission volume periodic features, and transmission volume mutation features are extracted from the transmission volume processing data as key transmission volume features. Based on the key characteristics of the transmission volume, fractal features are extracted using fractal analysis methods to determine the trend characteristics of the transmission volume. Trend curves are generated based on the principle of self-similarity for analysis to obtain the data change trend. The steps for extracting the fractal features include: The effective time window for fractal analysis is determined based on the statistical characteristics of the transmission volume, and multiple periodic segments are obtained by segmenting according to the periodic characteristics of the transmission volume. The sliding R / S method is used to calculate the periodic fractal parameters of each periodic segment, and the fractal dimension is calculated for the periodic segments with drastic fluctuations to match the complexity. The effective time window is divided into multiple mutation stages based on the mutation characteristics of the transmission volume, and the corresponding mutation fractal parameters are calculated. The periodic fractal parameters and the mutation fractal parameters are classified and integrated according to the key characteristics of the transmission volume to form the fractal features; The impact of the data transmission volume on the data of the communication equipment room is analyzed to obtain equipment temperature change data, and an initial temperature and humidity control strategy is formulated in combination with the external factor data; The initial temperature and humidity control strategy is adjusted based on the time period transmission changes to obtain a temperature and humidity control strategy, which is then executed by the DCS.

2. The method for controlling temperature and humidity in a communication equipment room based on DCS according to claim 1, characterized in that, The steps for classifying and obtaining the device function data include: Classification criteria are defined based on the physical attributes, functional attributes, and operational characteristics of the equipment, and the equipment data in the communication equipment room is preprocessed to obtain equipment processing data. Based on the classification criteria, the data processed by the device is divided into a hierarchical structure, into a first level and a second level; Key parameters reflecting functional characteristics at each level are extracted and correlated with physical location to obtain the device functional data.

3. The method for controlling temperature and humidity in a communication equipment room based on DCS according to claim 1, characterized in that, The steps for predicting the transmission changes over the specified time period include: Based on the fractal characteristics, a future preset time period transmission volume trend defect is generated as an initial baseline; The external factor data is classified into natural environment, business scheduling and operation and maintenance to obtain multiple influencing factors. A regression model with the change in transmission volume is constructed to calculate the influence weight of different influencing factors. The correction amount of the influencing factors to the initial baseline is calculated from both the perspectives of persistence and suddenness. Based on the interaction between different influencing factors, a coupling coefficient is introduced to adjust the correction amount to obtain the total correction amount, and the time period transmission change is calculated in combination with the initial baseline.

4. The method for controlling temperature and humidity in a communication equipment room based on DCS according to claim 1, characterized in that, The formula for calculating the transmission change over the specified time period is expressed as follows: ； ； In the formula, This is the total correction amount. It is a change in transmission over time. It is the coupling coefficient. It is the first The and the first The product of the individual factor corrections for each factor. This is the initial baseline.

5. The method for controlling temperature and humidity in a communication equipment room based on DCS according to claim 1, characterized in that, The steps for obtaining the temperature change data of the device include: Align the data transmission volume with the data of the communication equipment room, and establish a correspondence between the equipment and the equipment from which the transmission volume originates; The correlation between transmission volume and temperature for each device is calculated based on the device correspondence, and the temperature response delay is obtained through cross-correlation analysis. The basic impact characteristics are obtained by aggregating them according to the device type. Segmented analysis of transmission volume and temperature is performed to identify nonlinear relationships and extract nonlinear influence characteristics. Based on the influence patterns of the basic influence characteristics and the nonlinear influence characteristics on the equipment temperature, the equipment temperature change data is obtained by combining the data transmission volume.

6. The method for controlling temperature and humidity in a communication equipment room based on DCS according to claim 1, characterized in that, The steps for formulating the initial temperature and humidity control strategy include: From the temperature change data of the equipment, the safe temperature range of different types of equipment is extracted, and temperature and humidity adjustment targets are set according to the functional equipment areas; The impact of the external factor data on temperature and humidity is categorized into temperature interference, humidity interference, and indirect impact, and the correction direction is determined accordingly. Based on the temperature and humidity adjustment target and the correction direction, and combined with the execution devices that can be called by the DCS system, adjustment methods are formulated from three aspects: temperature control, humidity control and coordinated regulation, and the initial temperature and humidity regulation strategy is obtained by prioritizing the methods according to energy consumption and accuracy.

7. The method for controlling temperature and humidity in a communication equipment room based on DCS according to claim 6, characterized in that, The steps for adjusting the temperature and humidity control strategy include: Based on the time-period transmission changes, the equipment temperature increment at different time periods is calculated to determine the basis for strategy adjustment, and conflict analysis is performed with the initial temperature and humidity control strategy to obtain demand control. For demand regulation in different time periods, an adaptation gap list is obtained based on the shortcomings of the initial temperature and humidity regulation strategy recorded in the time period records; Based on the aforementioned list of adaptation gaps and the controllable resources of the DCS system, the temperature and humidity control strategy is obtained by adjusting the timing of regulation, equipment parameters, and collaborative logic.

8. A DCS-based temperature and humidity control system for a communication equipment room, comprising the DCS-based temperature and humidity control method for a communication equipment room as described in any one of claims 1 to 7, characterized in that, The control system includes: The data classification module is used to collect data transmission volume, communication equipment room data, and external factor data, and classify the communication equipment room data to obtain equipment function data. The data transmission trend prediction module is used to analyze the data transmission volume according to the fractal method of data transmission characteristics to obtain the data change trend, and combine the external factor data to predict the data change trend to obtain the time period transmission change. The initial temperature and humidity control strategy formulation module is used to analyze the impact of the data transmission volume on the data of the communication equipment room to obtain the equipment temperature change data, and formulate the initial temperature and humidity control strategy in combination with the external factor data. The time-period temperature control execution module is used to adjust the initial temperature and humidity control strategy according to the time-period transmission changes to obtain a temperature and humidity control strategy, and execute the temperature and humidity control strategy through DCS.

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