Self-cleaning type intelligent positive pressure system for machine room or clean environment

Abstract

The invention belongs to the technical field of air conditioning, and particularly discloses a self-cleaning type intelligent positive pressure system for a machine room or a clean environment, which comprises a positive pressure maintaining module, a multi-stage air filtering module, a self-cleaning execution module and a central control module, the positive pressure maintaining module is used for inputting filtered air into the closed space, so that the internal air pressure of the space is higher than the external air pressure; the positive pressure maintaining module comprises a frequency conversion fan and a pressure sensor set used for detecting the internal and external pressure difference of the environment. The multi-stage air filtering module is arranged at the air inlet end of the frequency conversion fan and used for conducting multi-stage purification on sucked air. The self-cleaning execution module is connected with the multi-stage air filtering module and used for removing dust attached to the multi-stage air filtering module. The invention aims to solve the problem that a positive pressure system in the prior art cannot dynamically maintain a clean environment in a high-concentration and high-volatility dust pollution environment.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning, and in particular to a self-cleaning intelligent positive pressure system for a machine room or a clean environment. Background Art

[0002] In computer rooms (such as server rooms and communication rooms) and clean environments (such as electronic component production workshops and laboratories), stable equipment operation and environmental cleanliness are highly dependent on continuous positive pressure protection. By maintaining internal air pressure higher than the external pressure, it can effectively block the intrusion of pollutants such as dust, water vapor, and corrosive gases, thereby avoiding equipment short circuits, damage to precision components, or a decrease in product yield.

[0003] However, traditional positive pressure systems have two core pain points: First, filter components are prone to clogging due to long-term pollutant interception, requiring regular manual disassembly, replacement, or cleaning. This not only increases maintenance costs and downtime risks, but can also compromise environmental sealing during operation. Second, the systems often operate in a fixed air volume mode and are unable to dynamically adjust output based on real-time air pressure changes or pollutant concentrations, resulting in energy waste or failure of positive pressure protection (e.g., air pressure fluctuations causing backflow of external pollutants). Furthermore, computer rooms and clean environments have stringent requirements for airflow stability and noise control. The impact of fan start-up and shutdown, component wear noise, and the risk of secondary contamination during cleaning and maintenance further restrict their application in demanding scenarios. Summary of the Invention

[0004] The present invention provides a self-cleaning intelligent positive pressure system for a machine room or clean environment, aiming to solve the problem that the positive pressure system in the prior art cannot dynamically maintain a clean environment in a high-concentration, highly volatile dust pollution environment.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A self-cleaning intelligent positive pressure system for a computer room or clean environment, comprising a positive pressure maintaining module, a multi-stage air filtration module, a self-cleaning execution module and a central control module; the positive pressure maintaining module is used to input filtered air into a confined space so that the internal air pressure of the space is higher than the external air pressure; the positive pressure maintaining module includes a variable frequency fan and a pressure sensor group for detecting the pressure difference between the internal and external environments; the multi-stage air filtration module is arranged at the air inlet end of the variable frequency fan and is used to perform multi-stage purification on the inhaled air; the self-cleaning execution module is connected to the multi-stage air filtration module and is used to remove dust attached to the multi-stage air filtration module; the central control module is electrically connected to the pressure sensor group, the variable frequency fan and the self-cleaning execution module respectively, and the central control module is configured to receive the pressure difference signal of the pressure sensor group and dynamically adjust the speed of the variable frequency fan through a PID algorithm to maintain a set micro-positive pressure value; and control the self-cleaning execution module to perform cleaning operations according to preset conditions or feedback from at least one of the sensors.

[0007] In one aspect of the present disclosure, the multi-stage air filtration module includes at least a primary filter, a medium-efficiency filter and a high-efficiency filter arranged in sequence along the air flow direction; the self-cleaning execution module includes a high-pressure pulse air blowing unit arranged on the primary filter and the medium-efficiency filter; and an ultrasonic vibration unit, which is arranged on the high-efficiency filter and is used to clean the high-efficiency filter.

[0008] In one aspect of the present disclosure, the system also includes a dust concentration sensor and a filter pressure differential sensor, and the filter pressure differential sensor is used to monitor the pressure drop on both sides of the primary filter, the medium efficiency filter and the high efficiency filter; the central control module is also configured to trigger the self-cleaning execution module to work when at least one of the two situations occurs: the pressure drop monitored by the filter pressure differential sensor exceeds a first preset threshold, or the dust concentration sensor detects a sudden change in external dust concentration and enters a stable period.

[0009] In one aspect of the present disclosure, the system also includes an edge computing unit with a built-in machine learning algorithm, which is configured to predict the dust concentration change trend in the future time period based on historical environmental data and external operation data; and a communication module, through which the central control module is connected to the cloud server; the central control module is used to adjust the operation strategy of the variable frequency fan in advance according to the predicted dust concentration change trend.

[0010] In one aspect of the present disclosure, the external operating data includes a coal train schedule, and the operating strategy includes controlling the variable frequency fan to increase speed and switch to a higher level of filtration mode before a predicted dust concentration peak arrives.

[0011] In one aspect of the present disclosure, the system also includes an environmental integrated sensor group, which is used to monitor one or more of the temperature and humidity in the enclosed space; the central control module is configured to dynamically adjust the ventilation volume based on a multi-objective optimization algorithm, and coordinately control the temperature and humidity and dilute harmful gases while maintaining a slightly positive pressure.

[0012] In one aspect of the present disclosure, the system further includes a renewable energy power supply module, which is used to provide auxiliary or main power for the variable frequency fan, the central control module and the self-cleaning execution module.

[0013] In one aspect of the present disclosure, the system further includes a heat recovery unit, which is connected between the exhaust duct and the fresh air duct of the system and is used to pre-treat the input fresh air through heat exchange to reduce the overall energy consumption of the system.

[0014] In one aspect of the present disclosure, the central control module is further configured to perform trend analysis and implement predictive maintenance based on the operating current and vibration sensor data of the variable frequency fan, and issue an early warning signal before a target component failure occurs.

[0015] In one aspect of the present disclosure, the renewable energy power supply module mainly includes a solar photovoltaic panel and an energy storage battery. The solar photovoltaic panel is installed on the top of the computer room, connected to the storage battery, and used to provide electrical energy to the storage battery; the storage battery is installed inside the computer room and is used to power the electrical equipment in the system.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The present invention combines a pressure sensor group, a variable frequency fan, and a PID algorithm in a central control module to form a closed-loop negative feedback control system. The system can monitor the pressure difference in real time and dynamically adjust the fan power through an algorithm, thereby dynamically maintaining a micro-positive pressure environment, effectively resisting external interference, maintaining pressure stability, and fundamentally blocking dust intrusion. By also introducing a self-cleaning execution module, the system is no longer a purely consumable product, that is, there is no need to replace the filter when it is clogged. Instead, it has the ability to self-maintain. It can automatically remove some dust from the filter, greatly extending the filter replacement cycle, thereby directly reducing spare parts costs, logistics costs, and expensive manual maintenance times. Finally, the multi-stage air filtration module ensures high filtration accuracy, ensuring that only clean air can enter the machine room. At the same time, the dynamic positive pressure maintenance and self-cleaning functions work together to ensure the long-term stability and reliability of the system, providing internal equipment with an ultra-clean operating environment that far exceeds national standards, thereby significantly reducing equipment failure rates. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0019] Figure 1 This is a flow chart of the positive pressure maintenance module in the present invention.

[0020] Figure 2 This is a flow chart of the multi-stage air filtration module in the present invention.

[0021] Figure 3 This is a flow chart of the edge computing and communication module in the present invention. DETAILED DESCRIPTION

[0022] The present invention will be further described below in conjunction with the embodiments. The embodiments described are only some embodiments of the present invention and are not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0023] Example 1

[0024] See also Figure 1-Figure 3 As shown, this embodiment discloses a self-cleaning intelligent positive pressure system for a computer room or clean environment, including a positive pressure maintenance module, a multi-stage air filtration module, a self-cleaning execution module and a central control module; the positive pressure maintenance module is used to input filtered air into a confined space so that the internal air pressure of the space is higher than the external air pressure; the positive pressure maintenance module includes a variable frequency fan and a pressure sensor group for detecting the pressure difference between the internal and external environments; the multi-stage air filtration module is arranged at the air inlet end of the variable frequency fan and is used to perform multi-stage purification on the inhaled air; the self-cleaning execution module is connected to the multi-stage air filtration module and is used to remove dust attached to the multi-stage air filtration module; the central control module is electrically connected to the pressure sensor group, the variable frequency fan and the self-cleaning execution module respectively, and the central control module is configured to receive the pressure difference signal of the pressure sensor group and dynamically adjust the speed of the variable frequency fan through a PID algorithm to maintain a set micro-positive pressure value; and control the self-cleaning execution module to perform cleaning operations according to preset conditions or feedback from at least one of the sensors.

[0025] The present invention combines a pressure sensor group, a variable frequency fan, and a PID algorithm in a central control module to form a closed-loop negative feedback control system. The system can monitor the pressure difference in real time and dynamically adjust the fan power through an algorithm, thereby dynamically maintaining a micro-positive pressure environment, effectively resisting external interference, maintaining pressure stability, and fundamentally blocking dust intrusion. By also introducing a self-cleaning execution module, the system is no longer a purely consumable product, that is, there is no need to replace the filter when it is clogged. Instead, it has the ability to self-maintain. It can automatically remove some dust from the filter, greatly extending the filter replacement cycle, thereby directly reducing spare parts costs, logistics costs, and expensive manual maintenance times. Finally, the multi-stage air filtration module ensures high filtration accuracy, ensuring that only clean air can enter the machine room. At the same time, the dynamic positive pressure maintenance and self-cleaning functions work together to ensure the long-term stability and reliability of the system, providing internal equipment with an ultra-clean operating environment that far exceeds national standards, thereby significantly reducing equipment failure rates.

[0026] In some embodiments, PID is an abbreviation of proportional, integral and derivative, and its core is to calculate the control output based on the current error, the accumulation of past errors and the trend of future errors;

[0027] The continuous-time ideal algorithm formula is configured as:

[0028]

[0029] in, It represents the control output at time t, which corresponds to the target speed command of the variable frequency fan in this system and is used to adjust the air intake to control the pressure difference between the inside and outside of the machine room;

[0030] Indicates the proportional coefficient, which is different from the current deviation It is directly proportional to the intensity of the response to the current deviation;

[0031] express The pressure difference deviation at each moment is used to quantify the difference between the actual internal and external pressure difference of the computer room and the set target positive pressure value, providing a basis for the subsequent dynamic adjustment of the variable frequency fan speed;

[0032] Indicates the integration time, which eliminates the system steady-state error by accumulating historical deviations The smaller it is, the stronger the integral effect is;

[0033] It represents the integral of the deviation from the initial moment to the moment t, that is, the cumulative sum of historical deviations. Its function is to solve the problem that proportional control cannot eliminate the steady-state error;

[0034] Indicates the differential time. By calculating the rate of change of the deviation, the future trend of the deviation is predicted and adjustments are made in advance to suppress system overshoot.

[0035] Indicates the rate of change of the deviation, reflecting the speed and direction of the deviation change over time. Its function is to provide advanced control and enhance system stability;

[0036] Since the central control module, that is, PLC, is a digital system, it measures and calculates with a fixed sampling period T, so the discretized PID formula must be used. This is the form actually used in actual programming.

[0037] At K sampling moments, PID output The calculation formula is configured as:

[0038]

[0039] in, Indicates the current sampling sequence number. =0, 1, 2, 3...;

[0040] Indicates the sampling period, that is, how long the PLC calculates the PID, for example 100ms;

[0041] Indicates the The error value at the time of sampling;

[0042] Indicates the times, which is the error value at the last sampling;

[0043] Represents the cumulative sum of all error values ​​from the beginning to the current moment;

[0044] It represents the difference between the current error and the previous error divided by time, which is approximately the differential.

[0045] In order to avoid starting the calculation from 0 each time, the incremental PID algorithm is usually used in programming, which only calculates the change in the output Δ , more suitable for application: .

[0046] at last, = .

[0047] Therefore, in actual use, the control loop in the PLC is as follows:

[0048] 1. Sampling: Read the specific value of the pressure sensor at a period of T;

[0049] 2. Calculation error: calculated using the deviation formula;

[0050] 3. Calculate PID output: Use discrete formula to calculate standard signal ;

[0051] 4. Output execution: The signal is sent to the frequency converter, which adjusts the power frequency supplied to the fan according to the signal, thereby accurately controlling the fan speed.

[0052] 5. Wait for the next cycle: Sleep until the next sampling cycle arrives and repeat step 1 for sampling.

[0053] By properly adjusting the PID parameters, the system can quickly, smoothly and accurately compensate for disturbances such as tunnel piston wind, and stabilize the positive pressure within a preset range.

[0054] Example 2

[0055] See also Figure 1-Figure 3 As shown, this embodiment is further optimized on the basis of embodiment one. In this embodiment, the multi-stage air filtration module includes at least a primary filter, a medium-efficiency filter and a high-efficiency filter arranged in sequence along the air flow direction; the self-cleaning execution module includes a high-pressure pulse air blowing unit arranged on the primary filter and the medium-efficiency filter; and an ultrasonic vibration unit, which is arranged on the high-efficiency filter and is used to clean the high-efficiency filter.

[0056] In some embodiments, the system also includes a dust concentration sensor and a filter pressure differential sensor, and the filter pressure differential sensor is used to monitor the pressure drop on both sides of the primary filter, the medium efficiency filter and the high efficiency filter; the central control module is also configured to trigger the self-cleaning execution module to work when at least one of the two situations occurs: the pressure drop monitored by the filter pressure differential sensor exceeds a first preset threshold, or the dust concentration sensor detects a sudden change in external dust concentration and enters a stable period.

[0057] In some embodiments, the system also includes an edge computing unit with a built-in machine learning algorithm, which is configured to predict the dust concentration change trend in future time periods based on historical environmental data and external operation data; and a communication module, through which the central control module is connected to the cloud server; the central control module is used to adjust the operation strategy of the variable frequency fan in advance according to the predicted dust concentration change trend.

[0058] During actual use, the edge computing unit and the machine learning algorithm realize three major functions, namely dust prediction, fault warning and adaptive control. The edge computing unit receives time series data streams from various sensors. The software stack running inside it includes a data preprocessing module, a feature extraction module and one or more lightweight machine learning models. The processing results are sent to the central control module, namely PLC, through the communication bus to execute the final decision.

[0059] In some embodiments, the external operating data includes a coal train schedule, and the operating strategy includes controlling the variable frequency fan to increase speed and switch to a higher level of filtering mode before a predicted dust concentration peak arrives.

[0060] In some embodiments, the system also includes an environmental integrated sensor group, which is used to monitor one or more of the temperature and humidity in the enclosed space; the central control module is configured to dynamically adjust the ventilation volume based on a multi-objective optimization algorithm, and coordinately control the temperature and humidity and dilute harmful gases while maintaining a slightly positive pressure.

[0061] In some embodiments, the system further includes a renewable energy power supply module, which is used to provide auxiliary or main power for the variable frequency fan, the central control module and the self-cleaning execution module.

[0062] In some embodiments, the system further includes a heat recovery unit, which is connected between the exhaust duct and the fresh air duct of the system and is used to pre-treat the input fresh air through heat exchange to reduce the overall energy consumption of the system.

[0063] In some embodiments, the central control module is further configured to perform trend analysis and implement predictive maintenance based on the operating current and vibration sensor data of the variable frequency fan, and issue an early warning signal before a target component failure occurs.

[0064] In some embodiments, the renewable energy power supply module mainly includes solar photovoltaic panels and energy storage batteries. The solar photovoltaic panels are installed on the top of the computer room, connected to the storage batteries, and used to provide electrical energy to the storage batteries; the storage batteries are installed inside the computer room and are used to power the electrical equipment in the system.

[0065] As an optional implementation, in this embodiment, for example: the positive pressure maintenance module is a DC variable frequency centrifugal fan with a rated power of 5.5kW, a nominal air volume of 1000 m³ / h, and stepless speed regulation within the range of 0-50Hz.

[0066] The air inlet and outlet of the fan are connected to the air duct through flanges to ensure air tightness;

[0067] The pressure sensor group used to detect pressure differentials uses MEMS silicon capacitive pressure sensors with a range of 0-1kPa, an accuracy of ±0.1%FS, and an operating temperature of -40°C-125°C. The two sensors are precisely installed on the inner and outer walls of the computer room with a spacing of less than 2 meters. The pressure differential data is transmitted to the central control module in real time via the RS485 bus at a sampling frequency of 10Hz.

[0068] The multi-stage air filtration module adopts a three-stage progressive filtration design and is installed at the air inlet end of the fan.

[0069] The primary filter uses a G4-grade non-woven fabric filter, which mainly intercepts large dust particles with a particle size of ≥5μm and a dust holding capacity of up to 500g / m². Its frame is made of aluminum alloy and is easy to disassemble and assemble.

[0070] The medium-efficiency filter adopts F7-grade industrial bag filter, and the filtration efficiency for particles with a diameter of ≥1μm is not less than 95%.

[0071] The high-efficiency filter uses H13 grade glass fiber filter paper, and the filtration efficiency for particles with a size of ≥0.3μm is not less than 99.97%.

[0072] Among them, each filter unit is equipped with independent mounting rails and sealing strips to prevent airflow short-circuiting, and filter pressure differential sensors are installed on both sides of each filter. For example: based on the micro-pressure differential sensor chip, it is used to monitor the filter blockage in real time. When the pressure difference of the primary filter exceeds 150Pa, the medium-efficiency filter exceeds 300Pa, and the high-efficiency filter exceeds 500Pa, the sensor will send an alarm signal to the control system.

[0073] The self-cleaning execution module is mainly composed of a high-pressure pulse air blowing unit and an ultrasonic vibration unit. The high-pressure pulse air blowing unit is set for the primary filter and the medium-efficiency filter. The unit includes a small air compressor, an air tank and a set of Venturi blowpipe arrays embedded in the filter frame. The Venturi blowpipe is provided with multiple nozzles aimed at the filter material. When the control solenoid valve receives the signal, the high-pressure air in the air tank is instantly ejected through the nozzle, forming a strong pulse airflow, penetrating the filter material, causing the dust to fall off, and the fallen dust is collected in the ash hopper at the bottom. The ash hopper is equipped with a manual or electric ash discharge valve.

[0074] The ultrasonic vibration unit is designed for high-efficiency filters. It consists of an ultrasonic generator and a conduction plate. The conduction plate is tightly coupled with the frame of the high-efficiency filter. When started, the ultrasonic generator generates a low frequency, such as 20-40kHz, or any low-power mechanical vibration, which is transmitted to the entire filter through the conduction plate, causing embedded ultrafine particles, especially PM2.5, to loosen and detach from the filter material fibers due to high-frequency vibration. This process is usually performed when the system is briefly shut down or running at low air volume to avoid secondary inhalation of dust; the loosened dust can be carried away by subsequent normal airflow or an auxiliary slight negative pressure suction port.

[0075] The system also includes a sensing and perception system, including a dust concentration sensor, an environmental integrated sensor group, and a vibration sensor. The dust concentration sensor uses a laser scattering principle sensor to monitor the PM2.5 and PM10 concentrations inside and outside the computer room in real time, with a measurement range of 0-1000μg / m³ and an accuracy of ±10%.

[0076] The comprehensive environmental sensor group integrates temperature and humidity sensors, CO electrochemical sensors, and NO2 electrochemical sensors. This sensor group is installed in the equipment area inside the computer room to comprehensively assess the environmental quality.

[0077] Vibration sensors are installed on the fan motor and non-rotating parts to monitor the health of the equipment.

[0078] The auxiliary energy-saving unit is mainly composed of a renewable energy power supply module and a heat recovery unit. Among them, the renewable energy power supply module is installed with a set of flexible monocrystalline silicon solar photovoltaic panels with a peak power of 2kW in an open area at the tunnel entrance or on the roof of the machine room, coupled with a set of 48V / 200Ah lithium iron phosphate energy storage batteries and an intelligent controller. This module can independently power the system's control part and sensors all year round, and assist in driving the wind turbine when there is sufficient sunshine, significantly reducing mains electricity consumption.

[0079] The heat recovery unit uses a plate-fin sensible heat recovery device. The new exhaust air ducts cross-flow through the recovery device but do not mix with each other. In winter, the waste heat of the exhaust air is used to preheat the cold fresh air; in summer, the low-temperature exhaust air is used to cool the high-temperature fresh air. The measured heat recovery efficiency can reach more than 60%, effectively reducing the load on the computer room air conditioner.

[0080] During actual use, the program in the central control module controls the entire system to operate according to the following logic.

[0081] S1: Basic positive pressure maintenance: PLC continuously reads the pressure difference signal of the pressure sensor group. Set the target positive pressure value The pressure is 25 Pa, and the PLC's built-in PID control algorithm calculates the deviation in real time as follows:

[0082] And output the control signal to the frequency converter to dynamically adjust the fan speed and stabilize the actual pressure difference within the range of the set value ±2Pa.

[0083] S2: Intelligent self-cleaning control: Self-cleaning is not triggered on a fixed time basis, but is based on multi-condition intelligent decision-making;

[0084] S201: When the filter is clogged, if the reading of any filter differential pressure sensor exceeds its set threshold for 5 minutes, the PLC determines that the filter is clogged and needs to be cleaned;

[0085] S202: When an external event occurs, the dust concentration sensor detects that the external PM10 concentration instantly soars due to the passage of a train and then returns to the baseline level. This indicates that a large dust invasion has ended and a large amount of dust has attached to the filter. The PLC will trigger a preventive cleaning at this time.

[0086] S203: After being triggered, the PLC first controls the fan to slow down to the lowest frequency, and then starts the high-pressure pulse air blowing in the corresponding self-cleaning unit according to the filter type, blowing a group of filter bags each time, with an interval of 5 seconds, and a cycle of 3 times. The ultrasonic vibration continues to run for 2 minutes. After the cleaning is completed, the fan resumes normal operation, and the PLC continues to monitor the pressure difference changes to evaluate the cleaning effect.

[0087] S3: Prediction and proactive regulation: A trained long short-term memory neural network model is deployed on the edge computing unit;

[0088] S301: Data input. Model input includes local historical dust concentration data, real-time train schedules obtained from the railway information system via an API, wind speed and direction data in tunnels, and weather forecast information.

[0089] S302: Prediction and Decision-Making: The model runs every 10 minutes, predicting the PM2.5 concentration curve at the machine room entrance over the next hour. If a concentration peak is predicted in 15 minutes due to a passing train, the edge computing unit sends a command to the PLC.

[0090] S303: Execution: After receiving the instruction, the PLC starts the strengthening mode 5 minutes in advance and sets the target positive pressure value From 25Pa to 35Pa, the upper limit of the fan speed is increased by 20%, and part of the fresh air channel can be bypassed to ensure sufficient air volume to maintain high pressure. After the peak, the system automatically returns to normal mode.

[0091] S4: Multi-objective collaborative optimization: The integrated control algorithm of the PLC needs to balance multiple and sometimes conflicting objectives;

[0092] S401: Determine priorities, with maintaining positive pressure being the highest priority, equipment heat dissipation being the second priority, and energy conservation and hazardous gas control being the third priority;

[0093] S402: When the room temperature T > 28°C, while maintaining a minimum positive pressure (e.g., 10 Pa), appropriately increase the fan speed and ventilation frequency to aid heat dissipation.

[0094] S403: When the CO concentration in the equipment room is > 15ppm, the system generates an alarm and calculates and executes the minimum required fresh air dilution volume while maintaining positive pressure;

[0095] S404: At night or during periods without vehicles, if the environmental parameters are normal, the system automatically enters energy-saving mode, operates at the lowest speed to maintain a positive pressure of approximately 10Pa, and gives priority to using solar power.

[0096] S5: Predictive maintenance: The system continuously monitors the operating current and vibration spectrum of the fan, performs time and frequency domain analysis through the edge computing unit, and establishes a health baseline. Once abnormal current fluctuations or vibration energy is significantly enhanced at a specific frequency, such as the characteristic frequency of a bearing fault, the system will send an early warning message to the operation and maintenance personnel more than one week in advance, even if the equipment is still operating normally, to indicate possible bearing wear or impeller imbalance and recommend planned maintenance.

[0097] In the description of the present invention, it should be understood that the terms "coaxial", "bottom", "one end", "top", "middle", "the other end", "upper", "one side", "top", "inside", "front", "center", "two ends", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0098] In addition, the terms "first", "second", "third" and "fourth" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first", "second", "third" and "fourth" may explicitly or implicitly include at least one such feature.

[0099] In the present invention, unless otherwise clearly stipulated and limited, the terms such as "installation", "setting", "connection", "fixation" and "screw-on" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integrated connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. Unless otherwise clearly defined, ordinary technicians in this field can understand the specific meanings of the above terms in the present invention according to the specific circumstances.

[0100] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A self-cleaning intelligent positive pressure system for a machine room or clean environment, characterized in that: include: A positive pressure maintenance module is used to input filtered air into the confined space to make the internal pressure of the space higher than the external pressure; the positive pressure maintenance module includes a variable frequency fan and a pressure sensor group for detecting the pressure difference between the internal and external environment; A multi-stage air filtration module is provided at the air inlet end of the variable frequency fan and is used to perform multi-stage purification on the inhaled air; a self-cleaning execution module connected to the multi-stage air filtration module and used to remove dust attached to the multi-stage air filtration module; The central control module is electrically connected to the pressure sensor group, the variable frequency fan and the self-cleaning execution module respectively. The central control module is configured to receive the pressure difference signal of the pressure sensor group and dynamically adjust the speed of the variable frequency fan through the PID algorithm to maintain the set micro-positive pressure value; and control the self-cleaning execution module to perform cleaning operations according to preset conditions or feedback from at least one of the sensors.

2. A self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 1, characterized in that: The multi-stage air filtration module at least includes: A primary filter, a medium filter and a high efficiency filter are sequentially arranged along the air flow direction; the self-cleaning execution module includes a high-pressure pulse air blowing unit arranged on the primary filter and the medium filter; as well as The ultrasonic vibration unit is arranged on the high-efficiency filter and is used for cleaning the high-efficiency filter.

3. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 2, characterized in that: The system also includes a dust concentration sensor and a filter pressure difference sensor, wherein the filter pressure difference sensor is used to monitor the pressure drop on both sides of the primary filter, the medium efficiency filter and the high efficiency filter; The central control module is also configured to trigger the self-cleaning execution module to operate when at least one of the following two situations occurs: the pressure drop monitored by the filter pressure difference sensor exceeds a first preset threshold, or the dust concentration sensor detects that the external dust concentration enters a stable period after a sudden change.

4. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 1, characterized in that: The system further includes, The edge computing unit, with built-in machine learning algorithms, is configured to predict dust concentration trends in future time periods based on historical environmental data and external operational data; and A communication module, through which the central control module is connected to the cloud server; The central control module is used to adjust the operation strategy of the variable frequency fan in advance according to the predicted dust concentration change trend.

5. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 4, characterized in that: The external operation data includes a coal train schedule, and the operation strategy includes controlling the variable frequency fan to increase speed and switch to a higher level of filtering mode before a predicted dust concentration peak arrives.

6. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 1, characterized in that: The system further includes, An environmental integrated sensor group for monitoring one or more of temperature and humidity in a confined space; The central control module is configured to dynamically adjust the ventilation volume based on a multi-objective optimization algorithm, coordinately control the temperature and humidity and dilute harmful gases while maintaining a slightly positive pressure.

7. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 1, characterized in that: The system further includes, The renewable energy power supply module is used to provide auxiliary or main power for the variable frequency fan, the central control module and the self-cleaning execution module.

8. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 1, characterized in that: The system further includes, The heat recovery unit is connected between the exhaust duct and the fresh air duct of the system and is used to pre-treat the input fresh air through heat exchange to reduce the overall energy consumption of the system.

9. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 1, characterized in that: The central control module is further configured to perform trend analysis and implement predictive maintenance based on the operating current and vibration sensor data of the variable frequency fan, and issue an early warning signal before a target component failure occurs.

10. The self-cleaning intelligent positive pressure system for a computer room or clean environment according to claim 7, characterized in that: The renewable energy power supply module mainly includes solar photovoltaic panels and energy storage batteries. The solar photovoltaic panels are installed on the top of the computer room, connected to the storage batteries, and used to provide electricity to the storage batteries; the storage batteries are installed inside the computer room and are used to power the electrical equipment in the system.

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