Machine room equipment diagnosis method based on sensing and digitization cooperation

Abstract

The invention discloses a machine room equipment diagnosis method based on sensing and digitization cooperation, and belongs to the technical field of digitization inspection. The method solves the problem that the updating of the existing electromechanical equipment is lack of a scientific detection method, formulates a scientific and reasonable machine room equipment performance test and physical examination scheme by comparing various test parameters of the unit with the preset threshold value, assists factory data of the unit and various report bills as references, sets the threshold value, and improves the reliability of the machine room equipment performance test and physical examination. The authenticity of threshold setting and the accuracy of machine room equipment diagnosis are further improved; by comparing the real-time data with the preset threshold value, the abnormity is quickly identified; after the unit is identified to be abnormal, the real-time data and the multi-dimensional parameters are comprehensively analyzed based on the decision tree, a closed-loop mechanism of threshold dynamic monitoring-multi-parameter decision analysis-intelligent diagnosis is formed, and the robustness of machine room equipment performance judgment is ensured.

Description

Technical Field

[0001] The present invention relates to the field of digital inspection technology, and in particular to a computer room equipment diagnosis method based on sensing and digital collaboration. Background Art

[0002] As a crucial component of a building's mechanical and electrical systems, many buildings face aging and damage over time, low operational efficiency, and poor user experience, impacting operational quality and system safety. To address these issues, mechanical and electrical systems require varying degrees of repair, updating, and renovation. This not only improves building safety and comfort, but also maximizes building functionality and enhances building quality.

[0003] However, current mechanical and electrical equipment upgrades often lack scientific testing methods, leading to a blanket approach to renovations and upgrades. This often involves wholesale demolition, making them incompatible with building usage requirements. The lack of scientific testing methods for machine room units makes it impossible to determine a suitable replacement timeline. This leads to the premature demolition of some reusable machine rooms, while obsolete units remain operational, undermining the energy-saving requirements of urban machine room equipment renewal.

[0004] To this end, we proposed a computer room equipment diagnosis method based on sensing and digital collaboration. Summary of the Invention

[0005] The purpose of the present invention is to provide a computer room equipment diagnosis method based on sensing and digital collaboration, which avoids data packet loss or interruption due to signal attenuation by comparing communication distance parameters with preset thresholds; verifies the rationality of data volume and type through a second reference coefficient to ensure the accuracy of data reception, lays a solid data foundation for subsequent formulation of thresholds based on factory data and historical data, improves the authenticity of threshold setting and the accuracy of computer room equipment diagnosis; quickly identifies abnormal signals by comparing real-time data with preset thresholds; after identifying abnormal signals, conducts a comprehensive analysis of real-time data and multi-dimensional parameters based on a decision tree, forming a closed-loop mechanism through threshold dynamic monitoring-multi-parameter decision analysis-intelligent diagnosis, ensuring the robustness of computer room equipment performance judgment, and solving the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A computer room equipment diagnosis method based on sensing and digital collaboration includes the following steps: Deploy various sensors on water pumps, chillers, and cooling towers to collect real-time operating parameters of the refrigeration units in the computer room; Build a database to store factory data, real-time data, and historical data of the refrigeration units in the computer room; Set thresholds based on factory data and historical data, and regularly compare real-time data with the thresholds to determine the energy consumption status of the computer room's refrigeration units; Some refrigeration units' energy consumption records, due to the lack of automatic metering in older equipment, can only be understood based on electricity bills. In this case, the energy consumption status of each unit can be determined by combining the refrigeration unit's operating time, that is, nighttime and daytime peak and off-peak electricity prices. The operating records of a single unit and the monthly electricity bills of the equipment group are combined to determine the energy consumption status of each unit. Decision tree technology was introduced to extract feature information from historical data. Labels were defined based on the operating status of the refrigeration units in the computer room. The decision tree model was used to train the historical data and learn the relationships between different features. When there are abnormalities in the comparison results, the feature information of the real-time data is extracted through the decision tree, the comparison results and feature information are comprehensively analyzed, and the analysis results are output to accurately determine the operating status of the refrigeration unit in the computer room.

[0007] Furthermore, thresholds are set based on factory data and historical data. Real-time data is regularly compared with the thresholds to determine the energy consumption status of the refrigeration units in the computer room. Specifically: Regularly obtain the latest factory data and historical data of the computer room refrigeration units stored in the database for the past six months; Based on factory data and industry standards, extract the equipment's operating data or operating data of each frequency from the historical data table, calculate the average energy efficiency (COP) cooling capacity to power consumption ratio of the historical data, and analyze the fluctuation range of the historical energy efficiency (COP) cooling capacity to power consumption ratio; Based on the service life and maintenance records of the refrigeration units in the computer room, regularly optimize the reasonable threshold range and dynamically adjust the threshold according to actual conditions; Regularly extract data from the electricity bill and actual cooling capacity of the refrigeration unit, calculate the actual energy efficiency (COP) cooling capacity to power consumption ratio, and compare the actual ratio with the threshold; If the actual ratio is lower than the threshold, it indicates that the energy consumption of the refrigeration unit in the computer room is abnormal and triggers a verification alarm; For older equipment rooms without storage platforms and individual energy meters for chillers, pumps, and cooling towers, but with a master meter to measure the overall energy consumption of the chiller room, estimate the total cooling capacity actually required each month by fitting the building's temperature, area, occupancy density, thermal inertia of the building envelope, and the use of heat dissipation equipment; The determination of the energy consumption status of the water pump includes but is not limited to the following steps: Calculate the hourly flow rate of the chilled water pump based on the chilled water supply and return water temperature difference and the total cooling load of the system; According to the pipeline characteristic relationship of the chilled water system, calculate the relationship between the flow rate in the pipeline and the pressure head of the pipeline system; Calculate the required head, shaft power and energy consumption of the water pump in the distribution system based on the relationship between the shaft power, flow rate and head of the variable frequency pump; Calculate the hourly flow rate required by the chilled water pump pipeline based on the hourly cooling load throughout the year, and calculate the hourly resistance throughout the year based on the equipment parameters and characteristic curve; According to the flow-efficiency relationship curve of the water pump, the hourly efficiency of the water pump is obtained, and the cumulative energy consumption of the chilled water pump for the whole year is calculated.

[0008] Furthermore, formulating thresholds based on factory data and historical data also includes the following steps: The historical data of the refrigeration unit in the computer room is transmitted to the cloud platform through wireless communication technology; Obtain the communication distance parameter between the computer room and the cloud platform as the first reference coefficient; A communication distance threshold is pre-set, and a communication distance parameter is compared with the communication distance threshold to determine whether the communication distance parameter is within the network distance threshold range; if so, it indicates that the first reference coefficient is accurate; if the first reference coefficient is not within the network distance threshold range, a wired transmission communication mode is considered; Obtain the amount and type of historical data uploaded by the refrigeration unit in the computer room as the second reference coefficient; Preset upper and lower floating thresholds, compare the data volume and data type of historical data uploaded with the upper and lower floating thresholds, and determine whether the data volume and data type of historical data uploaded are within the upper and lower floating thresholds; if so, it indicates that the second reference coefficient is accurate; The verification results of the first reference coefficient and the second reference coefficient are combined to verify whether the uploaded results of the historical data of the refrigeration unit in the computer room are accurate.

[0009] Furthermore, the comparison results and feature information are comprehensively analyzed and the analysis results are output to accurately determine the operating status of the refrigeration unit in the computer room, specifically: After a verification alarm is triggered, the comparison results and real-time data are used as the main analysis factors. The age of the refrigeration units in the computer room, maintenance records, and seasonal climate are used as multiple parameters and simultaneously input into the decision tree for training. Analyze the relationship between different features and labels in the main analysis factors through decision tree analysis, and conduct comprehensive analysis on multiple parameters; Based on the decision rules, the operating status of the refrigeration unit in the computer room can be further judged to avoid misjudgment caused by relying on a single comparison result; Based on the judgment results, determine whether the computer room refrigeration unit needs to be replaced.

[0010] Furthermore, the comparison results and feature information are comprehensively analyzed and the analysis results are output, which also includes the following steps: Based on the comparison results of the actual energy efficiency COP cooling capacity to power consumption ratio and the threshold value, combined with the analysis results of the decision tree, a line graph of the energy efficiency COP cooling capacity to power consumption ratio and different parameters is drawn; Analyze the changing trend of the ratio of energy efficiency (COP) cooling capacity to power consumption in the line chart. If the ratio shows a clear downward trend and the decline exceeds the set threshold, it indicates that the cooling efficiency of the computer room refrigeration unit is on a downward trend.

[0011] Furthermore, based on the judgment results, it is determined whether the refrigeration unit in the computer room needs to be replaced, specifically: Obtain the judgment results of historical data and preliminarily classify the judgment results of historical data, including: repairable failures and irreversible damage or high-cost failures; For repairable faults, it is recommended to prioritize maintenance measures and monitor whether the parameters return to normal range after repair; For irreversible damage or high-cost failures, maintenance or replacement of equipment is recommended based on the failure factors.

[0012] Furthermore, for irreversible damage or high-cost failures, maintenance or replacement of equipment is recommended based on the failure factors, specifically: Conduct an economic analysis for irreversible damage or high-cost failures, comparing the full lifecycle cost of replacing the equipment with the cumulative cost of maintaining the failed equipment. If the latter exceeds 70% of the former, replacement is recommended. Conduct reliability assessments for irreversible damage or high-cost failures, counting the number of failures and downtime duration of the faulty equipment over the past two years. If the average number of failures per year is ≥3 or the cumulative downtime is >72 hours, replacement is recommended. Conduct a risk level assessment for irreversible damage or high-cost failures. If the faulty device is redundant and the failure does not affect business continuity, replacement can be postponed. If the device is primary and has no redundancy, replacement is recommended as a priority.

[0013] Furthermore, feature information of historical data is extracted and labels are defined according to the operating status of the refrigeration units in the computer room. Specifically, Extract historical data from the database, clean and standardize the historical data, and convert the historical data into a format for analysis; Extract characteristic information related to the operating status of the refrigeration unit in the computer room from historical data, including but not limited to: current, energy consumption, cooling capacity, pressure, temperature, energy efficiency COP, operating time, and maintenance records; Different labels are defined based on the different operating states of the refrigeration units in the computer room. The labels are classified into two categories: normal operation and abnormal operation. According to the different fault factors of the refrigeration units in the computer room, the abnormal operation labels are further subdivided, including: Class A faults caused by abnormal current and Class B faults caused by abnormal temperature.

[0014] Furthermore, the method also includes the steps of calculating the water pump efficiency by measuring the flow rate, head and input power of the water pump, and determining whether the water pump needs to be replaced based on this, specifically: The water pump flow rate was measured by a handheld ultrasonic flow meter; Convert the pressure difference between the inlet and outlet of the water pump into the lift value; Use a power meter or calculate the input power based on the motor nameplate parameters and the voltage and current during operation, and then calculate the real-time efficiency of the water pump; If the real-time efficiency is lower than the preset threshold, it is determined that the water pump needs to be replaced.

[0015] Furthermore, the method also includes the step of testing the performance of the cooling tower, specifically: Calculate the cooling tower's approach, cooling efficiency, and water drift rate; The approximation is calculated by the difference between the cooling tower outlet water temperature and the ambient wet bulb temperature, reflecting the heat dissipation efficiency; Cooling efficiency is calculated based on the inlet water temperature, outlet water temperature and air wet bulb temperature, and measures the cooling tower's ability to reduce water temperature; The water drift rate is calculated as the ratio of the amount of water drift per unit time to the cooling water flow rate into the tower. If the water drift rate exceeds the preset standard, it is determined that there is a water drift problem in the cooling tower and maintenance or replacement is required.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, by comparing the communication distance parameter with the preset threshold, it is ensured that the connection between the computer room refrigeration unit and the cloud platform is within the optimal network distance range, further ensuring the integrity of data transmission and avoiding data packet loss or interruption due to signal attenuation. The rationality of the data volume and type is verified by the second reference coefficient to reduce data errors and anomalies. This ensures the accuracy of data reception, lays a solid data foundation for the subsequent formulation of thresholds based on factory data and historical data, improves the authenticity of the threshold setting, and further ensures the accuracy of the diagnosis of the computer room refrigeration unit.

[0017] 2. In the present invention, abnormal signals are quickly identified by comparing real-time data with preset thresholds. After the abnormal signals are identified, a comprehensive analysis of real-time data and multi-dimensional parameters is performed based on a decision tree, forming a closed-loop mechanism through threshold dynamic monitoring-multi-parameter decision analysis-intelligent diagnosis, realizing digital inspection, avoiding erroneous conclusions caused by deviations from a single data point, and ensuring the robustness of the performance judgment of the equipment in the computer room. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1This is a flow chart of the computer room equipment diagnosis method based on sensing and digital collaboration of the present invention; Figure 2 Schematic diagram of hourly flow rate of the chilled water pump of the present invention throughout the year; Figure 3 This is a schematic diagram of the hourly resistance of the pipe network of the present invention; Figure 4 Schematic diagram of the flow-efficiency relationship curve of the chilled water pump of the present invention; Figure 5 This is a schematic diagram of the cumulative changes in energy consumption of the variable frequency water pump of the present invention throughout the year; Figure 6 This is a schematic diagram of the annual cooling capacity of a building according to the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] In order to solve the technical problems in existing technologies, the update of mechanical and electrical equipment is often due to the lack of scientific detection methods, the phenomenon of over-the-top renovation, and the mode of overall renovation and demolition, which makes it not meet the needs of building use, please refer to Figure 1 , this embodiment provides the following technical solutions: A computer room equipment diagnosis method based on sensing and digital collaboration includes the following steps: Various sensors are deployed on water pumps, chillers, and cooling towers, such as digital pressure sensors, temperature sensors, smart meters and other wireless test instruments, noise sensors, and vibration sensors. These sensors are used to collect real-time operating parameters of the refrigeration units in the computer room, such as current, energy consumption, cooling capacity, pressure, temperature, and other data. These sensors also monitor whether the vibration and noise of the equipment meet the requirements of the computer room. A deviation of more than 20% from the factory parameter table is used as an auxiliary judgment condition for replacement. During specific implementation, the actual performance of the refrigeration units, water pump groups, and cooling towers under various operating conditions is tested every 7 to 14 days, and compared with the equipment parameter table at the time of on-site installation to make a judgment on energy consumption attenuation.

[0021] Build a database to store factory data, real-time data, and historical data of the refrigeration units in the computer room; Thresholds are established based on factory data and historical data. Real-time data is regularly compared with the thresholds to determine the energy consumption status of the refrigeration units in the computer room. Specifically: Regularly obtain the latest factory data and historical data of the computer room refrigeration units stored in the database for the past six months; Based on factory data and industry standards, extract equipment operating data from historical data tables, calculate the average COP (Cooling Performance Requirement) ratio of cooling capacity to power consumption for historical data, and analyze the fluctuation range of the historical COP ratio. The COP calculation formula is as follows: Based on the service life and maintenance records of the refrigeration units in the computer room, regularly optimize the reasonable threshold range and dynamically adjust the threshold according to actual conditions; Regularly extract data from real-time data, calculate the actual energy efficiency (COP) cooling capacity to power consumption ratio, and compare the actual ratio with the threshold; If the actual ratio is lower than the threshold, it indicates that the energy consumption of the room's refrigeration unit is abnormal, and a verification alarm is triggered. For example, for a refrigeration unit, the difference between the actual COP (cooling capacity to power consumption) and the factory standard COP can be calculated. If the actual COP is significantly lower than the factory standard COP, it indicates that there may be a problem with the energy loss mechanism of the refrigerator, such as refrigerant leakage or heat exchanger scaling. In one embodiment, equipment power-on and power-off status and electricity bills from the past three years are collected to assess equipment energy efficiency. For example, a computer room contains four centrifugal variable-frequency chillers with one standby. The July electricity bill for the unit group is 5 million yuan, and the control platform indicates that the standby unit was not turned on. The three units were essentially in common use. The total operating time of the three units in different frequency bands during that month is extracted, and combined with the power consumption per unit time for each frequency band, the theoretical total power consumption for each unit is calculated. For example, the total operating cost for the 50Hz frequency band is 1.5 million yuan, the total operating cost for the 75Hz frequency band is 1.5 million yuan, and the total operating cost for the 100Hz frequency band is 1.9 million yuan. The theoretical cost is 4.9 million yuan, but the actual cost is 5 million yuan, within a 5% error, making the judgment reasonable. At the same time, according to the time periods and cooling capacity supply of each frequency displayed on the unit, the cooling capacity provided by each frequency segment of the unit can be obtained. The cooling capacity of a single frequency / the power consumption of this frequency = the cooling efficiency (COP) of this frequency. Then, the COP values ​​of each frequency are combined, and the comprehensive actual COP1 value is obtained according to the weighted usage time of each frequency. By comparing it with the comprehensive COP2 value of the equipment at the factory, the attenuation efficiency of the unit can be judged.

[0022] like Figure 6 As shown, for old computer rooms without storage platforms and individual energy meters for refrigeration units, water pumps and cooling towers, but with a total meter to measure the comprehensive energy consumption of the refrigeration room, the total cooling capacity actually required each month can be estimated through system simulation by fitting the building's temperature, area, occupant density, thermal inertia performance of the building envelope and the use of heat dissipation equipment.

[0023] In one embodiment, some very old computer rooms may not even have a data storage platform for querying, or even individual energy meters for the chillers, water pumps, and cooling towers. Instead, there's only a master meter measuring the overall energy consumption of the chiller room. In this case, the actual total cooling capacity required each month can be estimated. For example, the required cooling capacity for that month can be fitted based on the building temperature, building area, occupancy density, thermal inertia of the building envelope, and cooling equipment usage provided by the unit. By comparing the total electricity consumption bills for the equipment (using a rule of thumb of 60%-65% for chillers, 20%-25% for pumps, and 10%-20% for cooling towers), the approximate total cost and total cooling capacity of the chillers can be estimated, resulting in the total COP1 value of the chiller group, which can be compared with the comprehensive COP2 value of the equipment at the time of shipment. If the COP1 is less than 3.0, it indicates that the unit needs to be replaced. If the COP1 is between 3.0 and 3.5, it indicates that it can be replaced. Otherwise, it can be retained.

[0024] The determination of the energy consumption status includes but is not limited to the following steps: Calculate the hourly flow rate of the chilled water pump based on the chilled water supply and return water temperature difference and the total cooling load of the system; According to the pipeline characteristic relationship of the chilled water system, calculate the relationship between the flow rate in the pipeline and the pressure head of the pipeline system; Calculate the required head, shaft power and energy consumption of the water pump in the distribution system based on the relationship between the shaft power, flow rate and head of the variable frequency pump; Calculate the hourly flow rate required by the chilled water pump pipeline based on the hourly cooling load throughout the year, and calculate the hourly resistance throughout the year based on the equipment parameters and characteristic curve; According to the flow-efficiency relationship curve of the water pump, the hourly efficiency of the water pump is obtained, and the cumulative energy consumption of the chilled water pump for the whole year is calculated.

[0025] In one embodiment, assuming that the supply and return temperature difference of chilled water is always maintained at 6°C (10 / 16°C), the hourly flow rate of the chilled water pump can be calculated according to the following formula: Where, is the total cooling load of the system; is the specific heat capacity of water, in J / kg·℃; is the mass flow rate, in kg / s; is the supply and return water temperature difference, in °C; The pipeline characteristic curve is the relationship curve between the flow rate in the pipeline and the pressure head (i.e., pressure head) of the pipeline system. The pipeline characteristic relationship of the chilled water system is shown as follows: Where, is the head of the chilled water pump in the pipeline, in meters; is the pipeline impedance, in s 2 / m 5 ; is the volume flow rate of the pipe network, in m 3 / s; The relationship between the shaft power, flow rate and head of the variable frequency pump is: Where, is the shaft power of the water pump, in kW; is the fluid density, in units of 9.8 kN / m 3 ; is the water pump efficiency, unit is %; is the lift, in m; is the volume flow rate in m 3 / h, is the density of water in kg / m 3 .

[0026] According to the above formula, the required head, shaft power and energy consumption of the water pump of the distribution system can be calculated; The chilled water pump piping system in a hotel area of ​​a certain project is taken as the research object. According to the hourly cooling load throughout the year, the hourly flow required by the chilled water pump piping is calculated. The hourly flow is as follows: Figure 2 As shown above; Based on the equipment parameters and characteristic curve of the hotel area chilled water pump selected above, combined with the hourly flow rate of the hotel area chilled water pump calculated above, the hourly resistance of the hotel area chilled water pump (hourly head of the chilled water pump) can be calculated according to the pipeline characteristic relationship of the chilled water system. The pipe network resistance is shown as follows Figure 3 As shown; Using the annual hourly flow and hourly resistance (head) calculated above, and according to the flow-efficiency relationship curve of the pump (such as Figure 4 As shown), calculate the hourly efficiency of the water pump , calculate the hourly shaft power of the variable frequency chilled water pump in the hotel area , and finally according to the hourly shaft power The cumulative energy consumption of the chilled water pump for the whole year can be calculated. The calculation result is as follows: Figure 5 As shown, the annual operating energy consumption is 9320.66 kWh.

[0027] Secondly, it also includes: transmitting historical data of the refrigeration units in the computer room to the cloud platform through wireless communication technologies such as Wi-Fi, Bluetooth, and NB-IoT; Obtain the communication distance parameter between the computer room and the cloud platform as the first reference coefficient; pre-set a communication distance threshold, compare the communication distance parameter with the communication distance threshold, and determine whether the communication distance parameter is within the network distance threshold range; if so, it indicates that the first reference coefficient is accurate; if the first reference coefficient is not within the network distance threshold range, consider using a wired transmission communication mode; The amount and type of historical data uploaded by the refrigeration unit in the computer room are obtained as the second reference coefficient; upper and lower floating thresholds are pre-set, and the amount and type of historical data uploaded are compared with the upper and lower floating thresholds to determine whether the amount and type of historical data uploaded are within the upper and lower floating thresholds; if so, it indicates that the second reference coefficient is accurate; The verification results of the first reference coefficient and the second reference coefficient are combined to verify whether the uploaded results of the historical data of the refrigeration unit in the computer room are accurate, thereby ensuring the stability and reliability of the data transmission of the refrigeration unit in the computer room and avoiding data loss or delay.

[0028] The beneficial effects achieved by the above content are: by comparing the communication distance parameters with the preset threshold, the connection between the computer room refrigeration unit and the cloud platform is ensured to be within the optimal network distance range, further ensuring the integrity of data transmission and avoiding data packet loss or interruption due to signal attenuation; the rationality of the data volume and type is verified through the second reference coefficient, reducing data errors and anomalies; thereby ensuring the accuracy of data reception, laying a solid data foundation for the subsequent formulation of thresholds based on factory data and historical data, improving the authenticity of the threshold setting, and further ensuring the accuracy of the diagnosis of the computer room refrigeration unit.

[0029] Decision tree technology was introduced to extract feature information from historical data. Labels were defined based on the operating status of the refrigeration units in the computer room. The decision tree model was used to train the historical data and learn the relationships between different features. Specifically: Extract historical data from the database, clean and standardize the historical data, and convert the historical data into a format for analysis; Extract characteristic information related to the operating status of equipment in the computer room from historical data, including but not limited to: current, energy consumption, cooling capacity, pressure, temperature, energy efficiency COP, operating hours, and maintenance records; Different labels are defined based on the different operating states of the refrigeration units in the computer room. The labels are classified into two categories: normal operation and abnormal operation. For example, a condition where the COP is above the threshold and other parameters are within the normal range is defined as normal operation; a condition where the COP is below the threshold or some key parameters are outside the normal range is defined as abnormal operation. Based on the different failure factors of the computer room's refrigeration units, abnormal operation labels are further subdivided into: Class A faults for abnormal current and Class B faults for abnormal temperature. For example, a Class A fault is defined when the energy efficiency COP is below the threshold and the current is abnormally high; a Class B fault is defined when the energy efficiency COP is below the threshold and the temperature is abnormally high. This ensures the rationality of the characteristic information and the accuracy of the labels.

[0030] When the comparison results are abnormal, the decision tree is used to extract the feature information of the real-time data, and the comparison results and feature information are comprehensively analyzed. The analysis results are output and the operating status of the refrigeration unit in the computer room is accurately determined. Specifically: After a verification alarm is triggered, the comparison results and real-time data are used as the main analysis factors. The age of the refrigeration units in the computer room, maintenance records, and seasonal climate are used as multiple parameters and simultaneously input into the decision tree for training. Analyze the relationship between different features and labels in the main analysis factors through decision tree analysis, and conduct comprehensive analysis on multiple parameters; Based on the decision-making rules, the operating status of the refrigeration unit in the computer room is further determined to avoid misjudgment caused by relying on a single comparison result. For example, if the current is >10A, the energy consumption is >50kW, and the cooling capacity is <100kW, it is judged to be an internal problem in the refrigeration system; if the current is >15A, the energy consumption is >60kW, and the cooling capacity is <120kW, it is judged to be a motor failure. Another example: if the current is normal but the cooling capacity decreases, it may be scaling of the heat exchanger; if the current increases but the cooling capacity does not increase, it may be a motor failure. Based on the judgment results, determine whether the refrigeration unit in the computer room needs to be replaced; specifically: Obtain the judgment results of historical data and preliminarily classify the judgment results of historical data, including: repairable failures and irreversible damage or high-cost failures; For repairable faults, it is recommended to prioritize maintenance measures and monitor whether the parameters return to normal range after repair; For irreversible damage or high-cost failures, we recommend maintenance or replacement of equipment based on the cause of the failure. Specifically: For irreversible damage or high-cost failures, an economic analysis is conducted, comparing the full lifecycle cost of replacing the new equipment (including purchase, installation, and energy consumption) with the cumulative cost of maintaining the failed equipment. If the latter exceeds 70% of the former, replacement is recommended. Furthermore, if the energy efficiency ratio of the new equipment, such as the COP value, is at least 20% higher than that of the failed equipment, replacement can bring long-term energy savings. Conduct reliability assessments for irreversible damage or high-cost failures, counting the number of failures and downtime duration of the faulty equipment over the past two years. If the average annual failure rate is ≥3 or the cumulative downtime is >72 hours, replacement is recommended. For example, if the remaining life of core components such as compressors and motors is less than 1 year, early replacement is recommended to avoid sudden downtime. The specific basis for implementation is: 1. If the annual repair or maintenance cost of the refrigeration unit is greater than the purchase price of the unit * 0.1, the number of repairs is ≥ 2 times / year, and the number of fault errors is ≥ 6 times / year, the unit is considered to be eligible for replacement.

[0031] 2. If the annual repair or maintenance cost of the water pump unit is greater than the purchase price of the equipment * 0.2, the number of repairs is ≥ 2 times / year, and the number of fault reports is ≥ 4 times / year, the unit is considered to be eligible for replacement.

[0032] 3. If the annual repair or maintenance cost of the cooling tower is greater than the purchase price of the equipment * 0.1, the number of repairs is ≥ 2 times / year, and the number of fault reports is ≥ 6 times / year, the unit is considered to be eligible for replacement.

[0033] Conduct a risk level assessment for irreversible damage or high-cost failures. If the faulty equipment is redundant and the failure does not affect business continuity, replacement can be postponed. If it is a main equipment without redundancy, it is recommended to replace it first. Specifically, observe whether the pressure gauge and temperature gauge of the refrigeration unit meet the data under each design condition; whether the pressure and total flow of each frequency of the water pump group meet the data under the design condition; the approximate value of the cooling tower, that is, whether the real-time difference between the return water temperature of the cooling tower and the environment is within 5°C. If the deviation is more than 20%, it can be determined that the conditions for replacement are met. The calculation formula for the cooling tower approximation is: Approximation = outlet water temperature - wet bulb temperature Approximation is an important indicator for evaluating the performance of cooling towers. It refers to the temperature difference between the cooling water outlet temperature and the wet bulb temperature, usually expressed as ΔT. The smaller the ΔT, the greater the heat load handled by the cooling tower and the better the cooling effect.

[0034] Table 1. Computer room equipment fault diagnosis table Trend characteristics Association parameters Decision tree results Suggestions Energy efficiency COP slow decline Ambient temperature rise Refrigerant leak Emergency maintenance and refrigerant replenishment Energy efficiency COP drops sharply Increased equipment age Compressor wear Replace the compressor In one embodiment, it is also possible to determine whether the refrigeration unit in the machine room needs to be replaced by using an integral method; for example: If the ratio of the comprehensive efficiency COP1 value of a single refrigeration unit to the comprehensive efficiency COP2 value at the time of leaving the factory is less than 0.6 (excluding 0.6), 0.3 points will be deducted; If the ratio of the comprehensive efficiency COP1 value of a single refrigeration unit to the comprehensive efficiency COP2 value at the factory is found to be between 0.6 and 0.8 (0.1 points will be deducted); otherwise, no points will be deducted; If the ratio of the actual efficiency of the unit comprehensive power consumption of a single pump group to the factory comprehensive efficiency is less than 0.7 (excluding 0.7), 0.3 points will be deducted; If the ratio of the actual efficiency of the unit comprehensive power consumption of a single pump group to the factory comprehensive efficiency is found to be between 0.7 and 0.85 (excluding 0.85), 0.1 points will be deducted; otherwise, no points will be deducted; If the ratio of the comprehensive efficiency COP1 of a single refrigeration unit to the comprehensive efficiency COP2 at the time of leaving the factory is less than 0.6 (excluding 0.6), 0.5 points will be deducted; If the ratio of the comprehensive efficiency COP1 value of a single refrigeration unit to the comprehensive efficiency COP2 value at the factory is found to be between 0.6 and 0.8 (excluding 0.4), 0.3 points will be deducted; otherwise, no points will be deducted; If the ratio of the actual efficiency of the unit comprehensive power consumption of a single pump group to the factory comprehensive efficiency is less than 0.7 (excluding 0.7), 0.5 points will be deducted; If it is found that the ratio of the actual efficiency of the unit comprehensive power consumption of a single water pump group to the factory comprehensive efficiency is between 0.7 and 0.85 (excluding 0.85), 0.3 points will be deducted; otherwise, no points will be deducted.

[0035] Based on the above specific judgment criteria, if the refrigeration unit and water pump unit meet any of the above conditions, 0.1 points will be deducted.

[0036] If the comprehensive judgment score is higher than 0.7 points (excluding 0.7 points), you can consider retaining the equipment; if it is between 0.5 and 0.7 points (excluding 0.5 points), you can consider replacing the equipment; if the comprehensive score is below 0.5 points (including 0.5 points), the equipment must be replaced.

[0037] Based on the comparison results of the actual energy efficiency COP cooling capacity and power consumption ratio with the threshold value, combined with the analysis results of the decision tree, a line graph of the energy efficiency COP cooling capacity and power consumption ratio and different parameters is drawn; Analyze the changing trend of the ratio of energy efficiency (COP) cooling capacity to power consumption in the line chart. If the ratio shows a clear downward trend and the decline exceeds the set threshold, it indicates that the cooling efficiency of the computer room refrigeration unit is on a downward trend.

[0038] The beneficial effects achieved by the above content: This diagnostic method not only focuses on a single parameter, but also comprehensively considers the relationship between multiple parameters; for example: combining the refrigerator's current, energy consumption, cooling capacity, pressure, temperature and other data to analyze the mutual influence between them; if it is found that the current is normal but the energy consumption increases and the cooling capacity decreases, there may be a problem inside the refrigeration system; if the current increases, the energy consumption increases but the cooling capacity does not increase accordingly, there may be a fault in the motor and other components.

[0039] The computer room equipment diagnostic method also includes calculating the pump efficiency by measuring the pump flow rate, head, and input power, and using this to determine whether the pump needs to be replaced. Specifically, the following steps are performed: The water pump flow rate was measured by a handheld ultrasonic flow meter; Convert the pressure difference between the inlet and outlet of the water pump into the lift value; Use a power meter or calculate the input power based on the motor nameplate parameters and the voltage and current during operation, and then calculate the real-time efficiency of the water pump; If the real-time efficiency is lower than the preset threshold, it is determined that the water pump needs to be replaced.

[0040] Among them, the water pump efficiency test can usually be carried out through the following steps: Determine the measurement parameters: flow rate, head, input power and other parameters of the pump; Pump flow testing: A handheld ultrasonic flowmeter can be used to measure flow by detecting and calculating the difference in ultrasonic pulse velocity in the forward and reverse directions of the fluid. The velocity of sound waves propagating in the fluid is determined based on the fluid medium, pipe material, pipe diameter, and wall thickness. By measuring the time difference in sound wave transmission, the flow velocity, and thus the flow rate, can be calculated. The time difference in sound wave transmission is proportional to the fluid velocity, as shown in the following equation: Where, is the flow velocity (m / s); is the speed of ultrasound in non-flowing media; is the measured time difference between upstream and downstream propagation (s); is the distance between the two receivers (Z-type connection) (m); is the pipe diameter (m); Water pump head test: by measuring or reading the pressure difference between the inlet and outlet of the water pump and converting it into the head value; Input power: A power meter can be used to measure the input electrical power of the pump motor; The input power of the chilled water pump can be directly measured using a power measuring instrument. Common measurement methods include connecting a power sensor, power analyzer, or other device to the pump's motor circuit to obtain the input power value in real time. If you don’t have professional measuring equipment, you can also calculate based on the motor’s nameplate parameters and the voltage, current and other parameters during operation; The input power of the motor ( ) can be obtained by the formula: = √3 × U × I × cosφ Real-time theoretical power, also known as water power: = in, is the water pump power (kW); is the acceleration due to gravity (9.81m / s 2 ); is the flow rate (m3 / s); is the lift (m); Finally, the real-time efficiency of the chilled water pump is: η= Calculate pump efficiency: Pump efficiency 00%.

[0041] The equipment room diagnostic method also includes the steps of cooling tower performance testing, specifically: Calculate the cooling tower's approach, cooling efficiency, and water drift rate; The approximation is calculated by the difference between the cooling tower outlet water temperature and the ambient wet bulb temperature, reflecting the heat dissipation efficiency; The approximation calculation of the cooling tower is based on the difference between the cooling tower outlet water temperature and the ambient wet bulb temperature. This difference reflects the cooling tower's heat dissipation efficiency. The approximation calculation formula is: Approximation = outlet water temperature - wet bulb temperature Approximation is an important indicator for evaluating the performance of cooling towers. It refers to the temperature difference between the cooling water outlet temperature and the wet bulb temperature. It is usually expressed as ΔT. The smaller the ΔT, the greater the heat load handled by the cooling tower and the better the cooling effect. Cooling efficiency is calculated based on the inlet water temperature, outlet water temperature and air wet bulb temperature, and measures the cooling tower's ability to reduce water temperature; The cooling efficiency of a cooling tower is usually calculated using the following formula: Cooling efficiency Eff(%) = (T1 - T2) / (T1 - Twb) × 100% Where: T1 is the water inlet temperature, that is, the temperature of the cooling water when it enters the cooling tower; T2 is the water outlet temperature, that is, the temperature of the cooling water when it leaves the cooling tower; Twb is the air wet bulb temperature, that is, the temperature measured on the wet bulb thermometer in the environment, which takes into account the effect of humidity in the air on the temperature; This formula measures the cooling tower's ability to reduce water temperature. The closer the efficiency value is to 100%, the stronger the cooling capacity of the cooling tower is, and it can reduce the water temperature to a level closer to the wet-bulb temperature of the air. The cooling capacity should be no less than 95.0%; The water drift rate is calculated as the ratio of the amount of water drift per unit time to the cooling water flow rate into the tower. If the water drift rate exceeds the preset standard, it is determined that there is a water drift problem in the cooling tower and maintenance or replacement is required. The water drift rate refers to the ratio of the water drift volume (mass flow rate, unit kg / h) per unit time to the cooling water flow rate (mass flow rate, unit kg / h) into the tower; The water drift rate of open cooling towers should not exceed 0.010%.

[0042] It should be noted that cooling towers are generally judged by their proximity and water drift rate (that is, the difference between the treated water temperature and the outdoor temperature, as well as the weight of water loss). In addition, if there is excessive dirt and blockage, or the fan heat dissipation does not meet the requirements, partial repairs or overall replacement should be considered.

[0043] In one embodiment, a computer room is equipped with four chilled water pumps and one standby chiller installed in conjunction with a refrigeration unit. It is detected that the itemized electricity bill for the chilled water pump group in July is 300,000 yuan. Data from the control platform shows that the corresponding standby chiller was not turned on that month, and the remaining chillers were basically in a shared state of three (because the chillers provided sufficient cooling capacity, one chiller was not turned on). The chilled water pumps are turned on or off according to the working status of the corresponding refrigeration unit. The total operating time of the three chilled water pumps that month, recorded by the master control platform, can be used to calculate the actual total power consumption P of each pump that month.

[0044] The actual power of the water pump can be calculated by the flow rate of the water pump in each period (usually hour by hour) stored on the platform (or manually recorded) and the pressure difference before and after the water pump according to P1=QρgH / 1000, (P1 is the actual power of the water pump, kW; Q is the volume flow rate of the water pump, m 3 / h; ρ is the liquid density, kg / m 3 ; g is the acceleration due to gravity, 9.81m / s 2 ; H is the pump head, m, which can be converted from the pressure difference before and after the pump); The COP value of a single pump = the actual power P1 of the single pump / (the power consumption of the single pump at the corresponding time P electric x the pump motor efficiency η electric). The actual pump energy efficiency ratio COP1 value can be obtained by weighted calculation of the pump efficiency in each time period. The energy efficiency ratio COP2 value of the pump at the time of leaving the factory can be calculated based on the pump nameplate and the corresponding equipment performance curve. The attenuation efficiency of the pump can be determined by comparing the two data.

[0045] When the COP value of the water pump drops by 30% compared with the factory parameters, the water pump is considered to be seriously aged and replacement of the water pump will be given priority.

[0046] Working principle: By comparing real-time data with preset thresholds, abnormal signals can be quickly identified. After identifying abnormal signals, a comprehensive analysis of real-time data and multi-dimensional parameters is performed based on a decision tree, forming a closed-loop mechanism through threshold dynamic monitoring - multi-parameter decision analysis - intelligent diagnosis, realizing digital inspection, avoiding erroneous conclusions caused by deviations from a single data point, and ensuring the robustness of equipment performance judgments in the computer room.

[0047] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "including," "having," or any other variations thereof are intended to cover non-exclusive possessors, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or includes elements that are inherent to such process, method, article, or apparatus.

[0048] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions, and alterations may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A computer room equipment diagnosis method based on sensing and digital collaboration, characterized in that: The method comprises the following steps: Deploy various sensors on water pumps, chillers, and cooling towers to collect real-time operating parameters of the refrigeration units in the computer room; Build a database to store factory data, real-time data, and historical data of the refrigeration units in the computer room; Set thresholds based on factory data and historical data, and regularly compare real-time data with the thresholds to determine the energy consumption status of the computer room's refrigeration units; Decision tree technology was introduced to extract feature information from historical data. Labels were defined based on the operating status of the refrigeration units in the computer room. The decision tree model was used to train the historical data and learn the relationships between different features. When there are abnormalities in the comparison results, the feature information of the real-time data is extracted through the decision tree, the comparison results and feature information are comprehensively analyzed, and the analysis results are output to accurately determine the operating status of the refrigeration unit in the computer room.

2. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 1 is characterized by: Thresholds are established based on factory data and historical data. Real-time data is regularly compared with the thresholds to determine the energy consumption status of the refrigeration units in the computer room. Specifically: Regularly obtain the latest factory data and historical data of the computer room refrigeration units stored in the database for the past six months; Based on factory data and industry standards, extract the equipment's operating data or operating data of each frequency from the historical data table, calculate the average energy efficiency (COP) cooling capacity to power consumption ratio of the historical data, and analyze the fluctuation range of the historical energy efficiency (COP) cooling capacity to power consumption ratio; Based on the service life and maintenance records of the refrigeration units in the computer room, regularly optimize the reasonable threshold range and dynamically adjust the threshold according to actual conditions; Regularly extract data from the electricity bill and actual cooling capacity of the refrigeration unit, calculate the actual energy efficiency (COP) cooling capacity to power consumption ratio, and compare the actual ratio with the threshold; If the actual ratio is lower than the threshold, it indicates that the energy consumption of the refrigeration unit in the computer room is abnormal and triggers a verification alarm; For older equipment rooms without storage platforms and individual energy meters for chillers, pumps, and cooling towers, but with a master meter to measure the overall energy consumption of the chiller room, estimate the total cooling capacity actually required each month by fitting the building's temperature, area, occupancy density, thermal inertia of the building envelope, and the use of heat dissipation equipment; The determination of the energy consumption status of the water pump includes but is not limited to the following steps: Calculate the hourly flow rate of the chilled water pump based on the chilled water supply and return water temperature difference and the total cooling load of the system; According to the pipeline characteristic relationship of the chilled water system, calculate the relationship between the flow rate in the pipeline and the pressure head of the pipeline system; Calculate the required head, shaft power and energy consumption of the water pump in the distribution system based on the relationship between the shaft power, flow rate and head of the variable frequency pump; Calculate the hourly flow rate required by the chilled water pump pipeline based on the hourly cooling load throughout the year, and calculate the hourly resistance throughout the year based on the equipment parameters and characteristic curve; According to the flow-efficiency relationship curve of the water pump, the hourly efficiency of the water pump is obtained, and the cumulative energy consumption of the chilled water pump for the whole year is calculated.

3. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 2 is characterized by: Developing thresholds based on factory data and historical data also includes the following steps: The historical data of the refrigeration unit in the computer room is transmitted to the cloud platform through wireless communication technology; Obtain the communication distance parameter between the computer room and the cloud platform as the first reference coefficient; A communication distance threshold is pre-set, and a communication distance parameter is compared with the communication distance threshold to determine whether the communication distance parameter is within the network distance threshold range; if so, it indicates that the first reference coefficient is accurate; if the first reference coefficient is not within the network distance threshold range, a wired transmission communication mode is considered; Obtain the amount and type of historical data uploaded by the refrigeration unit in the computer room as the second reference coefficient; Preset upper and lower floating thresholds, compare the data volume and data type of historical data uploaded with the upper and lower floating thresholds, and determine whether the data volume and data type of historical data uploaded are within the upper and lower floating thresholds; if so, it indicates that the second reference coefficient is accurate; The verification results of the first reference coefficient and the second reference coefficient are combined to verify whether the uploaded results of the historical data of the refrigeration unit in the computer room are accurate.

4. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 2 is characterized by: The comparison results and feature information are comprehensively analyzed and output to accurately determine the operating status of the refrigeration unit in the computer room, specifically: After a verification alarm is triggered, the comparison results and real-time data are used as the main analysis factors. The age of the refrigeration units in the computer room, maintenance records, and seasonal climate are used as multiple parameters and simultaneously input into the decision tree for training. Analyze the relationship between different features and labels in the main analysis factors through decision tree analysis, and conduct comprehensive analysis on multiple parameters; Based on the decision rules, the operating status of the refrigeration unit in the computer room can be further judged to avoid misjudgment caused by relying on a single comparison result; Based on the judgment results, determine whether the computer room refrigeration unit needs to be replaced.

5. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 4 is characterized in that: Comprehensively analyzing the comparison results and feature information and outputting the analysis results also includes the following steps: Based on the comparison results of the actual energy efficiency COP cooling capacity to power consumption ratio and the threshold value, combined with the analysis results of the decision tree, a line graph of the energy efficiency COP cooling capacity to power consumption ratio and different parameters is drawn; Analyze the changing trend of the ratio of energy efficiency (COP) cooling capacity to power consumption in the line chart. If the ratio shows a clear downward trend and the decline exceeds the set threshold, it indicates that the cooling efficiency of the computer room refrigeration unit is on a downward trend.

6. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 4 is characterized in that: Based on the judgment results, determine whether the equipment room cooling unit needs to be replaced. Specifically: Obtain the judgment results of historical data and preliminarily classify the judgment results of historical data, including: repairable failures and irreversible damage or high-cost failures; For repairable faults, it is recommended to prioritize maintenance measures and monitor whether the parameters return to normal range after repair; For irreversible damage or high-cost failures, maintenance or replacement of equipment is recommended based on the failure factors.

7. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 6 is characterized by: For irreversible damage or high-cost failures, we recommend maintenance or replacement of equipment based on the cause of the failure. Specifically: Conduct an economic analysis for irreversible damage or high-cost failures, comparing the full lifecycle cost of replacing the equipment with the cumulative cost of maintaining the failed equipment. If the latter exceeds 70% of the former, replacement is recommended. Conduct reliability assessments for irreversible damage or high-cost failures, counting the number of failures and downtime duration of the faulty equipment over the past two years. If the average number of failures per year is ≥3 or the cumulative downtime is >72 hours, replacement is recommended. Conduct a risk level assessment for irreversible damage or high-cost failures. If the faulty device is redundant and the failure does not affect business continuity, replacement can be postponed. If the device is primary and has no redundancy, replacement is recommended as a priority.

8. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 1 is characterized by: Extract the characteristic information of historical data and define labels based on the operating status of the cooling units in the computer room. Specifically: Extract historical data from the database, clean and standardize the historical data, and convert the historical data into a format for analysis; Extract characteristic information related to the operating status of the refrigeration unit in the computer room from historical data, including but not limited to: current, energy consumption, cooling capacity, pressure, temperature, energy efficiency COP, operating time, and maintenance records; Different labels are defined based on the different operating states of the refrigeration units in the computer room. The labels are classified into two categories: normal operation and abnormal operation. According to the different fault factors of the refrigeration units in the computer room, the abnormal operation labels are further subdivided, including: Class A faults caused by abnormal current and Class B faults caused by abnormal temperature.

9. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 1 is characterized by: The method further includes the steps of calculating the water pump efficiency by measuring the flow rate, head and input power of the water pump, and using this to determine whether the water pump needs to be replaced, specifically: The water pump flow rate was measured by a handheld ultrasonic flow meter; Convert the pressure difference between the inlet and outlet of the water pump into the lift value; Use a power meter or calculate the input power based on the motor nameplate parameters and the voltage and current during operation, and then calculate the real-time efficiency of the water pump; If the real-time efficiency is lower than the preset threshold, it is determined that the water pump needs to be replaced.

10. The computer room equipment diagnosis method based on sensing and digital collaboration according to claim 1 is characterized in that: The method further comprises the step of testing the performance of the cooling tower, specifically: Calculate the cooling tower's approach, cooling efficiency, and water drift rate; The approximation is calculated by the difference between the cooling tower outlet water temperature and the ambient wet bulb temperature, reflecting the heat dissipation efficiency; Cooling efficiency is calculated based on the inlet water temperature, outlet water temperature and air wet bulb temperature, and measures the cooling tower's ability to reduce water temperature; The water drift rate is calculated as the ratio of the amount of water drift per unit time to the cooling water flow rate into the tower. If the water drift rate exceeds the preset standard, it is determined that there is a water drift problem in the cooling tower and maintenance or replacement is required.

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