Machine room power equipment fault early warning method and system based on data analysis

Abstract

The invention relates to the technical field of early warning and response, in particular to a machine room power equipment fault early warning method and system based on data analysis. The method is used for detecting and early warning fault points of the circuit board of the uninterruptible power supply under special environmental conditions of dust and vibration interference in a control room of a metallurgical plant; a dust sensor is installed in a control room, a self-adaptive dust concentration early warning model is established, and a dust concentration early warning threshold value is calculated through the self-adaptive dust concentration early warning model; installing a vibration sensor on the uninterruptible power supply in a normal operation state, establishing a vibration strength evaluation model, and calculating a comprehensive vibration index through the vibration strength evaluation model; and establishing a dust-vibration cooperative influence model, calculating a dust-vibration influence factor through the dust-vibration cooperative influence model, judging a fault early warning level according to a numerical value of the dust-vibration influence factor, and generating a maintenance strategy.

Description

Technical Field

[0001] The present invention relates to the technical field of early warning and response, and in particular to a method and system for early warning of power equipment failure in a machine room based on data analysis. Background Art

[0002] An uninterruptible power supply is a device used to provide power guarantee. It can continuously supply power to the load through energy storage methods such as batteries when the main power supply fails. In the control room of a metallurgical plant, the uninterruptible power supply is one of the main power equipment in the computer room. Its stable operation is crucial to the entire control room. Due to the special environmental conditions of the control room of the metallurgical plant, in addition to routine equipment maintenance, it is also necessary to consider the impact of special environmental conditions such as dust and vibration in the metallurgical plant on equipment performance. Dust accumulation will hinder the air flow of the radiator, causing the equipment to overheat and shorten the service life of the uninterruptible power supply; dust may also cause short circuits in components on the circuit board, increasing the risk of equipment failure. Long-term vibration may cause the solder joints of components on the circuit board to loosen, affecting the stability and reliability of the equipment; strong vibration may cause damage to the internal components of the uninterruptible power supply, which in turn causes the uninterruptible power supply to fail. In the control room of the metallurgical plant, the impact of dust and vibration on the uninterruptible power supply is analyzed through sensor technology and data, and the fault warning capability and maintenance efficiency of the uninterruptible power supply are improved to ensure the stable operation of the uninterruptible power supply. Summary of the invention

[0003] (1) Technical issues to be solved

[0004] The purpose of the present invention is to provide a method and system for early warning of power equipment failure in a computer room based on data analysis, which uses dust sensors and vibration sensors to monitor and collect data in real time, and combines historical data such as the operating status of the uninterruptible power supply in the control room to analyze the relationship between the probability of failure of the uninterruptible power supply circuit board and the dust concentration and vibration intensity, so as to obtain an early warning and response plan.

[0005] (2) Technical solution

[0006] To achieve the above-mentioned purpose, on the one hand, the present invention provides a method for early warning of power equipment failure in a computer room based on data analysis, which is used to detect and early warning of failure points of uninterruptible power supply circuit boards under special environmental conditions of dust and vibration interference in the control room of a metallurgical plant; characterized in that the method comprises the following steps:

[0007] S10, installing a dust sensor in the control room, and monitoring the dust concentration in the air in real time through the dust sensor; establishing an adaptive dust concentration warning model, and calculating the dust concentration warning threshold through the adaptive dust concentration warning model; reporting a fault warning signal when it is monitored that the dust concentration in the control room reaches the dust concentration warning threshold, and cleaning the circuit board, cooling system and equipment surroundings of the uninterruptible power supply.

[0008] S20, installing a vibration sensor on an uninterruptible power supply in normal operation, collecting real-time vibration data of the uninterruptible power supply through the vibration sensor; identifying the correlation between vibration intensity and uninterruptible power supply failure based on the vibration data, establishing a vibration intensity assessment model, and calculating a comprehensive vibration index through the vibration intensity assessment model.

[0009] S30, forming a dust-vibration joint monitoring data set through the data collected by the dust sensor and the vibration sensor, establishing a dust-vibration synergistic impact model based on the impact of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board, calculating the dust-vibration impact factor through the dust-vibration synergistic impact model, and judging the fault warning level according to the numerical value of the dust-vibration impact factor, and generating a maintenance strategy.

[0010] Furthermore, the method for calculating the dust concentration warning threshold by using the adaptive dust concentration warning model includes:

[0011] The dust sensor is installed near the uninterruptible power supply in the control room and at the air inlet of the ventilation system to monitor the dust concentration data in the control room in real time. An adaptive dust concentration warning model is established based on the monitored dust concentration data set, and the dust concentration warning threshold D is calculated. t .

[0012] The dust concentration warning threshold D t Calculated by the following formula:

[0013]

[0014] in, is the historical dust concentration average; σ D is the standard deviation of dust concentration; max(D t-n:t-1 ) is the maximum dust concentration value in the previous n time windows; α represents the weight of the historical dust concentration average value, β represents the weight of the historical dust concentration standard deviation, γ represents the weight of the maximum dust concentration value in the previous n time windows, and α+β+γ=1.

[0015] Furthermore, the method for determining the weight coefficients α, β, and γ includes:

[0016] The weight coefficients α, β, and γ are determined by optimizing the objective function as follows:

[0017] Q(α,β,γ)=αE p +βE n +γVar(D t );

[0018] Among them, E pIt indicates the false alarm rate of the model judging normal dust concentration as high concentration; E n Indicates the false alarm rate that the model fails to identify high dust concentration; Var(D t ) represents the warning threshold D t The threshold fluctuation.

[0019] The actual impact of false alarms and missed alarms on uninterruptible power supply fault detection is analyzed through historical data, and the values ​​of α and β are set according to the actual degree of impact; the values ​​of α, β, and γ are adjusted through cross-validation method to achieve the best balance among false alarm rate, missed alarm rate, and threshold fluctuation.

[0020] Furthermore, the method for calculating the comprehensive vibration index by using the vibration intensity assessment model includes:

[0021] A vibration sensor is installed near the uninterruptible power supply in the control room. The real-time vibration data of the uninterruptible power supply is collected by the vibration sensor, and the specific vibration amplitude value and vibration frequency are recorded. A vibration intensity evaluation model is established based on the collected vibration data set, and a comprehensive vibration index is calculated.

[0022] The comprehensive vibration index is calculated by the following formula:

[0023]

[0024] Among them, V i A comprehensive vibration index indicating the overall vibration intensity; j Indicates the vibration amplitude of the jth frequency band; F j represents the vibration frequency of the jth frequency band; A1 represents the standardized vibration amplitude; F1 represents the standardized vibration frequency; m represents the number of frequency bands.

[0025] Collect historical data on uninterruptible power supply failures, analyze the relationship between the uninterruptible power supply failure rate and the vibration intensity assessment model through historical data, and calculate the comprehensive vibration index that will cause an increase in the uninterruptible power supply failure rate.

[0026] Furthermore, the method for establishing a dust-vibration synergistic impact model based on the influence of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board includes:

[0027] The formula for calculating the dust-vibration impact factor through the dust-vibration synergistic impact model is expressed as:

[0028]

[0029] Where R represents the dust-vibration impact factor of the uninterruptible power supply, which is the comprehensive dust concentration and vibration intensity; D c Indicates the current dust concentration; D tIndicates the warning threshold of dust concentration; V1 is the standardized vibration intensity; V i is the comprehensive vibration index; p1 and p2 represent nonlinear indexes.

[0030] The uninterruptible power supply fault warning level is determined according to the value of the dust-vibration impact factor, and a maintenance strategy is generated.

[0031] Furthermore, the method for determining the uninterruptible power supply fault warning level according to the value of the dust-vibration impact factor R includes:

[0032] The fault warning level is divided into three levels; when the dust-vibration impact factor R value is greater than or equal to the first preset threshold, the third level alarm is triggered; when the dust-vibration impact factor R value is less than the first preset threshold and greater than or equal to the second preset threshold, the second level alarm is triggered; when the dust-vibration impact factor R value is less than the second preset threshold and greater than the third preset threshold, the first level alarm is triggered; wherein the first preset threshold is greater than the second preset threshold, and the second preset threshold is greater than the third preset threshold.

[0033] Based on the same inventive concept, on the other hand, the present invention also provides a computer room power equipment fault warning system based on data analysis, the system comprising: a first monitoring and warning module, a second monitoring and warning module, and a comprehensive monitoring and warning module, the modules being connected in sequence;

[0034] The first monitoring and early warning module is used to install a dust sensor in the control room, and monitor the dust concentration in the air in real time through the dust sensor; establish an adaptive dust concentration early warning model, and calculate the dust concentration early warning threshold through the adaptive dust concentration early warning model; when it is monitored that the dust concentration in the control room reaches the dust concentration early warning threshold, a fault early warning signal is reported, and the circuit board, cooling system and equipment surroundings of the uninterruptible power supply are cleaned.

[0035] The second monitoring and early warning module is used to install a vibration sensor on an uninterruptible power supply in normal operating state, collect real-time vibration data of the uninterruptible power supply through the vibration sensor; identify the correlation between vibration intensity and uninterruptible power supply failure based on the vibration data, establish a vibration intensity assessment model, and calculate a comprehensive vibration index through the vibration intensity assessment model.

[0036] The comprehensive monitoring and early warning module is used to form a dust-vibration joint monitoring data set through the data collected by the dust sensor and the vibration sensor, establish a dust-vibration synergistic impact model based on the impact of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board, calculate the dust-vibration impact factor through the dust-vibration synergistic impact model, and judge the fault warning level according to the numerical value of the dust-vibration impact factor to generate a maintenance strategy.

[0037] (3) Beneficial effects

[0038] Compared with the prior art, the beneficial effects of the present invention are: through sensor technology and data analysis methods, the impact of special environmental conditions such as dust and vibration in the control room of a metallurgical plant on the uninterruptible power supply is analyzed, and the fault warning capability and maintenance efficiency of the uninterruptible power supply are improved to ensure the stable operation of the uninterruptible power supply. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flowchart of a method for early warning of power equipment failure in a computer room based on data analysis according to Embodiment 1 of the present invention;

[0040] Figure 2 This is a schematic diagram of the module composition of a computer room power equipment fault warning system based on data analysis according to Example 2 of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0042] Example 1: Figure 1 As shown, this embodiment provides a method for early warning of power equipment failure in a computer room based on data analysis, which is used to detect and early warning of failure points of uninterruptible power supply circuit boards under special environmental conditions of dust and vibration interference in the control room of a metallurgical plant; it is characterized in that the method comprises the following steps:

[0043] S10. Install a dust sensor in the control room, and monitor the dust concentration in the air in real time through the dust sensor; establish an adaptive dust concentration warning model, and calculate the dust concentration warning threshold through the adaptive dust concentration warning model; when it is monitored that the dust concentration in the control room reaches the dust concentration warning threshold, report a fault warning signal, and clean the circuit board, cooling system and equipment surroundings of the uninterruptible power supply.

[0044] S20. Install a vibration sensor on an uninterruptible power supply in normal operation, and collect real-time vibration data of the uninterruptible power supply through the vibration sensor; identify the correlation between vibration intensity and uninterruptible power supply failure based on the vibration data, establish a vibration intensity assessment model, and calculate a comprehensive vibration index through the vibration intensity assessment model.

[0045] S30. The data collected by the dust sensor and the vibration sensor form a dust-vibration joint monitoring data set. Based on the influence of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board, a dust-vibration synergistic influence model is established. The dust-vibration influence factor is calculated through the dust-vibration synergistic influence model, and the fault warning level is judged according to the numerical value of the dust-vibration influence factor to generate a maintenance strategy.

[0046] For example: Based on the fault warning results, formulate targeted maintenance strategies and prioritize high-risk factors; regularly inspect and clean equipment to reduce the impact of dust and vibration on equipment. Collect data after the fault occurs, update and optimize the fault prediction model to improve accuracy; adjust the dust concentration and vibration intensity thresholds based on actual operating experience, and continuously improve the warning plan.

[0047] It should be noted that the method for calculating the dust concentration warning threshold by using the adaptive dust concentration warning model includes:

[0048] S11. Install dust sensors near the uninterruptible power supply in the control room and at the air inlet of the ventilation system to monitor the dust concentration data in the control room in real time; establish an adaptive dust concentration warning model based on the monitored dust concentration data set, and calculate the dust concentration warning threshold D t .

[0049] S12, the dust concentration warning threshold D t Calculated by the following formula:

[0050]

[0051] in, is the historical dust concentration average; σ D is the standard deviation of dust concentration; max(D t-n:t-1 ) is the maximum dust concentration value in the previous n time windows; α represents the weight of the historical dust concentration average value, β represents the weight of the historical dust concentration standard deviation, γ represents the weight of the maximum dust concentration value in the previous n time windows, and α+β+γ=1.

[0052] For example: The dust concentration data of the past 10 time windows are monitored: D1 = 30, D2 = 32, D3 = 28, D4 = 35, D5 = 31, D6 = 29, D7 = 34, D8 = 33, D9 = 30, D 10 =36; calculate the average dust concentration The standard deviation of dust concentration is σ D =2.52, assuming n=5, then the maximum value of the first five time windows is m(D6, D7, D8, D9, D 10)=36, assuming α=0.5,β=0.3,γ=0.2; then the final calculation is D t =23.856, that is, the dust concentration warning threshold is 23.86. If the current dust concentration value monitored in real time exceeds this threshold, the system will issue a fault warning and prompt the uninterruptible power supply equipment to be cleaned.

[0053] It should be noted that the method for determining the weight coefficients α, β, and γ includes:

[0054] S121, the weight coefficients α, β, γ are determined by optimizing the objective function as follows:

[0055] Q(α,β,γ)=αE p +βE n +γVar(D t );

[0056] Among them, E p It indicates the false alarm rate of the model judging normal dust concentration as high concentration; E n Indicates the false alarm rate that the model fails to identify high dust concentration; Var(D t ) represents the warning threshold D t The threshold fluctuation.

[0057] S122. Analyze the actual impact of false alarms and missed alarms on uninterruptible power supply fault detection through historical data, and set the values ​​of α and β according to the actual impact level; adjust the values ​​of α, β, and γ through cross-validation method to achieve the best balance among false alarm rate, missed alarm rate, and threshold fluctuation.

[0058] For example, suppose there are the following historical data: During the monitoring period, there were 100 measurements of normal dust concentration, 10 of which were incorrectly judged as high concentration. Calculate the false alarm rate E p =0.1; During the monitoring period, there were 80 high dust concentration measurements, of which 5 were not identified as high concentrations. The underreporting rate E was calculated. n =0.0625; Assume that the change of the warning threshold in the past period of time is as follows D t =[22,24,23,25,21], the mean of the warning threshold is calculated to be 23, and the variance is 2, so the threshold fluctuation Var(D t)=2; assuming that α=0.5, β=0.3, γ=0.2 are set, the target optimization function Q(α,β,γ)=0.46875 is calculated; by adjusting the values ​​of α, β, and γ, we find the combination that minimizes the objective function Q(α,β,γ). Assuming that the weights are revalued to α=0.4, β=0.4, and γ=0.2, the target optimization function Q(α,β,γ)=0.465 is calculated; therefore, the new weight combination reduces the value of the objective function, indicating that the balance between the false alarm rate, the missed alarm rate, and the threshold volatility has been improved.

[0059] It should be noted that the method for calculating the comprehensive vibration index through the vibration intensity assessment model includes:

[0060] S21. Install a vibration sensor near the uninterruptible power supply in the control room, collect real-time vibration data of the uninterruptible power supply through the vibration sensor, and record the specific vibration amplitude value and vibration frequency; establish a vibration intensity assessment model through the collected vibration data set, and calculate a comprehensive vibration index.

[0061] S22. The comprehensive vibration index is calculated by the following formula:

[0062]

[0063] Among them, V i A comprehensive vibration index indicating the overall vibration intensity; j Indicates the vibration amplitude of the jth frequency band; F j represents the vibration frequency of the jth frequency band; A1 represents the standardized vibration amplitude; F1 represents the standardized vibration frequency; m represents the number of frequency bands.

[0064] S23. Collect historical data on uninterruptible power supply failures, analyze the relationship between the uninterruptible power supply failure rate and the vibration intensity assessment model through the historical data, and calculate the comprehensive vibration index that will cause an increase in the uninterruptible power supply failure rate.

[0065] For example: Assuming that three segments of vibration data are monitored, frequency band 1: vibration amplitude is 0.5, vibration frequency is 10, frequency band 2: vibration amplitude is 1.0, vibration frequency is 20, frequency band 3: vibration amplitude is 1.5, vibration frequency is 30; set the standardized vibration amplitude to 1.0, the standardized vibration frequency to 20; then the final calculated comprehensive vibration index is 21.78.

[0066] It should be noted that the method for establishing a dust-vibration synergistic impact model based on the influence of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board includes:

[0067] S31, the formula for calculating the dust-vibration impact factor through the dust-vibration synergistic impact model is expressed as:

[0068]

[0069] Where R represents the dust-vibration impact factor of the uninterruptible power supply, which is the comprehensive dust concentration and vibration intensity; D c Indicates the current dust concentration; D t Indicates the warning threshold of dust concentration; V1 is the standardized vibration intensity; V i is the comprehensive vibration index; p1 and p2 represent nonlinear indexes.

[0070] S32: Determine the uninterruptible power supply fault warning level according to the value of the dust-vibration impact factor and generate a maintenance strategy.

[0071] For example: Assume that the current dust concentration D c =30, dust concentration warning threshold D t =40, standardized vibration intensity V1 = 1.0, comprehensive vibration index V i =0.5, nonlinear index p1=2, p2=1.5, the data is entered into the calculation formula of dust vibration factor, and R=2.424 is calculated.

[0072] It should be noted that the method for determining the uninterruptible power supply fault warning level according to the value of the dust-vibration impact factor R includes:

[0073] S321. The fault warning level is divided into three levels; when the dust-vibration influence factor R value is greater than or equal to the first preset threshold, the third level alarm is triggered; when the dust-vibration influence factor R value is less than the first preset threshold and greater than or equal to the second preset threshold, the second level alarm is triggered; when the dust-vibration influence factor R value is less than the second preset threshold and greater than the third preset threshold, the first level alarm is triggered; wherein the first preset threshold is greater than the second preset threshold, and the second preset threshold is greater than the third preset threshold.

[0074] For example: assuming that the first preset threshold is 3.0, the second preset threshold is 2.0, and the third preset threshold is 3.0, three levels of fault warning levels are set: the third level alarm is the dust-vibration impact factor R>=3.0, the highest warning level, and the greatest fault risk; the second level alarm is the dust-vibration impact factor R<3.0 and R>=2.0, a medium fault risk warning; the first level alarm is the dust-vibration impact factor R<2.0 and R>=1.0, a minor fault risk warning; based on the warning level, the corresponding maintenance strategy is generated: the first level alarm is to increase the monitoring frequency, prepare to clean the uninterruptible power supply, and consider inspecting the uninterruptible power supply; the second level alarm is to inspect the uninterruptible power supply equipment, assess the possible failure risk, and consider maintenance in the short term; the third level alarm is to immediately shut down for inspection, and make necessary repairs or replace the uninterruptible power supply.

[0075] Embodiment 2: Based on the same inventive concept, Figure 2 As shown, this embodiment also provides a computer room power equipment fault warning system based on data analysis, the system includes: a first monitoring and warning module, a second monitoring and warning module, and a comprehensive monitoring and warning module, and the modules are connected in sequence;

[0076] The first monitoring and early warning module is used to install a dust sensor in the control room, and monitor the dust concentration in the air in real time through the dust sensor; establish an adaptive dust concentration early warning model, and calculate the dust concentration early warning threshold through the adaptive dust concentration early warning model; when it is monitored that the dust concentration in the control room reaches the dust concentration early warning threshold, a fault early warning signal is reported, and the circuit board, cooling system and equipment surroundings of the uninterruptible power supply are cleaned.

[0077] The second monitoring and early warning module is used to install a vibration sensor on an uninterruptible power supply in normal operating state, collect real-time vibration data of the uninterruptible power supply through the vibration sensor; identify the correlation between vibration intensity and uninterruptible power supply failure based on the vibration data, establish a vibration intensity assessment model, and calculate a comprehensive vibration index through the vibration intensity assessment model.

[0078] The comprehensive monitoring and early warning module is used to form a dust-vibration joint monitoring data set through the data collected by the dust sensor and the vibration sensor, establish a dust-vibration synergistic impact model based on the impact of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board, calculate the dust-vibration impact factor through the dust-vibration synergistic impact model, and judge the fault warning level according to the numerical value of the dust-vibration impact factor to generate a maintenance strategy.

[0079] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0080] Finally, it should be noted that: Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for early warning of power equipment failure in a computer room based on data analysis, which is used to detect and early warning of failure points of uninterruptible power supply circuit boards under special environmental conditions of dust and vibration interference in the control room of a metallurgical plant; characterized in that: The method comprises the following steps: S10, installing a dust sensor in the control room, and monitoring the dust concentration in the air in real time through the dust sensor; establishing an adaptive dust concentration warning model, and calculating the dust concentration warning threshold through the adaptive dust concentration warning model; reporting a fault warning signal when the dust concentration in the control room reaches the dust concentration warning threshold, and cleaning the circuit board, cooling system and equipment surroundings of the uninterruptible power supply; S20, installing a vibration sensor on an uninterruptible power supply in a normal operating state, collecting real-time vibration data of the uninterruptible power supply through the vibration sensor; identifying a correlation between vibration intensity and uninterruptible power supply failure based on the vibration data, establishing a vibration intensity evaluation model, and calculating a comprehensive vibration index through the vibration intensity evaluation model; S30, forming a dust-vibration joint monitoring data set through the data collected by the dust sensor and the vibration sensor, establishing a dust-vibration synergistic impact model based on the impact of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board, calculating the dust-vibration impact factor through the dust-vibration synergistic impact model, and judging the fault warning level according to the numerical value of the dust-vibration impact factor, and generating a maintenance strategy.

2. A method for early warning of power equipment failure in a computer room based on data analysis as claimed in claim 1, characterized in that: The method for calculating the dust concentration warning threshold by using the adaptive dust concentration warning model includes: The dust sensor is installed near the uninterruptible power supply in the control room and at the air inlet of the ventilation system to monitor the dust concentration data in the control room in real time. An adaptive dust concentration warning model is established based on the monitored dust concentration data set, and the dust concentration warning threshold D is calculated. t ; The dust concentration warning threshold D t Calculated by the following formula: in, is the historical dust concentration average; σ D is the standard deviation of dust concentration; max(D t-n:t-1 ) is the maximum dust concentration value in the previous n time windows; α represents the weight of the historical dust concentration average value, β represents the weight of the historical dust concentration standard deviation, γ represents the weight of the maximum dust concentration value in the previous n time windows, and α+β+γ=1.

3. A method for early warning of power equipment failure in a computer room based on data analysis as claimed in claim 2, characterized in that: The method for determining the weight coefficients α, β, and γ includes: The weight coefficients α, β, and γ are determined by optimizing the objective function as follows: Q(α,β,γ)=αE p +βE n +γVar(D t ); Among them, E p It indicates the false alarm rate of the model judging normal dust concentration as high concentration; E n Indicates the false alarm rate that the model fails to identify high dust concentration; Var(D t ) represents the warning threshold D t Threshold volatility; The actual impact of false alarms and missed alarms on uninterruptible power supply fault detection is analyzed through historical data, and the values ​​of α and β are set according to the actual degree of impact; the values ​​of α, β, and γ are adjusted through cross-validation method to achieve the best balance among false alarm rate, missed alarm rate, and threshold fluctuation.

4. A method for early warning of power equipment failure in a computer room based on data analysis as claimed in claim 1, characterized in that: The method for calculating the comprehensive vibration index by using the vibration intensity assessment model comprises: Install a vibration sensor near the uninterruptible power supply in the control room, collect real-time vibration data of the uninterruptible power supply through the vibration sensor, and record the specific vibration amplitude value and vibration frequency; establish a vibration intensity assessment model through the collected vibration data set, and calculate a comprehensive vibration index; The comprehensive vibration index is calculated by the following formula: Among them, V i A comprehensive vibration index indicating the overall vibration intensity; j Indicates the vibration amplitude of the jth frequency band; F j represents the vibration frequency of the jth frequency band; A1 represents the standardized vibration amplitude; F1 represents the standardized vibration frequency; m represents the number of frequency bands; Collect historical data on uninterruptible power supply failures, analyze the relationship between the uninterruptible power supply failure rate and the vibration intensity assessment model through historical data, and calculate the comprehensive vibration index that will cause an increase in the uninterruptible power supply failure rate.

5. The method for early warning of power equipment failure in a computer room based on data analysis as claimed in claim 1, characterized in that: The method for establishing a dust-vibration synergistic impact model based on the influence of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board includes: The formula for calculating the dust-vibration impact factor through the dust-vibration synergistic impact model is expressed as: Where R represents the dust-vibration impact factor of the uninterruptible power supply, which is the comprehensive dust concentration and vibration intensity; D c Indicates the current dust concentration; D t Indicates the warning threshold of dust concentration; V1 is the standardized vibration intensity; V i is the comprehensive vibration index; p1 and p2 represent nonlinear index; The uninterruptible power supply fault warning level is determined according to the value of the dust-vibration impact factor, and a maintenance strategy is generated.

6. A method for early warning of power equipment failure in a computer room based on data analysis as claimed in claim 5, characterized in that: The method for determining the uninterruptible power supply fault warning level according to the value of the dust-vibration impact factor R comprises: The fault warning level is divided into three levels; when the dust-vibration impact factor R value is greater than or equal to the first preset threshold, the third level alarm is triggered; when the dust-vibration impact factor R value is less than the first preset threshold and greater than or equal to the second preset threshold, the second level alarm is triggered; when the dust-vibration impact factor R value is less than the second preset threshold and greater than the third preset threshold, the first level alarm is triggered; wherein the first preset threshold is greater than the second preset threshold, and the second preset threshold is greater than the third preset threshold.

7. A computer room power equipment fault early warning system based on data analysis, used to execute the method according to any one of claims 1 to 6, characterized in that: The system comprises: a first monitoring and early warning module, a second monitoring and early warning module, and a comprehensive monitoring and early warning module, wherein the modules are connected in sequence; The first monitoring and early warning module is used to install a dust sensor in the control room, monitor the dust concentration in the air in real time through the dust sensor; establish an adaptive dust concentration early warning model, and calculate the dust concentration early warning threshold through the adaptive dust concentration early warning model; when it is monitored that the dust concentration in the control room reaches the dust concentration early warning threshold, report a fault early warning signal, and clean the circuit board, cooling system and equipment surroundings of the uninterruptible power supply; The second monitoring and early warning module is used to install a vibration sensor on the uninterruptible power supply in normal operation, collect real-time vibration data of the uninterruptible power supply through the vibration sensor; identify the correlation between vibration intensity and uninterruptible power supply failure based on the vibration data, establish a vibration intensity evaluation model, and calculate the comprehensive vibration index through the vibration intensity evaluation model; The comprehensive monitoring and early warning module is used to form a dust-vibration joint monitoring data set through the data collected by the dust sensor and the vibration sensor, establish a dust-vibration synergistic impact model based on the impact of the synergistic effect of dust and vibration on the failure of the uninterruptible power supply circuit board, calculate the dust-vibration impact factor through the dust-vibration synergistic impact model, and judge the fault warning level according to the numerical value of the dust-vibration impact factor to generate a maintenance strategy.

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