A power communication intelligent computer room operation and maintenance management system and method thereof

Abstract

The present invention discloses an operation and maintenance management system and method for an electric power communication intelligent computer room, and relates to the technical field of operation and maintenance management of an electric power communication intelligent computer room. Through intelligent devices and sensors, key data such as electromagnetic interference intensity and environmental dust concentration are collected in high and low voltage switch cabinets, and the operation status of the power system is monitored in real time. By analyzing the changes in these data, it is judged whether the current environmental conditions are suitable for the normal operation of sensors and intelligent terminals, and the environmental conditions are divided into three levels: suitable, medium and unsuitable. For medium-suitable environmental conditions, their changes are further monitored and analyzed to evaluate the degree of interference to the equipment. If the interference degree is high, it is evaluated whether the equipment needs to be adjusted or replaced to ensure the stability of the system. If the interference is low, the normal operation of the equipment is maintained. Through this method, the safety, reliability and operation efficiency of the power system are effectively improved, and the risk of multiple point failures caused by extreme environmental conditions is prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of operation and maintenance management of electric power communication intelligent computer rooms, and in particular to an operation and maintenance management system and method for an electric power communication intelligent computer room. Background Art

[0002] The operation and maintenance management of the power communication smart room refers to the use of intelligent means and information technology to monitor, maintain and manage the equipment in the power communication room to ensure the safe and stable operation of the room equipment. The system usually integrates technologies such as the Internet of Things, cloud computing, and big data. Through functions such as remote monitoring, data analysis, and fault diagnosis, it realizes intelligent maintenance and management of equipment, reduces manual operations, and improves operation and maintenance efficiency. In this management system, high and low voltage switchgear is one of the common equipment, mainly used to control and protect circuits in power systems. Through the intelligent operation and maintenance management system, the operating status and fault information of high and low voltage switchgear can be monitored in real time to ensure the safety and continuity of power supply.

[0003] High and low voltage switchgear is an electrical device used to achieve the transmission, distribution and control of electric energy in the power system. It consists of two parts, high voltage and low voltage. The high voltage part is usually used to connect power stations or substations, carrying the input and output of high voltage power; the low voltage part is mainly responsible for the further distribution and control of power, ensuring that power is safely and reliably delivered to various electrical equipment. High and low voltage switchgear usually contains components such as circuit breakers, switches, fuses, disconnectors and protective devices to protect the power system from overload, short circuit and other faults.

[0004] When high and low voltage switchgear is operated and maintained, data processing is required. Data processing usually refers to the collection, monitoring and analysis of various operating data in the power system through intelligent devices and sensors. These data include information such as voltage, current, power, temperature, and equipment status. Through data processing, the operating status of the switchgear can be monitored in real time, fault diagnosis, early warning, remote control, and maintenance optimization can be performed, thereby improving the safety, reliability, and efficiency of the power system. However, in high and low voltage switchgear, sensors and intelligent terminals may be affected by extreme environmental conditions (such as high temperature, humidity, dust, and electromagnetic interference), which may cause equipment damage or data reading errors. And if environmental deterioration is not detected and handled in time, it may cause multiple points of failure in the system, which is difficult to repair in a short time, and thus affect the stability of the entire power network.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide an electric power communication intelligent computer room operation and maintenance management system and method thereof to solve the deficiencies in the background technology.

[0007] In order to achieve the above object, the present invention provides the following technical solution: a method for operation and maintenance management of a power communication smart computer room, comprising the following steps:

[0008] S1: Collect status data of sensors and smart terminals, the status data including electromagnetic interference intensity data, and collect environmental data around high and low voltage switch cabinets, the environmental data including dust concentration data of high and low voltage switch cabinet environments;

[0009] S2: Analyze the changes in the collected electromagnetic interference intensity data and the dust concentration data of the high and low voltage switch cabinet environment to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divide the current environmental conditions into three levels: suitable, medium and unsuitable;

[0010] S3: For sensors and smart terminals under moderately suitable environmental conditions, continuously monitor and analyze changes in environmental conditions, and determine the degree of interference to sensors and smart terminals based on the analysis results;

[0011] S4: If the medium-suitable environmental conditions have a high degree of interference with the sensors and smart terminals, determine whether the equipment needs to be adjusted or replaced. If the medium-suitable environmental conditions have a low degree of interference with the sensors and smart terminals, maintain the normal operation of the equipment.

[0012] Preferably, in S2, the electromagnetic interference spatial distribution anomaly index is generated after analyzing the changes in the collected electromagnetic interference intensity data, wherein the electromagnetic interference spatial distribution anomaly index is obtained by:

[0013] Collect the electromagnetic interference intensity data at n spatial positions, and the electromagnetic interference intensity value at each position is xi, then the data matrix X is expressed as: Among them, n is the number of spatial positions, p is the dimension of electromagnetic interference intensity data at different frequency bands or time points, and the standardized matrix Z is obtained after standardization. The covariance matrix C is calculated for the standardized data matrix Z, and the expression is: In the formula, each element C of the covariance matrix C ijRepresents the covariance between variables xi and xj; calculates the eigenvalue λi and the corresponding eigenvector vi of the covariance matrix C, expressed as: Cvi=λivi; where λi represents the variance of the data in the direction of the i-th principal component, and vi represents the corresponding principal component direction. The first k principal components are selected according to the size of the eigenvalue. The selected principal components form a matrix Vk, which is composed of k eigenvectors v1, v2,…, vk, expressed as: Vk=[v1v2…vk]; projects the standardized data matrix Z onto the principal component direction, and calculates the principal component score matrix T, expressed as: T=Z*Vk; where T is a matrix of n×k dimensions, representing the score of each position in the principal component direction. According to the principal component score, the electromagnetic interference spatial distribution anomaly index is calculated, that is, the degree to which the score of each position deviates from the center, expressed as: Among them, Anomaly Index i It is the electromagnetic interference spatial distribution anomaly index.

[0014] Preferably, in S2, the dust accumulation index is generated after analyzing the changes in the collected high and low voltage switch cabinet environmental dust concentration data, and the dust accumulation index is obtained by:

[0015] Record at different times t i The measured dust concentration value C(t i ), where i = 1, 2, ..., n represents the time point of measurement, C(t i ) is at time t i The dust concentration at the time is defined as Δt, and the time interval between each time point is defined as Δt = t i+2 -t i In each time interval, the accumulated amount of dust is the product of dust concentration and time interval, expressed as: A i =C(t i )·Δt;A i is the dust accumulation. The accumulation in all time periods is added together to get the total dust accumulation. The expression is: A total is the total dust accumulation. The dust accumulation index is converted into the average dust accumulation per unit time through normalization, that is, the dust accumulation index, which is expressed as: Where T is the total observation time and DAI is the dust accumulation index.

[0016] Preferably, the electromagnetic interference spatial distribution anomaly index and the dust accumulation index are converted into a first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model uses each group of first eigenvectors to predict the suitability value label of the current environmental conditions as a prediction target, and takes minimizing the sum of prediction errors for the suitability value labels of all current environmental conditions as a training target. The machine learning model is trained until the sum of prediction errors converges, then the model training is stopped, and the suitability value of the current environmental conditions is determined based on the model output results, wherein the machine learning model is a polynomial regression model.

[0017] Preferably, the suitability value of the current environmental condition obtained is compared with a gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the suitability value of the current environmental condition is compared with the first standard threshold and the second standard threshold respectively;

[0018] If the suitability value of the current environmental conditions is greater than the second standard threshold, it means that the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and the suitability is high, and it is divided into a suitable environmental condition level; if the suitability value of the current environmental conditions is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and when the suitability is general, it is divided into a medium suitable environmental condition level; if the suitability value of the current environmental conditions is less than the first standard threshold, it means that the current environmental conditions are not suitable for the normal operation of sensors and smart terminals, and it is divided into an unsuitable environmental condition level.

[0019] Preferably, in S3, for sensors and smart terminals under moderately suitable environmental conditions, the changes in environmental conditions are continuously monitored and analyzed, and the degree of interference to the sensors and smart terminals is determined based on the analysis results, specifically:

[0020] For sensors and smart terminals under moderately suitable environmental conditions, that is, the suitability value of the current environmental conditions generated within a fixed time period is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the suitability values ​​of the current environmental conditions generated within a subsequent fixed time period that are greater than or equal to the first standard threshold and less than or equal to the second standard threshold are collected, and a data set is established. The mean and standard deviation of the data set are calculated, and after analyzing them, the degree of interference to the sensors and smart terminals is judged based on the analysis results.

[0021] Preferably, if the mean suitability value in the data set is greater than or equal to the reference threshold of the mean suitability value, and the standard deviation of the suitability value is less than the reference threshold of the standard deviation of the suitability value, it is classified as a low interference level; if the mean suitability value is greater than or equal to the reference threshold of the mean suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, it is classified as a medium interference level; if the mean suitability value is less than the reference threshold of the mean suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, it is classified as a high interference level; if the mean suitability value is less than the reference threshold of the mean suitability value, and the standard deviation of the suitability value is less than the reference threshold of the standard deviation of the suitability value, it is classified as a medium-low interference level.

[0022] Preferably, in S4, if the medium suitable environmental conditions have a high degree of interference with the sensor and the intelligent terminal, it is determined whether the device needs to be adjusted or replaced; if the medium suitable environmental conditions have a low degree of interference with the sensor and the intelligent terminal, the normal operation of the device is maintained, specifically:

[0023] If the interference degree of the medium suitable environmental conditions on the sensors and intelligent terminals is high, that is, the mean value of the suitability value is less than the reference threshold of the mean value of the suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, the probability of equipment failure is calculated according to the equipment failure model and the current environmental conditions. The expression is: P failure =f(μ s ,σ s , equipment type); where f is the calculation function of the failure probability, μ s is the mean of the suitability values ​​within the set, σ s is the standard deviation of suitability values ​​within the set, P failure is the probability of equipment failure;

[0024] The acquired probability of device failure is compared with the probability threshold. If the probability of device failure is greater than or equal to the probability threshold, it indicates a high risk of failure and the device should be replaced. If the probability of device failure is less than the probability threshold, it indicates a low risk of failure and the current device should continue to be used. If the moderately suitable environmental conditions have a low degree of interference with sensors and smart terminals, the normal operation of the device is maintained and there is no need to adjust or replace the device.

[0025] An operation and maintenance management system for a power communication smart computer room, comprising an environmental data collection module, an environmental suitability assessment module, a medium-suitability environment monitoring module, and an equipment adjustment and maintenance decision module;

[0026] An environmental data collection module collects status data of sensors and smart terminals, the status data including electromagnetic interference intensity data, and collects environmental data around high and low voltage switch cabinets, the environmental data including dust concentration data of high and low voltage switch cabinet environments;

[0027] The environmental suitability assessment module analyzes the changes in the collected electromagnetic interference intensity data and the dust concentration data of the high and low voltage switch cabinet environment to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divides the current environmental conditions into three levels: suitable, medium and unsuitable;

[0028] The medium-suitable environment monitoring module continuously monitors and analyzes the changes in environmental conditions for sensors and smart terminals under medium-suitable environmental conditions, and determines the degree of interference to the sensors and smart terminals based on the analysis results;

[0029] The equipment adjustment and maintenance decision module determines whether the equipment needs to be adjusted or replaced if the moderately suitable environmental conditions have a high degree of interference with sensors and smart terminals. If the moderately suitable environmental conditions have a low degree of interference with sensors and smart terminals, the normal operation of the equipment is maintained.

[0030] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0031] 1. The present invention effectively monitors the operation status of the power system by collecting and analyzing the status data (such as electromagnetic interference intensity data) of sensors and intelligent terminals in high and low voltage switch cabinets and the surrounding environment data (such as dust concentration data) in real time. Through the analysis of these data, the current environmental conditions are divided into three levels: suitable, medium and unsuitable. In particular, continuous monitoring and analysis are carried out for equipment under medium suitable environmental conditions to determine the degree of interference of the environment on the equipment. If the degree of interference is high, the system can promptly evaluate and decide whether the equipment needs to be adjusted or replaced to ensure the stable operation of the equipment.

[0032] 2. The present invention can not only improve the safety and reliability of the power system, but also prevent equipment failures caused by extreme environmental conditions through intelligent data processing and analysis, thereby reducing system downtime and maintenance costs. At the same time, for equipment under moderately suitable environmental conditions, refined monitoring and analysis can avoid unnecessary equipment replacement, extend the service life of the equipment, and ensure the efficient operation of the power system. Therefore, the system can respond to complex environmental changes more intelligently and improve the overall power management level. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0034] Figure 1The present invention is a method flow chart of a method for operation and maintenance management of a power communication intelligent computer room.

[0035] Figure 2 This is a module schematic diagram of an electric power communication intelligent computer room operation and maintenance management system of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0037] For examples, see Figure 1 As shown, the power communication smart room operation and maintenance management method described in this embodiment includes the following steps:

[0038] S1: Collect status data of sensors and smart terminals, the status data including electromagnetic interference intensity data, and collect environmental data around high and low voltage switch cabinets, the environmental data including dust concentration data of high and low voltage switch cabinet environments;

[0039] S2: Analyze the changes in the collected electromagnetic interference intensity data and the dust concentration data of the high and low voltage switch cabinet environment to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divide the current environmental conditions into three levels: suitable, medium and unsuitable;

[0040] S3: For sensors and smart terminals under moderately suitable environmental conditions, continuously monitor and analyze changes in environmental conditions, and determine the degree of interference to sensors and smart terminals based on the analysis results;

[0041] S4: If the medium-suitable environmental conditions have a high degree of interference with the sensors and smart terminals, determine whether the equipment needs to be adjusted or replaced. If the medium-suitable environmental conditions have a low degree of interference with the sensors and smart terminals, maintain the normal operation of the equipment.

[0042] In S1, status data of sensors and smart terminals are collected, the status data including electromagnetic interference intensity data, and environmental data around high and low voltage switch cabinets are collected, the environmental data including dust concentration data of high and low voltage switch cabinet environments, mainly including:

[0043] The electromagnetic interference intensity data refers to the interference intensity caused by external electromagnetic field sources in the internal and external environment of high and low voltage switch cabinets. This data reflects the impact of external electromagnetic fields on sensors and smart terminal electronic circuits.

[0044] Install dedicated EMI sensors or detection equipment inside and around high and low voltage switch cabinets. These devices can detect and record the EMI intensity in different frequency bands. Depending on the system requirements, you can choose to manually measure the EMI intensity data regularly, or use an automated system for continuous monitoring to capture any sudden or periodic EMI phenomena. The collected EMI intensity data is transmitted to the central data processing system for analysis. It is necessary to record the time, frequency range, interference intensity and other information of the data, and store these data in the database for subsequent analysis and system optimization.

[0045] Environmental dust concentration data refers to the concentration level of suspended particulate matter (PM10, PM2.5, etc.) in the air around high and low voltage switchgear. This data reflects the potential impact of dust on the internal equipment and sensors of the switchgear, especially the negative effects on the heat dissipation, insulation and wear of mechanical parts of the equipment.

[0046] Appropriate dust concentration sensors are installed on the outside and inside of high and low voltage switchgear to monitor the concentration of dust particles in the air in real time. These sensors are able to detect suspended particles in the air and output concentration data in numerical form. Dust concentration can be obtained through continuous monitoring or sampling at specific time intervals. For example, the monitoring frequency should be increased in dusty environments to more accurately reflect changes in dust concentration. The dust concentration data is aggregated into a central database through a transmission system, recording information such as time, location, concentration value, etc., and stored for a long time for trend analysis and environmental impact assessment.

[0047] S2: Analyze the changes in the collected electromagnetic interference intensity data and high and low voltage switch cabinet environmental dust concentration data to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divide the current environmental conditions into three levels: suitable, medium and unsuitable.

[0048] After analyzing the changes in the collected electromagnetic interference intensity data, an electromagnetic interference spatial distribution anomaly index is generated. The method for obtaining the electromagnetic interference spatial distribution anomaly index is as follows:

[0049] Collect electromagnetic interference intensity data at n spatial positions, and the electromagnetic interference intensity value of each position is xi (where i represents the index of the spatial position), then the data matrix X can be expressed as: Among them, n is the number of spatial positions, p is the dimension of electromagnetic interference intensity data at different frequency bands or time points, and the standardized matrix Z is obtained after standardization. The covariance matrix C is calculated for the standardized data matrix Z, and the expression is: In the formula, each element C of the covariance matrix C ijRepresents the covariance between variables xi and xj; calculates the eigenvalue λi and the corresponding eigenvector vi of the covariance matrix C, expressed as: Cvi=λivi; where λi represents the variance of the data in the direction of the i-th principal component, and vi represents the corresponding principal component direction. The first k principal components are selected according to the size of the eigenvalue. The cumulative variance explanation rate of these principal components should be high enough (such as greater than 80%). The selected principal components can form a matrix Vk, which is composed of k eigenvectors v1, v2,…, vk, expressed as: Vk=[v1v2…vk]; projects the standardized data matrix Z to the principal component direction, and calculates the principal component score matrix T, expressed as: T=Z*Vk; where T is a matrix of n×k dimensions, representing the score of each position in the principal component direction. According to the principal component score, the electromagnetic interference spatial distribution anomaly index is calculated, that is, the degree to which the score of each position deviates from the center, expressed as: Among them, Anomaly Index i It is the electromagnetic interference spatial distribution anomaly index.

[0050] According to the calculated electromagnetic interference spatial distribution anomaly index, the abnormal area of ​​electromagnetic interference in spatial distribution can be identified. The higher the anomaly index, the more abnormal the electromagnetic interference intensity distribution at that location. These data can be used for further fault diagnosis, locating electromagnetic interference sources or optimizing equipment layout.

[0051] The dust accumulation index is generated by analyzing the changes in the collected high and low voltage switch cabinet environmental dust concentration data. The method for obtaining the dust accumulation index is as follows:

[0052] Record at different times t i The dust concentration value C(t i ), where i = 1, 2, ..., n represents the time point of measurement, C(t i ) is at time t i The dust concentration at the time is defined as Δt, and the time interval between each time point is defined as Δt = t i+1 -t i In each time interval, the accumulated amount of dust is the product of dust concentration and time interval, expressed as: A i =C(t i )·Δt;A i is the dust accumulation. The accumulation in all time periods is added together to get the total dust accumulation. The expression is: A total is the total dust accumulation. The dust accumulation index is converted into the average dust accumulation per unit time through normalization, that is, the dust accumulation index, which is expressed as: Where T is the total observation time length (eg, T = n*Δt), and DAI is the dust accumulation index.

[0053] A higher DAI value indicates that during the observation period, the dust concentration in the environment is high and the accumulation rate is fast, which may have an adverse effect on the heat dissipation, insulation and mechanical performance of the equipment. DAI can be used to formulate equipment cleaning and maintenance plans. For example, a dust accumulation index threshold is set. When the DAI exceeds the threshold, equipment cleaning or filter replacement should be considered.

[0054] The electromagnetic interference spatial distribution anomaly index and the dust accumulation index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model takes the suitability value label of the current environmental conditions predicted by each group of first eigenvectors as the prediction target, and takes minimizing the sum of prediction errors of the suitability value labels of all current environmental conditions as the training target. The machine learning model is trained until the sum of prediction errors converges, and the model training is stopped. The suitability value of the current environmental conditions is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

[0055] The method for obtaining the suitability value of the current environmental conditions is as follows: from the first feature vector training data of the trained machine learning model, the corresponding function expression is obtained: CR = f1 (Anomaly Index i , DAI); where f1 is the output function of the model, Anomaly Index i is the electromagnetic interference spatial distribution anomaly index, DAI is the dust accumulation index, and CR is the suitability value of the current environmental conditions.

[0056] The obtained suitability value of the current environmental condition is compared with the gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the suitability value of the current environmental condition is compared with the first standard threshold and the second standard threshold respectively;

[0057] If the suitability value of the current environmental condition is greater than the second standard threshold, it means that the current environmental condition is suitable for the normal operation of the sensor and the smart terminal, and the suitability is high, and it is classified as a suitable environmental condition level;

[0058] If the suitability value of the current environmental condition is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the current environmental condition is suitable for the normal operation of the sensor and the smart terminal, but the suitability is average, and it is classified as a medium suitable environmental condition level;

[0059] If the suitability value of the current environmental condition is less than the first standard threshold, it means that the current environmental condition is not suitable for the normal operation of the sensor and the smart terminal, and it is classified as an unsuitable environmental condition level.

[0060] Under the appropriate environmental condition level, sensors and smart terminals can operate efficiently and safely in the current environment. Usually no additional protection or adjustment measures are required.

[0061] Although the medium suitable environmental condition level can support the normal operation of the equipment, there may be some potential risks. It is recommended to conduct regular monitoring and make minor adjustments or protection as needed.

[0062] Unsuitable environmental conditions pose a clear threat to the normal operation of the equipment, and it may be necessary to take immediate measures to improve the environmental conditions or consider moving the equipment to a more suitable environment.

[0063] S3: For sensors and smart terminals under moderately suitable environmental conditions, continuously monitor and analyze changes in environmental conditions, and determine the degree of interference to sensors and smart terminals based on the analysis results.

[0064] For sensors and smart terminals under moderately suitable environmental conditions, that is, the suitability value of the current environmental conditions generated within a fixed time period is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the suitability values ​​of the current environmental conditions generated within a subsequent fixed time period that are greater than or equal to the first standard threshold and less than or equal to the second standard threshold are collected, and a data set is established. The mean and standard deviation of the data set are calculated, and after analyzing them, the degree of interference to the sensors and smart terminals is judged based on the analysis results.

[0065] If the mean value of suitability in the data set is greater than or equal to the reference threshold of the mean value of suitability, and the standard deviation of suitability is less than the reference threshold of the standard deviation of suitability, it means that the environmental conditions are relatively stable and the suitability is high, and the interference to sensors and smart terminals is small, and it is classified as a low interference level;

[0066] If the mean suitability value is greater than or equal to the reference threshold of the mean suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, although the environmental suitability is high, the fluctuation is large, which may cause a certain degree of interference, and the equipment may need to cope with frequent environmental changes. It is classified as a medium interference level;

[0067] If the mean suitability value is less than the reference threshold of the mean suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, the environmental suitability is low and fluctuates greatly, which may cause significant interference to the equipment, and the equipment may malfunction or performance degradation, and it is classified as a high interference level;

[0068] If the mean suitability value is less than the reference threshold of the mean suitability value, and the standard deviation of the suitability value is less than the reference threshold of the standard deviation of the suitability value, although the suitability is low, the environment is relatively stable and the degree of interference is relatively low, but there may still be potential risks, and it is classified as medium and low interference level.

[0069] S4: If the medium-suitable environmental conditions have a high degree of interference with the sensors and smart terminals, determine whether the equipment needs to be adjusted or replaced. If the medium-suitable environmental conditions have a low degree of interference with the sensors and smart terminals, maintain the normal operation of the equipment.

[0070] If the interference degree of the medium suitable environmental conditions on the sensors and intelligent terminals is high, that is, the mean value of the suitability value is less than the reference threshold of the mean value of the suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, the probability of equipment failure is calculated according to the equipment failure model and the current environmental conditions. The expression is: P failure =f(μ s ,σ s , equipment type); where f is the calculation function of the failure probability, which depends on factors such as the suitability mean, standard deviation, and equipment type, μ s is the mean of the suitability values ​​within the set, σ s is the standard deviation of suitability values ​​within the set, P failure The probability of device failure is compared with the probability threshold. If the probability of device failure is greater than or equal to the probability threshold, it indicates that the failure risk is high and it is recommended to replace the device. If the probability of device failure is less than the probability threshold, it indicates that the failure risk is low and the current device can continue to be used. If the medium-suitable environmental conditions have a low degree of interference with sensors and smart terminals, the normal operation of the device is maintained and there is no need to adjust or replace the device.

[0071] In this embodiment, during the operation of the high and low voltage switchgear, the status data of the sensors and intelligent terminals (including electromagnetic interference intensity data) and the surrounding environment data (including environmental dust concentration data) are first collected. Then, these data are analyzed to determine whether the current environmental conditions are suitable for the normal operation of the sensors and intelligent terminals, and the environmental conditions are divided into three levels: suitable, medium and unsuitable. For equipment under medium suitable environmental conditions, the changes in environmental conditions are continuously monitored and analyzed, and the degree of interference with the equipment is determined based on the analysis results. If the degree of interference is found to be high, further evaluate whether the equipment needs to be adjusted or replaced; if the degree of interference is low, continue to maintain the normal operation of the equipment.

[0072] For examples, see Figure 2As shown, an operation and maintenance management system for a power communication smart computer room includes an environmental data collection module, an environmental suitability assessment module, a medium-suitability environment monitoring module, and an equipment adjustment and maintenance decision module;

[0073] An environmental data collection module collects status data of sensors and smart terminals, the status data including electromagnetic interference intensity data, and collects environmental data around high and low voltage switch cabinets, the environmental data including dust concentration data of high and low voltage switch cabinet environments;

[0074] The environmental suitability assessment module analyzes the changes in the collected electromagnetic interference intensity data and the dust concentration data of the high and low voltage switch cabinet environment to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divides the current environmental conditions into three levels: suitable, medium and unsuitable;

[0075] The medium-suitable environment monitoring module continuously monitors and analyzes the changes in environmental conditions for sensors and smart terminals under medium-suitable environmental conditions, and determines the degree of interference to the sensors and smart terminals based on the analysis results;

[0076] Equipment adjustment and maintenance decision module: if the medium-suitable environmental conditions have a high degree of interference with sensors and smart terminals, determine whether the equipment needs to be adjusted or replaced; if the medium-suitable environmental conditions have a low degree of interference with sensors and smart terminals, maintain the normal operation of the equipment;

[0077] An operation and maintenance management method for an electric power communication smart computer room provided by an embodiment of the present invention is realized through the above-mentioned set of operation and maintenance management system for an electric power communication smart computer room. The specific methods and processes of an operation and maintenance management system for an electric power communication smart computer room are detailed in the embodiment of the above-mentioned operation and maintenance management method for an electric power communication smart computer room, which will not be repeated here.

[0078] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0079] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0080] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0081] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0082] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0083] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0084] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for operation and maintenance management of a power communication intelligent computer room, characterized in that: The following steps are involved: S1: Collect status data of sensors and smart terminals, the status data including electromagnetic interference intensity data, and collect environmental data around high and low voltage switch cabinets, the environmental data including dust concentration data of high and low voltage switch cabinet environments; S2: Analyze the changes in the collected electromagnetic interference intensity data and the dust concentration data of the high and low voltage switch cabinet environment to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divide the current environmental conditions into three levels: suitable, medium and unsuitable; In S2, the collected electromagnetic interference intensity data changes are analyzed to generate an electromagnetic interference spatial distribution anomaly index, wherein the electromagnetic interference spatial distribution anomaly index is obtained by: Collect the electromagnetic interference intensity data at n spatial positions, and the electromagnetic interference intensity value at each position is xi, then the data matrix X is expressed as: Among them, n is the number of spatial positions, p is the dimension of electromagnetic interference intensity data at different frequency bands or time points, and the standardized matrix Z is obtained after standardization. The covariance matrix C is calculated for the standardized data matrix Z, and the expression is: In the formula, each element C of the covariance matrix C ij Represents the covariance between variables xi and xj; calculates the eigenvalue λi and the corresponding eigenvector vi of the covariance matrix C, expressed as: Cvi=λivi; where λi represents the variance of the data in the direction of the i-th principal component, and vi represents the corresponding principal component direction. The first k principal components are selected according to the size of the eigenvalue. The selected principal components form a matrix Vk, which is composed of k eigenvectors v1, v2,…, vk, expressed as: Vk=[v1v2…vk]; projects the standardized data matrix Z onto the principal component direction, and calculates the principal component score matrix T, expressed as: T=Z*Vk; where T is a matrix of n×k dimensions, representing the score of each position in the principal component direction. According to the principal component score, the electromagnetic interference spatial distribution anomaly index is calculated, that is, the degree to which the score of each position deviates from the center, expressed as: Among them, AnomalyIndex i is the electromagnetic interference spatial distribution anomaly index; The dust accumulation index is generated by analyzing the changes in the collected dust concentration data of the high and low voltage switch cabinet environment. The dust accumulation index is obtained by recording the dust concentration at different times t i The measured dust concentration value C(t i ), where i = 1, 2, ..., n represents the time point of measurement, C(t i ) is at time t i The dust concentration at the time is defined as Δt, and the time interval between each time point is defined as Δt = t i+1 -t i In each time interval, the accumulated amount of dust is the product of dust concentration and time interval, expressed as: A i =C(t i )·Δt;A i is the dust accumulation. The accumulation in all time periods is added to get the total dust accumulation. The expression is: A total is the total dust accumulation. The dust accumulation index is converted into the average dust accumulation per unit time through normalization, that is, the dust accumulation index, which is expressed as: Where T is the total observation time, and DAI is the dust accumulation index; S3: For sensors and smart terminals under moderately suitable environmental conditions, continuously monitor and analyze changes in environmental conditions, and determine the degree of interference to sensors and smart terminals based on the analysis results; S4: If the medium-suitable environmental conditions have a high degree of interference with the sensors and smart terminals, determine whether the equipment needs to be adjusted or replaced. If the medium-suitable environmental conditions have a low degree of interference with the sensors and smart terminals, maintain the normal operation of the equipment.

2. According to claim 1, a method for operation and maintenance management of a power communication intelligent computer room is characterized in that: The electromagnetic interference spatial distribution anomaly index and the dust accumulation index are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model takes the suitability value label of the current environmental conditions predicted by each group of first eigenvectors as the prediction target, and takes minimizing the sum of prediction errors of the suitability value labels of all current environmental conditions as the training target. The machine learning model is trained until the sum of prediction errors converges, and the model training is stopped. The suitability value of the current environmental conditions is determined according to the model output results, wherein the machine learning model is a polynomial regression model.

3. A method for operation and maintenance management of a power communication intelligent computer room according to claim 2, characterized in that: The obtained suitability value of the current environmental condition is compared with the gradient standard threshold, the gradient standard threshold includes a first standard threshold and a second standard threshold, and the first standard threshold is less than the second standard threshold, and the suitability value of the current environmental condition is compared with the first standard threshold and the second standard threshold respectively; If the suitability value of the current environmental condition is greater than the second standard threshold, it means that the current environmental condition is suitable for the normal operation of the sensor and the smart terminal, and the suitability is high, and it is classified as a suitable environmental condition level; If the suitability value of the current environmental condition is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, it means that the current environmental condition is suitable for the normal operation of the sensor and the smart terminal. If the suitability is average, it is classified as a medium suitable environmental condition level; If the suitability value of the current environmental condition is less than the first standard threshold, it means that the current environmental condition is not suitable for the normal operation of the sensor and the smart terminal, and it is classified as an unsuitable environmental condition level.

4. A method for operation and maintenance management of a power communication intelligent computer room according to claim 3, characterized in that: In S3, for sensors and smart terminals under moderately suitable environmental conditions, the changes in environmental conditions are continuously monitored and analyzed, and the degree of interference to the sensors and smart terminals is determined based on the analysis results, specifically: For sensors and smart terminals under moderately suitable environmental conditions, that is, the suitability value of the current environmental conditions generated within a fixed time period is greater than or equal to the first standard threshold and less than or equal to the second standard threshold, the suitability values ​​of the current environmental conditions generated within a subsequent fixed time period that are greater than or equal to the first standard threshold and less than or equal to the second standard threshold are collected, and a data set is established. The mean and standard deviation of the data set are calculated, and after analyzing them, the degree of interference to the sensors and smart terminals is judged based on the analysis results.

5. A method for operation and maintenance management of a power communication intelligent computer room according to claim 4, characterized in that: If the mean suitability value in the data set is greater than or equal to the reference threshold of the mean suitability value, and the standard deviation of the suitability value is less than the reference threshold of the standard deviation of the suitability value, it is classified as a low interference level; if the mean suitability value is greater than or equal to the reference threshold of the mean suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, it is classified as a medium interference level; if the mean suitability value is less than the reference threshold of the mean suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, it is classified as a high interference level; if the mean suitability value is less than the reference threshold of the mean suitability value, and the standard deviation of the suitability value is less than the reference threshold of the standard deviation of the suitability value, it is classified as a medium-low interference level.

6. A method for operation and maintenance management of a power communication intelligent computer room according to claim 5, characterized in that: In S4, if the medium suitable environmental conditions have a high degree of interference with the sensors and smart terminals, it is determined whether the equipment needs to be adjusted or replaced. If the medium suitable environmental conditions have a low degree of interference with the sensors and smart terminals, the normal operation of the equipment is maintained. Specifically: If the interference degree of the medium suitable environmental conditions on the sensors and intelligent terminals is high, that is, the mean value of the suitability value is less than the reference threshold of the mean value of the suitability value, and the standard deviation of the suitability value is greater than or equal to the reference threshold of the standard deviation of the suitability value, the probability of equipment failure is calculated according to the equipment failure model and the current environmental conditions. The expression is: P failure =f(μ S ,σ S , equipment type); where f is the calculation function of the failure probability, μ S is the mean value of suitability within the set, σ S is the standard deviation of suitability values ​​within the set, P failure is the probability of equipment failure; The acquired probability of device failure is compared with the probability threshold. If the probability of device failure is greater than or equal to the probability threshold, it indicates a high risk of failure and the device should be replaced. If the probability of device failure is less than the probability threshold, it indicates a low risk of failure and the current device should continue to be used. If the moderately suitable environmental conditions have a low degree of interference with sensors and smart terminals, the normal operation of the device is maintained and there is no need to adjust or replace the device.

7. An operation and maintenance management system for an electric power communication intelligent computer room, used to implement the operation and maintenance management method for an electric power communication intelligent computer room as described in any one of claims 1 to 6, characterized in that: It includes environmental data collection module, environmental suitability assessment module, medium-suitability environment monitoring module and equipment adjustment and maintenance decision module; An environmental data collection module collects status data of sensors and smart terminals, the status data including electromagnetic interference intensity data, and collects environmental data around high and low voltage switch cabinets, the environmental data including dust concentration data of high and low voltage switch cabinet environments; The environmental suitability assessment module analyzes the changes in the collected electromagnetic interference intensity data and the dust concentration data of the high and low voltage switch cabinet environment to determine whether the current environmental conditions are suitable for the normal operation of sensors and smart terminals, and divides the current environmental conditions into three levels: suitable, medium and unsuitable; The medium-suitable environment monitoring module continuously monitors and analyzes the changes in environmental conditions for sensors and smart terminals under medium-suitable environmental conditions, and determines the degree of interference to the sensors and smart terminals based on the analysis results; The equipment adjustment and maintenance decision module determines whether the equipment needs to be adjusted or replaced if the moderately suitable environmental conditions have a high degree of interference with sensors and smart terminals. If the moderately suitable environmental conditions have a low degree of interference with sensors and smart terminals, the normal operation of the equipment is maintained.

Images