CN116046187B - A unusual remote monitoring system of temperature for communication cabinet - Google Patents
A unusual remote monitoring system of temperature for communication cabinet Download PDFInfo
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Abstract
The invention relates to the field of data processing, in particular to a remote monitoring system for temperature abnormality of a communication cabinet, which comprises a data acquisition module, a data processing module and an early warning module, wherein the data acquisition module is used for acquiring the temperature abnormality of the communication cabinet: acquiring a communication cabinet temperature monitoring matrix and an environmental temperature data sequence; and a data processing module: obtaining a communication cabinet temperature optimization monitoring matrix according to the communication cabinet temperature monitoring matrix and the environmental temperature data sequence; obtaining a noise-free temperature element set according to a communication cabinet temperature optimization monitoring matrix, obtaining a data distribution index and a data change index of each noise-free temperature element according to the noise-free temperature set, further obtaining the abnormality degree of each noise-free temperature element, and obtaining an abnormality conclusion of the communication cabinet according to the abnormality degree; and the early warning module is used for: and carrying out early warning treatment according to the abnormal conclusion of the communication cabinet. Thereby realizing the accurate abnormal conclusion of the communication cabinet and improving the accuracy of the abnormal early warning of the communication cabinet.
Description
Technical Field
The application relates to the field of data processing, in particular to a remote monitoring system for temperature abnormality of a communication cabinet.
Background
Due to the high development of electronic technology and communication technology and the popularization of electronic equipment, the number of communication cabinets in a communication machine room is greatly increased. The communication cabinet is widely used equipment in modern information, the modern communication equipment has special requirements on environment temperature and humidity, equipment temperature and the like, when the temperature of the communication cabinet is too low, the phenomena of condensation and condensation of water vapor can be generated, the insulativity of a circuit board is reduced, an insulating material becomes more brittle, and the oxidization of electronic elements is accelerated; when the temperature is too high, the ageing speed of equipment electronic components is increased, and when serious, the electronic components are burnt out, so that the work is unstable, therefore, the working condition of the communication cabinet is required to be carefully monitored and checked by a person on duty in the working and running process of the communication cabinet, and the change conditions of the temperature and the like in the running process of the communication cabinet are mainly checked to judge whether abnormal phenomena exist or not.
However, most of the communication cabinets are continuously operated throughout the day, so that the real-time nursing and monitoring of the communication cabinets by manpower can cause manpower waste, and when enough nursing and monitoring personnel cannot be distributed to the communication cabinets, the communication cabinets are unattended, so that the detection is not real-time, the abnormal condition cannot be timely detected, and the condition of false detection is caused; when traditional through temperature sensor to the communication cabinet running condition, most monitor the temperature condition in the communication cabinet working process through single fixed temperature threshold, can not carry out comprehensive analysis to the communication cabinet temperature condition, can't synthesize local data situation and carry out accurate detection to the temperature abnormal condition, and the detection in-process receives the influence of factors such as various environmental temperature and passes, and detection accuracy is lower.
In summary, the invention provides a remote monitoring system for temperature abnormality of a communication cabinet, which monitors the operation temperature of the communication cabinet by analyzing the temperature data in the working process of the communication cabinet, extracts the temperature abnormality data, realizes the remote monitoring of the temperature abnormality of the communication cabinet, and avoids the problems of communication equipment loss, communication effect reduction and the like caused by serious abnormality of the temperature of the communication cabinet.
Disclosure of Invention
In order to solve the technical problem, the invention provides a temperature anomaly remote monitoring system for a communication cabinet, which comprises:
the system comprises a data acquisition module, a data processing module and an early warning module;
and a data acquisition module: acquiring temperature data to obtain a communication cabinet temperature monitoring matrix and an environmental temperature data sequence;
and a data processing module: obtaining optimization factors of all temperature elements in a communication cabinet temperature monitoring matrix according to the difference condition between the temperature data at all times in an environmental temperature data sequence and all temperature data in the communication cabinet temperature monitoring matrix, carrying out optimization treatment on all temperature elements according to the optimization factors of all temperature elements to obtain optimized temperature values of all temperature elements, replacing all temperature elements in the communication cabinet temperature monitoring matrix by using the optimized temperature values to obtain a communication cabinet temperature optimization monitoring matrix, and carrying out noise elimination treatment on the communication cabinet temperature optimization monitoring matrix to obtain a noise-free temperature element set, wherein the noise-free temperature element set is composed of noise-free temperature elements;
acquiring a first window of the noiseless temperature element, acquiring the number of the tuples of each category according to the first window of the noiseless temperature element, acquiring the number of the reference tuples of the first window, and acquiring the data distribution index of the noiseless temperature element according to the number of the tuples of each category and the number of the reference tuples; obtaining characteristic values of each noiseless temperature element according to the change condition of each noiseless temperature element in each direction, obtaining a first neighborhood difference value and a second neighborhood difference value of each noiseless temperature element according to the difference condition of each noiseless temperature element and neighborhood data, and obtaining a data change index of each noiseless temperature element according to the characteristic values, the first neighborhood difference value and the second neighborhood difference value of each noiseless temperature element; obtaining the abnormality degree of each noiseless temperature element according to the data distribution index and the data change index of each noiseless temperature element; taking a noise-free temperature element with the abnormality degree larger than a preset abnormality degree threshold value as abnormal data, and obtaining an abnormality conclusion of the communication cabinet according to the abnormality degree of the abnormal data;
and the early warning module is used for: and carrying out early warning treatment according to the abnormal conclusion.
Preferably, the optimizing factor of each temperature element in the temperature monitoring matrix of the communication cabinet is obtained according to the difference condition between the temperature data of each moment in the environmental temperature data sequence and each temperature data in the temperature monitoring matrix of the communication cabinet, and the optimizing factor comprises the following specific steps:
the calculation formula of the optimization factor of the temperature element of the ith row and the ith column is as follows:
wherein,,
temperature elements representing the ith row and the ith column in the communication cabinet temperature monitoring matrix, < >>
Optimization factor of temperature element representing the ith row and column->
Representing the ambient temperature at time v in the ambient temperature sequenceThe degree, k, represents the control coefficient,
is an absolute value sign.
Preferably, the optimizing process is performed on each temperature element according to the optimizing factor of each temperature element to obtain an optimized temperature value of each temperature element, and the method comprises the following specific steps:
the average value of all elements in the environment temperature sequence is called an environment temperature average value, and the average value of all elements in the communication cabinet temperature monitoring matrix is called a communication cabinet temperature average value;
obtaining optimized temperature values of all the temperature elements according to the ambient temperature average value, the communication cabinet temperature average value and the optimizing factors of all the temperature elements:
wherein,,
temperature elements representing the ith row and the ith column in the communication cabinet temperature monitoring matrix, < >>
Optimized temperature value representing temperature element of the ith row and column,/->
Optimization factor of temperature element representing the ith row and column->
Represents the mean value of the ambient temperature%>
And the average value of the temperature of the communication cabinet is shown.
Preferably, the noise removing process is performed on the communication cabinet temperature optimization monitoring matrix to obtain a noise-free temperature element set, which comprises the following specific steps:
performing cluster analysis on all elements in a communication cabinet temperature optimization matrix by adopting a DBSCAN algorithm, taking a cluster with only single data as an abnormal cluster, and taking the data in the abnormal cluster as noise data;
elements in the communication cabinet temperature optimization matrix which are not noise data are called noise-free data, and a set formed by all the noise-free data is called a noise-free temperature element set.
Preferably, the obtaining the number of the binary groups of each category according to the first window of the noise-free temperature element includes the following specific steps:
for a first window of each noise-free temperature element, acquiring the average value of all data in the first window as the window average value of each noise-free temperature element, and taking a vector formed by each data in the first window and the window average value as a binary group of each data in the first window, acquiring the belonging category of each data in the first window, taking the belonging category of each data in the first window as the belonging category of the corresponding binary group of each data, acquiring the number of the binary groups of each category, and acquiring the category number of the binary groups.
Preferably, the step of obtaining the number of the reference tuples of the first window includes the specific steps of:
and (3) the vector formed by each data and right adjacent data in the first window is called a reference binary group, and the number of the reference binary groups obtained by all the data in the first window is obtained.
Preferably, the obtaining the data distribution index of the noise-free temperature element according to the number of the binary groups of each category and the number of the reference binary groups comprises the following specific steps:
counting the proportion of the number of the binary groups of each category to the number of the reference binary groups, marking the proportion as the number of the binary groups of each category, and obtaining the data distribution index of each noise-free temperature element according to the number of the binary groups of each category:
wherein,,
indicating the ith noiselessTemperature element->
The data number of the j-th class of the doublet in the first window is the ratio, +.>
The number of classes representing the two tuples in the first window of the ith noise-free temperature element, ln () represents a logarithmic function based on a natural constant,/>
Represents the i-th noiseless temperature element +.>
Is a data distribution index of (a).
Preferably, the obtaining the characteristic value of each noise-free temperature element according to the change condition of each noise-free temperature element in each direction includes the following specific steps:
the row direction of the temperature optimization matrix of the communication cabinet is marked as the x direction, and the column direction is marked as the y direction;
based on a communication cabinet temperature optimization matrix, acquiring a second derivative of each noiseless temperature element in the x direction, a second derivative of each noiseless temperature element in the y direction and a second partial derivative of each noiseless temperature element in the xy direction, and forming a data change matrix of each noiseless temperature element by the second derivative of each noiseless temperature element in the x direction, the second derivative of each noiseless temperature element in the y direction and the second partial derivative of each noiseless temperature element in the xy direction;
and acquiring the characteristic value of the data change matrix of each noiseless temperature element as the characteristic value of each noiseless temperature element.
Preferably, the obtaining the first neighborhood difference value and the second neighborhood difference value of each noiseless temperature element according to the difference condition of each noiseless temperature element and the neighborhood data includes the specific steps that:
obtaining the absolute value of the difference between each noiseless temperature element and each data in the 8 neighborhood, obtaining the maximum value of the absolute value of the difference between each noiseless temperature element and all data in the 8 neighborhood, and marking the maximum value of the absolute value of the difference between each noiseless temperature element and all data in the 8 neighborhood as the first neighborhood difference of each noiseless temperature element, and obtaining the minimum value of the absolute value of the difference between each noiseless temperature element and all data in the 8 neighborhood as the second neighborhood difference of each noiseless temperature element.
Preferably, the obtaining the data change index of each noiseless temperature element according to the characteristic value of each noiseless temperature element, the first neighborhood difference value and the second neighborhood difference value includes the specific steps of:
the calculation formula of the data change index of the ith noiseless temperature element is as follows:
wherein,,
、/>
characteristic values of the i-th noise-free temperature element, respectively,>
、/>
the first neighborhood difference and the second neighborhood difference, respectively, representing the ith noiseless temperature element, exp () represents an exponential function based on a natural constant, +.>
Data change index indicating the i-th noise-free temperature element.
The embodiment of the invention has at least the following beneficial effects: the method comprises the steps of acquiring a communication cabinet temperature monitoring matrix and an environment temperature data sequence, and taking the influence of the environment temperature on the communication cabinet temperature data into consideration, so that the environment temperature data in the environment temperature sequence is utilized to optimize each temperature data in the communication cabinet temperature monitoring matrix to obtain the communication cabinet temperature optimization monitoring matrix. Because the sensor can generate noise data in the acquisition process, the temperature data in the communication cabinet temperature optimization monitoring matrix is subjected to noise analysis to obtain a noise-free temperature element set, and each temperature data in the noise-free temperature set eliminates the interference of external factors and only retains the abnormal condition caused by the abnormal temperature of the communication cabinet, so that a basis is provided for the subsequent abnormal analysis;
the abnormal condition of the communication cabinet is mainly represented by temperature abnormal data, so that the abnormal data is required to be acquired firstly, the data distribution disorder and the large data fluctuation of the data in the local area of the abnormal data are considered, the data distribution index of each noiseless temperature element is obtained according to the distribution disorder condition of the local area of each noiseless temperature element in the noiseless temperature set, the data change index of each noiseless temperature element is obtained according to the change condition of each noiseless temperature element in each direction, the abnormal degree of each noiseless temperature element is obtained according to the data distribution index and the data change index of each noiseless temperature element, the abnormal data is obtained according to the abnormal degree of each noiseless temperature element, the abnormal conclusion of the communication cabinet is obtained according to the abnormal degree of the abnormal data, and the abnormal conclusion of the communication cabinet is obtained in the mode.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a remote monitoring system for temperature abnormality of a communication cabinet.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description refers to a specific implementation, structure, characteristics and effects of a remote monitoring system for temperature abnormality of a communication cabinet according to the invention, which is provided by the invention, with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the remote monitoring system for temperature abnormality of a communication cabinet.
The invention provides a remote monitoring system for temperature abnormality of a communication cabinet, which comprises a data acquisition module, a data processing module and an early warning module; wherein the data acquisition module: acquiring a communication cabinet temperature monitoring matrix and an environmental temperature data sequence; and a data processing module: analyzing the temperature monitoring matrix of the communication cabinet and the environmental temperature data sequence to obtain an abnormal conclusion of the communication cabinet; and the early warning module is used for: and carrying out early warning treatment according to the abnormal conclusion of the communication cabinet.
Specifically, the remote monitoring system for temperature abnormality of a communication cabinet of the present embodiment provides a remote monitoring method for temperature abnormality of a communication cabinet, referring to fig. 1, the method includes the following steps:
and S001, acquiring a plurality of communication cabinet temperature data sequences and an environment temperature data sequence by using a temperature sensor, and constructing a communication cabinet temperature monitoring matrix by using the plurality of communication cabinet temperature data sequences.
The communication cabinet comprises a plurality of different equipment components, and mainly comprises an equipment cabinet air conditioner, a fan component, an oil engine interface module, a switching power supply, a storage battery pack, communication transmission equipment, an intelligent power distribution unit, a lead-acid storage battery pack, a rectifying module, a lighting device, an equipment cabinet support and other infrastructures. Therefore, the embodiment realizes the remote monitoring of the abnormal temperature of the communication cabinet by analyzing the time sequence data of the temperature parameter in the working process of the communication cabinet.
1. And (3) collecting a communication cabinet temperature data sequence:
temperature sensors are installed at M positions of the communication cabinet, temperature sensor types, models, numbers and position deployment operators of the temperature sensors can be set according to actual conditions, temperature data of the temperature sensors are collected once every interval u, N times of temperature data are collected for each temperature sensor, each temperature sensor can collect and obtain a N-dimensional communication cabinet temperature data sequence, M temperature sensors obtain M communication cabinet temperature data sequences, M in this embodiment is 4, u is 1s, N is 600, and other embodiments are set according to actual conditions.
2. Constructing a communication cabinet temperature monitoring matrix:
taking each communication cabinet temperature sequence as each row of a communication cabinet temperature monitoring matrix, forming a M-N communication cabinet temperature monitoring matrix by M communication cabinet temperature data sequences, and marking as
。
3. Collecting an environmental temperature data sequence:
the temperature sensors are arranged in the surrounding environment where the communication cabinet is located, the type, model and quantity of the temperature sensors and the position deployment implementation operators of the temperature sensors can be set according to actual conditions, the temperature data of the temperature sensors are acquired once every interval u time, N times of temperature data are acquired altogether, an N-dimensional environment temperature data sequence is obtained, and the N-dimensional environment temperature data sequence is recorded as
。
Step S002, optimizing each temperature element in the communication cabinet temperature monitoring matrix according to the environmental temperature data sequence to obtain a communication cabinet temperature optimizing monitoring matrix, and eliminating noise elements in the communication cabinet temperature optimizing monitoring matrix to obtain a noise-free temperature element set.
The temperature is a key factor affecting the abnormality of the communication cabinet, so that the temperature data in the communication cabinet needs to be analyzed, the abnormal data in the temperature data can reflect the abnormal condition of the communication cabinet, the abnormal data in the temperature data needs to be analyzed, and the interference of the environmental temperature, the noise acquired by the sensor and other factors needs to be eliminated before the abnormal analysis of the temperature data is performed.
1. Optimizing each temperature element in the communication cabinet temperature monitoring matrix to obtain a communication cabinet temperature optimizing monitoring matrix:
when the temperature sensor on the communication cabinet collects temperature data of the communication cabinet, the temperature sensor is affected by the ambient temperature, so that the collected temperature of the communication cabinet is inaccurate and cannot accurately represent the comprehensive temperature condition of equipment in the communication cabinet, therefore, the temperature elements in the temperature monitoring matrix of the communication cabinet are required to be optimized by using an ambient temperature data sequence to obtain a temperature optimization monitoring matrix of the communication cabinet, the comprehensive temperature condition of the equipment in the communication cabinet is accurately represented, and the optimization processing of the temperature elements in the temperature monitoring matrix of the communication cabinet is carried out as follows:
computing an ambient temperature data sequence
The mean value of all elements in (1) is recorded as the ambient temperature mean value +.>
The average value of all elements in the temperature monitoring matrix of the communication cabinet is obtained and marked as the average value of the temperature of the communication cabinet +.>
。
According to the ambient temperature average value and the communication cabinet temperature average value, optimizing each temperature element in the communication cabinet temperature monitoring matrix, wherein an optimizing model is as follows:
wherein,,
matrix for monitoring temperature of communication cabinetTemperature element of the (u) th row and (v) th column->
Optimized temperature value representing temperature element of the ith row and column,/->
Optimization factor of temperature element representing the ith row and column->
Represents the mean value of the ambient temperature%>
Indicating the average value of the temperature of the communication cabinet>
The environment temperature at the v-th moment in the environment temperature sequence is represented, k represents a regulating coefficient for controlling temperature data regulation, k is 0.3 in the embodiment, and other embodiments can be implemented according to actual settings, when->
The higher environmental temperature can lead to higher temperature in the collected communication cabinet, so that the value of each temperature element in the communication cabinet needs to be regulated down by using an optimization factor, the real temperature condition in the communication cabinet can be truly reflected, and the temperature of the communication cabinet is higher than the temperature of the communication cabinet>
The lower ambient temperature is indicated to result in lower temperature in the collected communication cabinet, so that the values of all temperature elements in the communication cabinet are required to be adjusted to be high by using an optimization factor, and the real temperature condition in the communication cabinet can be truly reflected>
Representing absolute value symbols.
Replacing the original temperature element by the optimized temperature value of each temperature element in the communication cabinet temperature monitoring matrix to obtain the communication cabinet temperature optimizing monitoring matrix
At the moment, all temperature elements in the communication cabinet temperature optimization monitoring matrix exclude interference of ambient temperature, and the real temperature condition in the communication cabinet can be truly reflected.
2. Removing noise data in the communication cabinet temperature optimization matrix to obtain a noise-free temperature element set:
noise interference can occur in the data acquisition process of the sensor, so that noise data exists in the acquired data, the noise data can interfere with temperature anomaly analysis, temperature anomalies caused by noise influence cannot be identified, or temperature anomalies caused by real temperature change of the communication cabinet can not be identified, and noise data in the data need to be removed to obtain a noise-free temperature element set, and the specific process is as follows:
the DBSCAN algorithm is adopted to perform cluster analysis on all elements in the communication cabinet temperature optimization matrix to obtain a plurality of cluster clusters, each cluster corresponds to one category, noise data has isolated characteristics, and abnormal data mostly show time continuity, so that the embodiment takes the cluster with single data as the abnormal cluster, and takes the data in the abnormal cluster as noise data. And removing all noise data from all elements of the communication cabinet temperature optimization matrix, and calling a set formed by the rest noise-free data as a noise-free temperature element set.
The method comprises the steps of obtaining a noise-free temperature element set, when the noise-free temperature element set is obtained, taking the condition that collected communication cabinet temperature data are interfered by ambient temperature into consideration, optimizing the communication cabinet temperature data by using the ambient temperature data to obtain a communication cabinet temperature optimization matrix, and simultaneously taking the condition that noise data exist in the communication cabinet temperature optimization matrix into consideration, obtaining the noise data in the communication cabinet temperature optimization matrix through cluster analysis, and removing the noise data to obtain the noise-free temperature element set.
Step S003, calculating data distribution indexes and data change indexes of each noiseless temperature element in the noiseless temperature element set, combining the local data distribution indexes and the change indexes to obtain the abnormal degree of each noiseless temperature element, and obtaining an abnormal data set according to the abnormal degree of each noiseless temperature element.
The interference of external factors on the abnormal analysis of the temperature of the communication cabinet is eliminated in the steps to obtain a noise-free temperature element set, and the abnormal analysis of each noise-free temperature element in the noise-free temperature element set is needed to obtain an abnormal data set, and the specific process is as follows:
for ease of description, each data in the set of noise-free temperature elements is referred to as a noise-free temperature element, and the i-th noise-free temperature element is referred to as
。
1. Determining data distribution indexes of each noiseless temperature element:
when the data is abnormal, the data distribution in the local area where the data is located is disordered, so that the data distribution index of each noiseless temperature element is obtained by analyzing the distribution condition of the local area of each noiseless temperature element, and the method specifically comprises the following steps:
and traversing each noiseless temperature element by utilizing a window of 5*5 for the communication cabinet temperature optimization matrix to obtain a first window of each noiseless temperature element.
For the ith noiseless temperature element
Acquiring the average value of all data in the first window and marking the average value as the window average value of each noise-free temperature element, and referring to a vector formed by each data in the first window and the window average value as a binary group of each data in the first window, wherein the class of each data in the first window is obtained in the step S002, and the class of each data in the first window is the class of the binary group corresponding to the data; the vector formed by each data and right adjacent data is called as a reference binary group, and when the data does not have right adjacent data in the first window, the average value of all data of the data in the first window is taken as the right adjacent data of the data, and the number of the reference binary groups of all the data in the first window is acquired; counting the number of the binary groups in the same categoryTaking the proportion of the number of the binary groups into consideration, marking the proportion of the number of the data of each binary group as the number of the binary groups, and marking the proportion of the number of the data of the j-th binary group as +.>
The method comprises the steps of carrying out a first treatment on the surface of the Obtaining data distribution indexes of each noiseless temperature element according to the data number proportion of each binary group:
wherein,,
represents the i-th noiseless temperature element +.>
The data number of the j-th class of the doublet in the first window is the ratio, +.>
Representing the number of classes of the two-tuple in the first window of the ith noise-free temperature element, ln () represents a logarithmic function based on a natural constant, +.>
Represents the i-th noiseless temperature element +.>
The larger the value, the more chaotic the data distribution of the local area around the i-th noiseless temperature element, and thus the higher the possibility that the i-th noiseless temperature element is abnormal data.
2. Determining the data change index of each noiseless temperature element:
when the data is abnormal, the fluctuation of the local area where the data is located is larger, so that the data change index of each noiseless temperature element is obtained by analyzing the fluctuation condition of each noiseless temperature element in different directions, and the method comprises the following specific steps:
(1) Acquiring characteristic values of a change matrix of each noiseless temperature element:
the row direction of the communication cabinet temperature optimization matrix is denoted as x direction, and the column direction is denoted as y direction.
Based on a communication cabinet temperature optimization matrix, obtaining a second derivative of an ith noiseless temperature element in the x direction
Second derivative in y-direction +.>
And second partial derivative in xy direction +.>
The variation condition of the ith noiseless temperature element in each direction can be reflected through the second derivatives in the x and y directions and the second partial derivatives in the xy directions; the second derivative in the x direction, the second derivative in the y direction and the second partial derivative in the xy direction of each noiseless temperature element form a data change matrix +.>
。
Acquiring eigenvalues of a data change matrix of an ith noiseless temperature element
、/>
As the characteristic value of the ith noiseless temperature element, the magnitude of the characteristic value reflects the intensity of the change of the data in the direction of the characteristic vector corresponding to the characteristic value and is used for representing the fluctuation condition of the data in the direction of the characteristic vector;
(2) Acquiring a first neighborhood difference value and a second neighborhood difference value of each noiseless temperature element:
acquiring the absolute value of the difference between the ith noiseless temperature element and each data in the 8 neighborhood, acquiring the maximum value of the absolute value of the difference between the ith noiseless temperature element and all data in the 8 neighborhood, and marking the maximum value as the first neighborhood difference of the ith noiseless temperature element
Obtaining the minimum value of the absolute value of the difference between the ith noiseless temperature element and all data in the 8 neighborhoods, and marking the minimum value as the second neighborhood difference of the ith noiseless temperature element +.>
。
(3) Acquiring data change indexes of each noiseless temperature element:
wherein,,
、/>
characteristic values of the data change matrix respectively representing the ith noise-free temperature element, a larger value indicating a more drastic change of the data in the direction of the characteristic vector corresponding to the value, +.>
、/>
Respectively representing a first neighborhood difference value and a second neighborhood difference value of the ith noiseless temperature element, wherein the first neighborhood difference value reflects the maximum difference value of the ith noiseless temperature element and neighborhood data, the second neighborhood difference value reflects the minimum difference value of the ith noiseless temperature element and the neighborhood data, and the second neighborhood difference value reflects the minimum difference value of the ith noiseless temperature element and the neighborhood data>
Reflects the difference change condition of the ith noiseless temperature element and the neighborhood data, and the larger the value is, the larger the difference change condition of the data and the neighborhood data is, so that the more severe the data change is in the local area where the data is located, the more the data change is>
Data change index ex representing the i-th noiseless temperature elementp () represents an exponential function based on a natural constant.
3. Calculating the abnormality degree of each noiseless temperature element:
wherein,,
a data distribution index indicating an i-th noiseless temperature element, the larger the value indicating that the data distribution in the local area of the i-th noiseless temperature data is more disordered, and thus the greater the degree of abnormality of the i-th noiseless temperature element, the more disordered the value is>
A data change index indicating an i-th noiseless temperature element, the larger the value indicating that the data change in the i-th noiseless temperature data partial area is more intense, and thus the greater the degree of abnormality of the i-th noiseless temperature data is,/>
Indicating the degree of abnormality of the i-th noise-free temperature element.
Normalizing the abnormal degree of each noiseless temperature element by using a softmax normalization method to obtain the normalized abnormal degree of each noiseless temperature element, and for convenience of description, the normalized abnormal degree of each noiseless temperature element is called as the abnormal degree of each noiseless temperature element.
4. Screening abnormal data:
the degree of abnormality is larger than a preset threshold value of degree of abnormality
Is divided into abnormal data, and a set of all abnormal data is called an abnormal data set, and in this embodiment, an abnormality degree threshold value is preset +.>
Take 0.45.
The abnormal data is obtained by analyzing the abnormal degree of each noiseless temperature element, obtaining the data distribution index of each noiseless temperature element by considering the disordered data distribution condition in the local area of each noiseless temperature element and obtaining the data change index of each noiseless temperature element by considering the data fluctuation condition in the local area of each noiseless temperature element and combining the data change index and the data distribution index.
And S004, obtaining a communication cabinet temperature abnormality index according to the abnormality degree of each abnormal data in the abnormal data set, and obtaining an abnormality conclusion of the communication cabinet according to the communication cabinet temperature abnormality index.
And taking the sum of the abnormality degrees of all data in the abnormal data set as an abnormality index of the communication cabinet, and normalizing the abnormality index of the communication cabinet by using a softmax normalization method to obtain the normalized abnormality index of the communication cabinet. When the normalized abnormal index of the communication cabinet is greater than a preset abnormal index threshold value
When the communication cabinet is judged to be abnormal, the early warning system sends out early warning alarm, and related personnel perform corresponding temperature adjustment processing on the communication cabinet after receiving the alarm so as to prevent electronic equipment inside the communication cabinet from being damaged due to the abnormal temperature; when the normalized abnormal index of the communication cabinet is smaller than the preset abnormal index threshold value, judging that the communication cabinet is not abnormal, and enabling the early warning system not to send out early warning alarm, wherein the preset abnormal index threshold value is in the embodiment>
Taking 0.65, the practitioner may in other embodiments be based on actual settings.
In summary, the embodiment of the invention provides a temperature anomaly remote monitoring system for a communication cabinet, which is used for acquiring a communication cabinet temperature monitoring matrix and an environmental temperature data sequence, and taking the influence of the environmental temperature on the communication cabinet temperature data into consideration, so that the environmental temperature data in the environmental temperature sequence is utilized to optimize each temperature data in the communication cabinet temperature monitoring matrix to acquire the communication cabinet temperature optimization monitoring matrix. Because the sensor can generate noise data in the acquisition process, the temperature data in the communication cabinet temperature optimization monitoring matrix is subjected to noise analysis to obtain a noise-free temperature element set, and each temperature data in the noise-free temperature set eliminates the interference of external factors and only retains the abnormal condition caused by the abnormal temperature of the communication cabinet, so that a basis is provided for the subsequent abnormal analysis;
the abnormal condition of the communication cabinet is mainly represented by temperature abnormal data, so that the abnormal data is required to be acquired firstly, the data distribution disorder and the large data fluctuation of the data in the local area of the abnormal data are considered, the data distribution index of each noiseless temperature element is obtained according to the distribution disorder condition of the local area of each noiseless temperature element in the noiseless temperature set, the data change index of each noiseless temperature element is obtained according to the change condition of each noiseless temperature element in each direction, the abnormal degree of each noiseless temperature element is obtained according to the data distribution index and the data change index of each noiseless temperature element, the abnormal data is obtained according to the abnormal degree of each noiseless temperature element, the abnormal conclusion of the communication cabinet is obtained according to the abnormal degree of the abnormal data, and the abnormal conclusion of the communication cabinet is obtained in the mode.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. And the foregoing description has been directed to specific embodiments of this specification. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
Claims (7)
1. A remote monitoring system for temperature anomalies in a communications cabinet, the system comprising:
the system comprises a data acquisition module, a data processing module and an early warning module;
and a data acquisition module: acquiring temperature data to obtain a communication cabinet temperature monitoring matrix and an environmental temperature data sequence;
and a data processing module: obtaining optimization factors of all temperature elements in a communication cabinet temperature monitoring matrix according to the difference condition between the temperature data at all times in an environmental temperature data sequence and all temperature data in the communication cabinet temperature monitoring matrix, carrying out optimization treatment on all temperature elements according to the optimization factors of all temperature elements to obtain optimized temperature values of all temperature elements, replacing all temperature elements in the communication cabinet temperature monitoring matrix by using the optimized temperature values to obtain a communication cabinet temperature optimization monitoring matrix, and carrying out noise elimination treatment on the communication cabinet temperature optimization monitoring matrix to obtain a noise-free temperature element set, wherein the noise-free temperature element set is composed of noise-free temperature elements;
acquiring a first window of the noiseless temperature element, acquiring the number of the tuples of each category according to the first window of the noiseless temperature element, acquiring the number of the reference tuples of the first window, and acquiring the data distribution index of the noiseless temperature element according to the number of the tuples of each category and the number of the reference tuples; obtaining characteristic values of each noiseless temperature element according to the change condition of each noiseless temperature element in each direction, obtaining a first neighborhood difference value and a second neighborhood difference value of each noiseless temperature element according to the difference condition of each noiseless temperature element and neighborhood data, and obtaining a data change index of each noiseless temperature element according to the characteristic values, the first neighborhood difference value and the second neighborhood difference value of each noiseless temperature element; obtaining the abnormality degree of each noiseless temperature element according to the data distribution index and the data change index of each noiseless temperature element; taking a noise-free temperature element with the abnormality degree larger than a preset abnormality degree threshold value as abnormal data, and obtaining an abnormality conclusion of the communication cabinet according to the abnormality degree of the abnormal data;
and the early warning module is used for: early warning treatment is carried out according to the abnormal conclusion;
the optimizing factors of the temperature elements in the communication cabinet temperature monitoring matrix are obtained according to the difference conditions between the temperature data at each moment in the environmental temperature data sequence and the temperature data in the communication cabinet temperature monitoring matrix, and the optimizing factors comprise the following specific steps:
the calculation formula of the optimization factor of the temperature element of the ith row and the ith column is as follows:
the optimizing process is carried out on each temperature element according to the optimizing factors of each temperature element to obtain the optimized temperature value of each temperature element, and the method comprises the following specific steps:
the average value of all elements in the environment temperature sequence is called an environment temperature average value, and the average value of all elements in the communication cabinet temperature monitoring matrix is called a communication cabinet temperature average value;
obtaining optimized temperature values of all the temperature elements according to the ambient temperature average value, the communication cabinet temperature average value and the optimizing factors of all the temperature elements:
noise elimination processing is carried out on the communication cabinet temperature optimization monitoring matrix to obtain a noise-free temperature element set, and the method comprises the following specific steps:
performing cluster analysis on all elements in a communication cabinet temperature optimization matrix by adopting a DBSCAN algorithm, taking a cluster with only single data as an abnormal cluster, and taking the data in the abnormal cluster as noise data;
elements in the communication cabinet temperature optimization matrix which are not noise data are called noise-free data, and a set formed by all the noise-free data is called a noise-free temperature element set.
2. The remote monitoring system for abnormal temperature of a communication cabinet according to claim 1, wherein the obtaining the number of the two-elements of each category according to the first window of the noise-free temperature element comprises the following specific steps:
for a first window of each noise-free temperature element, acquiring the average value of all data in the first window as the window average value of each noise-free temperature element, and taking a vector formed by each data in the first window and the window average value as a binary group of each data in the first window, acquiring the belonging category of each data in the first window, taking the belonging category of each data in the first window as the belonging category of the corresponding binary group of each data, acquiring the number of the binary groups of each category, and acquiring the category number of the binary groups.
3. The remote monitoring system for abnormal temperature of a communication cabinet according to claim 1, wherein the obtaining the number of the reference tuples of the first window comprises the following specific steps:
and (3) the vector formed by each data and right adjacent data in the first window is called a reference binary group, and the number of the reference binary groups obtained by all the data in the first window is obtained.
4. The remote monitoring system for abnormal temperature of a communication cabinet according to claim 1, wherein the obtaining the data distribution index of the noiseless temperature element according to the number of the two elements of each category and the number of the reference two elements comprises the following specific steps:
counting the proportion of the number of the binary groups of each category to the number of the reference binary groups, marking the proportion as the number of the binary groups of each category, and obtaining the data distribution index of each noise-free temperature element according to the number of the binary groups of each category:
5. The remote monitoring system for abnormal temperature of a communication cabinet according to claim 1, wherein the obtaining the characteristic value of each noise-free temperature element according to the change condition of each noise-free temperature element in each direction comprises the following specific steps:
the row direction of the temperature optimization matrix of the communication cabinet is marked as the x direction, and the column direction is marked as the y direction;
based on a communication cabinet temperature optimization matrix, acquiring a second derivative of each noiseless temperature element in the x direction, a second derivative of each noiseless temperature element in the y direction and a second partial derivative of each noiseless temperature element in the xy direction, and forming a data change matrix of each noiseless temperature element by the second derivative of each noiseless temperature element in the x direction, the second derivative of each noiseless temperature element in the y direction and the second partial derivative of each noiseless temperature element in the xy direction;
and acquiring the characteristic value of the data change matrix of each noiseless temperature element as the characteristic value of each noiseless temperature element.
6. The remote monitoring system for abnormal temperature of a communication cabinet according to claim 1, wherein the obtaining the first neighborhood difference value and the second neighborhood difference value of each noise-free temperature element according to the difference between each noise-free temperature element and the neighborhood data comprises the following specific steps:
obtaining the absolute value of the difference between each noiseless temperature element and each data in the 8 neighborhood, obtaining the maximum value of the absolute value of the difference between each noiseless temperature element and all data in the 8 neighborhood, and marking the maximum value of the absolute value of the difference between each noiseless temperature element and all data in the 8 neighborhood as the first neighborhood difference of each noiseless temperature element, and obtaining the minimum value of the absolute value of the difference between each noiseless temperature element and all data in the 8 neighborhood as the second neighborhood difference of each noiseless temperature element.
7. The remote monitoring system for abnormal temperature of a communication cabinet according to claim 1, wherein the obtaining the data change index of each noise-free temperature element according to the characteristic value of each noise-free temperature element, the first neighborhood difference value and the second neighborhood difference value comprises the following specific steps:
the calculation formula of the data change index of the ith noiseless temperature element is as follows:
wherein,,
、/>
characteristic values of the i-th noise-free temperature element, respectively,>
、/>
the first neighborhood difference and the second neighborhood difference, respectively, representing the ith noiseless temperature element, exp () represents an exponential function based on a natural constant, +.>
Data change index indicating the i-th noise-free temperature element.
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