CN117791869A - Data online monitoring method and system based on intelligent power distribution cabinet - Google Patents
Data online monitoring method and system based on intelligent power distribution cabinet Download PDFInfo
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Abstract
The invention belongs to the technical field of power distribution cabinet supervision, and particularly relates to a data online monitoring method and system based on an intelligent power distribution cabinet, wherein the data online monitoring system comprises an online monitoring platform, an electric power parameter detection module, a parameter self-adjusting module, an intra-cabinet risk comprehensive detection module, a component displacement detection module and a background management and control end; according to the intelligent power distribution cabinet, the electric power parameter detection module is used for monitoring and analyzing the electric power parameter of the intelligent power distribution cabinet, timely and accurately feeding back the electric power parameter expression condition of the intelligent power distribution cabinet, automatic adjustment is carried out on the risk storage parameter and the adjustment efficiency is evaluated when the electric power parameter abnormal signal is generated, safe and stable operation of the intelligent power distribution cabinet is effectively ensured, the internal risk condition of the intelligent power distribution cabinet is detected and analyzed, timely and accurately feeding back the risk degree in the intelligent power distribution cabinet, and the displacement condition of corresponding parts in the power distribution cabinet is analyzed when the low risk signal in the intelligent power distribution cabinet is generated, so that the operation risk of the intelligent power distribution cabinet is further reduced.
Description
Technical Field
The invention relates to the technical field of power distribution cabinet supervision, in particular to a data online monitoring method and system based on an intelligent power distribution cabinet.
Background
The power distribution cabinet is equipment for distributing and managing electric energy, is final-stage equipment of a power distribution system, is divided into a power distribution cabinet, a lighting power distribution cabinet, a metering cabinet and the like, and is mainly used for distributing the electric energy of a certain circuit of the power distribution equipment at the upper stage to nearby loads, the power distribution cabinet needs to provide protection, monitoring and control for the loads, and along with the continuous development of the power system, the power distribution cabinet is widely applied in the power system;
in the operation process of the intelligent power distribution cabinet, the operation data of the intelligent power distribution cabinet are difficult to monitor in real time and timely and accurately feed back the power parameter expression condition and the risk condition in the cabinet, and the displacement risk of the internal parts cannot be reasonably judged when the inside of the intelligent power distribution cabinet is in a low-risk state, so that the safety and stability operation of the intelligent power distribution cabinet are not facilitated to be ensured, and the stability and the reliability of a power system are influenced;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a data online monitoring method and system based on an intelligent power distribution cabinet, which solve the problems that in the prior art, the operation data of the intelligent power distribution cabinet is difficult to monitor in real time, the power parameter performance condition and the risk condition in the cabinet are fed back timely and accurately, and the risk of displacement of components in the intelligent power distribution cabinet cannot be judged reasonably when the inside of the intelligent power distribution cabinet is in a low risk state, so that the safety and stability of the intelligent power distribution cabinet are not guaranteed.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the data online monitoring system based on the intelligent power distribution cabinet comprises an online monitoring platform, an electric power parameter detection module, a parameter self-adjustment module, an intra-cabinet risk comprehensive detection module, a component displacement detection module and a background management and control end; the power parameter detection module monitors the power parameters of the intelligent power distribution cabinet and judges whether the power parameters exist or not, a power parameter normal signal or a power parameter abnormal signal is generated according to the power parameters, and the power parameter abnormal signal and the power parameters are sent to the parameter self-adjusting module and the background management and control end through the online monitoring platform; when the parameter self-adjusting module receives the power parameter abnormal signal, the risk saving parameter is automatically adjusted to meet the corresponding requirement;
the in-cabinet risk comprehensive detection module detects and analyzes the internal risk condition of the intelligent power distribution cabinet, generates an in-cabinet high risk signal or an in-cabinet low risk signal through analysis, sends the in-cabinet high risk signal to a background management and control end through an on-line monitoring platform, and sends the in-cabinet low risk signal to the component displacement detection module through the on-line monitoring platform; the component displacement detection module analyzes the displacement condition of the corresponding component in the power distribution cabinet, marks the corresponding component as a high-displacement component or a low-displacement component through analysis, generates a displacement detection unqualified signal or a displacement detection qualified signal, and sends the displacement detection unqualified signal to a background management and control end through the online monitoring platform; and the background control receives the abnormal signal of the power parameter, and sends out corresponding early warning when the high risk signal or the displacement detection disqualification signal in the cabinet.
Further, the specific operation process of the power parameter detection module includes:
acquiring power parameters required to be monitored of the intelligent power distribution cabinet, and marking the corresponding power parameters as i, wherein i is a natural number larger than 1; acquiring real-time parameter data of the power parameter i, comparing the real-time parameter data with preset real-time parameter data requirements, and marking the corresponding power parameter i as a risk parameter if the real-time parameter data does not meet the corresponding preset real-time parameter data requirements; if the existence parameter does not exist, generating a power parameter normal signal; if the existence of the risk parameter exists, generating a power parameter abnormality signal.
Further, when generating the power parameter abnormal signal, the power parameter detection module marks the deviation value of the real-time parameter data corresponding to the risk parameter as a power parameter deviation value compared with the deviation value required by the corresponding preset real-time parameter data, the power parameter deviation value is compared with the corresponding preset power parameter deviation threshold value, and if the power parameter deviation value exceeds the corresponding preset power parameter deviation threshold value, the corresponding risk parameter is marked as a risk parameter;
marking the number of the risk parameters in the intelligent power distribution cabinet as a risk parameter value, and marking the ratio of the number of the high risk parameters to the risk parameter deviation value as a high risk parameter value; carrying out weighted summation on the high risk parameter detection value and the risk parameter detection value to obtain a power parameter correction value, presetting a plurality of groups of preset power parameter correction value ranges, wherein each group of preset power parameter correction value ranges corresponds to a group of preset adjustment time periods, and comparing the power parameter correction value with all the preset power parameter correction value ranges one by one to determine the preset adjustment time periods matched with the power parameter correction value ranges and marking the preset adjustment time periods as set time periods;
when the parameter self-adjusting module adjusts the risk storage parameters of the intelligent power distribution cabinet, the moment that the parameter self-adjusting module receives the power parameter abnormal signal is obtained and is used as a time starting point to time, so that the real-time adjusting time length of the parameter self-adjusting module is collected, when the real-time adjusting time length reaches the set time length and the parameter adjustment of the intelligent power distribution cabinet is not completed, the adjustment condition of the parameter self-adjusting module is judged to be poor, a power parameter adjustment early warning signal is generated, the power parameter adjustment early warning signal is sent to a background management and control end through an online monitoring platform, and the background management and control end sends corresponding early warning when receiving the power parameter adjustment early warning signal.
Further, the specific operation process of the risk comprehensive inspection module in the cabinet comprises the following steps:
acquiring smoke concentration data of a plurality of detection points in an intelligent power distribution cabinet, marking the smoke concentration data with the largest numerical value as a smoke detection value in the cabinet, comparing the smoke detection value in the cabinet with a preset smoke detection threshold value in the cabinet, and generating a high risk signal in the cabinet if the smoke detection value in the cabinet exceeds the preset smoke detection threshold value in the cabinet;
if the in-cabinet risk analysis value does not exceed the preset in-cabinet risk analysis threshold, the in-cabinet risk analysis value of the intelligent power distribution cabinet is obtained through in-cabinet risk pipe analysis, the in-cabinet risk analysis value is compared with the preset in-cabinet risk analysis threshold in a numerical mode, and if the in-cabinet risk analysis value exceeds the preset in-cabinet risk analysis threshold, an in-cabinet high risk signal is generated; and if the risk analysis value in the cabinet does not exceed the preset risk analysis threshold value in the cabinet, generating a low risk signal in the cabinet.
Further, the concrete analysis process of the in-cabinet risk tube analysis is as follows:
acquiring real-time temperature and real-time humidity of corresponding detection points in the intelligent power distribution cabinet, performing difference calculation on the real-time temperature compared with a median value corresponding to a preset proper temperature range, and taking an absolute value to obtain a temperature value of the points in the cabinet, and acquiring the humidity value of the points in the cabinet in a similar way; respectively comparing the temperature value of the point in the cabinet with the humidity value of the point in the cabinet with a preset temperature threshold value of the point in the cabinet and a preset humidity threshold value of the point in the cabinet, and marking the corresponding detection point as a risk analysis point if the temperature value of the point in the cabinet or the humidity value of the point in the cabinet exceeds the corresponding preset threshold value;
the noise data and the vibration data generated by the intelligent power distribution cabinet during operation are collected and marked as an in-cabinet operation noise value and an in-cabinet operation vibration value respectively, and the number of dangerous analysis points in the intelligent power distribution cabinet is marked as an in-cabinet point measurement value; performing numerical calculation on the in-cabinet noise value, the in-cabinet vibration value and the in-cabinet point measurement value to obtain an in-cabinet risk table value, performing numerical comparison on the in-cabinet risk table value and a preset in-cabinet risk table threshold value, and marking the corresponding in-cabinet risk table value as an in-cabinet risk condition value if the in-cabinet risk table value exceeds the preset in-cabinet risk table threshold value;
acquiring the number of the risk condition values in the cabinet in the detection period, calculating the ratio of the number of the risk condition values to the number of the risk table values in the cabinet to obtain an abnormal value of the risk in the cabinet, summing all the risk table values in the detection period, calculating and taking an average value to obtain a sign value of the risk in the cabinet; and carrying out numerical calculation on the risk abnormal value and the risk sign value to obtain a risk analysis value.
Further, the specific operation process of the component displacement detection module comprises:
acquiring a component needing to be subjected to displacement monitoring in the intelligent power distribution cabinet, acquiring the actual displacement of a corresponding component, comparing the actual displacement with a corresponding preset actual displacement threshold value, and marking the corresponding component as a high-displacement component if the actual displacement exceeds the preset actual displacement threshold value; if the intelligent power distribution cabinet has a high-displacement component, generating a displacement detection failure signal;
if the high displacement component does not exist, acquiring a displacement acceleration value of the corresponding component in unit time, and carrying out numerical calculation on the actual displacement quantity and the displacement acceleration value of the corresponding component to obtain a displacement analysis value; comparing the displacement analysis value with a corresponding preset displacement analysis threshold value, and marking the corresponding part as a displacement risk part if the displacement analysis value exceeds the preset displacement analysis threshold value;
marking the number of the displacement risk components as component displacement risk measurement values, comparing the component displacement risk measurement values with preset component displacement risk measurement thresholds, and generating a displacement detection failure signal if the component displacement risk measurement values exceed the preset component displacement risk measurement thresholds; and if the component displacement risk measurement value does not exceed the preset component displacement risk measurement threshold value, generating a displacement detection qualified signal.
Further, the online monitoring platform is in communication connection with the cabinet body supervision and grading module, the cabinet body supervision and grading module collects the production date of the intelligent power distribution cabinet, marks the interval duration between the production date and the current date as a cabinet body production time detection value, and collects the total duration of the intelligent power distribution cabinet running in the interval duration between the production date and the current date and marks the total duration as the cabinet body running time detection value; respectively comparing the detection value during the production of the cabinet body and the detection value during the running of the cabinet body with a preset detection threshold value during the production of the cabinet body and a preset detection threshold value during the running of the cabinet body, and generating a strong supervision signal of the intelligent power distribution cabinet if the detection value during the production of the cabinet body or the detection value during the running of the cabinet body exceeds the corresponding preset threshold value;
if the detection value during cabinet production and the detection value during cabinet operation do not exceed the corresponding preset threshold values, a supervision period is set, and the number of times of generating power parameter abnormal signals, the number of times of generating power parameter adjustment early warning signals, the number of times of generating high risk signals in the cabinet and the number of times of generating displacement detection unqualified signals in the intelligent power distribution cabinet in the supervision period are collected and marked as a power parameter abnormal analysis value, a power parameter frequency analysis value, a cabinet risk frequency analysis value and a displacement detection frequency analysis value respectively; performing numerical calculation on the electric power parameter frequency analysis value, the in-cabinet risk frequency analysis value and the displacement detection frequency analysis value to obtain a cabinet supervision evaluation value, performing numerical comparison on the cabinet supervision evaluation value and a preset cabinet supervision evaluation threshold, and generating a strong supervision signal of the intelligent power distribution cabinet if the cabinet supervision evaluation value exceeds the preset cabinet supervision evaluation threshold; if the cabinet supervision evaluation value does not exceed the preset cabinet supervision evaluation threshold, generating a weak supervision signal of the intelligent power distribution cabinet; and the strong supervision signals or the weak supervision signals of the intelligent power distribution cabinet are sent to the background management and control end through the on-line monitoring platform.
Furthermore, the invention also provides a data on-line monitoring method based on the intelligent power distribution cabinet, which comprises the following steps:
step one, monitoring power parameters of an intelligent power distribution cabinet and judging whether the power parameters exist or not, and generating a power parameter normal signal or a power parameter abnormal signal according to the power parameters;
step two, when generating an abnormal signal of the power parameter, the parameter self-adjusting module automatically adjusts the risk parameter so as to meet the corresponding requirement;
detecting and analyzing the internal risk condition of the intelligent power distribution cabinet, and generating a high risk signal in the cabinet or a low risk signal in the cabinet through analysis;
and fourthly, when the low risk signal in the power distribution cabinet is generated, analyzing the displacement condition of the corresponding component in the power distribution cabinet, and generating a displacement detection unqualified signal or a displacement detection qualified signal through analysis.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the intelligent power distribution cabinet power parameter monitoring system, the power parameter detection module is used for monitoring the power parameter of the intelligent power distribution cabinet and judging whether the power parameter exists, so that a power parameter normal signal or a power parameter abnormal signal is generated, the power parameter performance condition of the intelligent power distribution cabinet can be timely and accurately fed back, the power parameter is automatically adjusted by the parameter self-adjusting module when the power parameter abnormal signal is generated so as to meet corresponding requirements, and the adjustment efficiency condition of the parameter self-adjusting module is detected and evaluated by the power parameter detection module so as to judge whether the power parameter adjustment early warning signal is generated or not, so that the safe and stable operation of the intelligent power distribution cabinet is effectively ensured;
2. according to the intelligent power distribution cabinet monitoring system, the internal risk condition of the intelligent power distribution cabinet is detected and analyzed through the in-cabinet risk comprehensive detection module, the in-cabinet risk degree of the intelligent power distribution cabinet can be timely and accurately fed back through analysis to generate the in-cabinet high risk signal or the in-cabinet low risk signal, the displacement condition of the corresponding part in the power distribution cabinet is analyzed through the part displacement detection module when the in-cabinet low risk signal is generated, the corresponding part is marked as the high displacement part or the low displacement part through analysis, and the displacement detection qualified signal or the displacement detection unqualified signal is generated, so that the operation risk of the intelligent power distribution cabinet is further reduced, and the supervision difficulty of the intelligent power distribution cabinet is reduced.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a system block diagram of a first embodiment of the present invention;
FIG. 2 is a system block diagram of a second embodiment of the present invention;
fig. 3 is a flow chart of a method according to a third embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: as shown in fig. 1, the online data monitoring system based on the intelligent power distribution cabinet provided by the invention comprises an online monitoring platform, a power parameter detection module, a parameter self-adjustment module, an in-cabinet risk comprehensive detection module, a component displacement detection module and a background management and control end, wherein the online monitoring platform is in communication connection with the power parameter detection module, the parameter self-adjustment module, the in-cabinet risk comprehensive detection module, the component displacement detection module and the background management and control end;
the power parameter detection module monitors the power parameters of the intelligent power distribution cabinet and judges whether the power parameters exist or not, a power parameter normal signal or a power parameter abnormal signal is generated according to the power parameters, the power parameter abnormal signal and the power parameters are sent to the parameter self-adjusting module and the background management and control end through the online monitoring platform, and corresponding early warning is sent when the background management and control end receives the power parameter abnormal signal, so that a manager can master the power parameter representation condition of the intelligent power distribution cabinet in detail, the manager can conveniently carry out manual remote control of the intelligent power distribution cabinet, and safe and stable operation of the intelligent power distribution cabinet is ensured; the specific operation process of the power parameter detection module is as follows:
acquiring electric power parameters (such as current, voltage and the like) required to be monitored of the intelligent power distribution cabinet, marking the corresponding electric power parameters as i, wherein i is a natural number larger than 1; the method comprises the steps of collecting real-time parameter data of the power parameter i, comparing the real-time parameter data with preset real-time parameter data requirements, and marking the corresponding power parameter i as an risk-saving parameter if the real-time parameter data do not meet the corresponding preset real-time parameter data requirements, wherein the deviation exists in the corresponding power parameter i; if the existence parameters do not exist, the intelligent power distribution cabinet is indicated that the performance of each electric power parameter is good when in operation, and then an electric power parameter normal signal is generated; if the existence of the risk parameters indicates that each electric power performance condition is poor when the intelligent power distribution cabinet operates, generating an electric power parameter abnormal signal.
When the parameter self-adjusting module receives the power parameter abnormal signal, the risk saving parameter is automatically adjusted to meet the corresponding requirement, so that the automatic adjustment of the operation parameter of the intelligent power distribution cabinet is realized, and the operation risk is reduced; when generating an abnormal signal of the power parameter, the power parameter detection module marks the deviation value of the real-time parameter data corresponding to the risk parameter as a power parameter deviation value compared with the deviation value required by the corresponding preset real-time parameter data, the power parameter deviation value is compared with a corresponding preset power parameter deviation threshold value, if the power parameter deviation value exceeds the corresponding preset power parameter deviation threshold value, the power parameter detection module indicates that the corresponding power parameter i has larger deviation and the safety risk is larger, and marks the corresponding risk parameter as a high risk parameter;
marking the number of the risk parameters in the intelligent power distribution cabinet as a risk parameter value, and marking the ratio of the number of the high risk parameters to the risk parameter deviation value as a high risk parameter value; weighting and summing the high risk parameter value XR and the risk parameter value XW through a formula XF=b1 xXR+b2 xW to obtain an electric power parameter analysis value XF, wherein b1 and b2 are preset weight coefficients, and b1 is more than b2 is more than 0; and, the larger the value of the power parameter calibration value XF, the greater the difficulty of adjusting the parameter, and the longer the required adjustment time;
a plurality of groups of preset power parameter calibration value ranges are preset, each group of preset power parameter calibration value ranges corresponds to a group of preset adjustment time periods respectively, the power parameter calibration values are compared with all the preset power parameter calibration value ranges one by one, so that the preset adjustment time periods matched with the power parameter calibration values are determined and marked as the set time periods; it should be noted that, the larger the value of the preset power parameter calibration value range is, the larger the value of the preset adjustment time length matched with the value is;
when the parameter self-adjusting module adjusts the risk storage parameters of the intelligent power distribution cabinet, the moment that the parameter self-adjusting module receives the power parameter abnormal signal is obtained and is used as a time starting point to time, so that the real-time adjusting time length of the parameter self-adjusting module is collected, when the real-time adjusting time length reaches the set time length and the parameter of the intelligent power distribution cabinet is not completely adjusted, the adjusting condition of the parameter self-adjusting module is judged to be poor, a power parameter adjusting early warning signal is generated, the power parameter adjusting early warning signal is sent to a background management and control end through an online monitoring platform, corresponding early warning is sent when the background management and control end receives the power parameter adjusting early warning signal, and a manager timely performs corresponding manual adjustment according to needs when receiving the corresponding early warning, so that the normal of each power parameter of the intelligent power distribution cabinet is ensured, and the safe and stable operation of the intelligent power distribution cabinet is further ensured.
The in-cabinet risk comprehensive detection module detects and analyzes the internal risk condition of the intelligent power distribution cabinet, generates an in-cabinet high risk signal or an in-cabinet low risk signal through analysis, and sends the in-cabinet high risk signal to the background management and control end through the on-line monitoring platform, the background management and control end sends out corresponding early warning when receiving the in-cabinet high risk signal, and when receiving the corresponding early warning, a manager timely performs cause investigation and tracing, and makes corresponding targeted improvement treatment measures according to needs, so that the in-cabinet risk of the intelligent power distribution cabinet is remarkably reduced; the specific operation process of the risk comprehensive detection module in the cabinet is as follows:
acquiring smoke concentration data of a plurality of detection points in the intelligent power distribution cabinet, marking the smoke concentration data with the largest numerical value as a smoke detection value in the cabinet, comparing the smoke detection value in the cabinet with a preset smoke detection threshold value in the cabinet, and if the smoke detection value in the cabinet exceeds the preset smoke detection threshold value in the cabinet, indicating that the internal risk of the intelligent power distribution cabinet is larger, generating a high risk signal in the cabinet; if the in-cabinet risk analysis value does not exceed the preset in-cabinet risk analysis threshold, the in-cabinet risk analysis value FM of the intelligent power distribution cabinet is obtained through in-cabinet risk pipe analysis, the in-cabinet risk analysis value FM is compared with the preset in-cabinet risk analysis threshold in a numerical mode, and if the in-cabinet risk analysis value FM exceeds the preset in-cabinet risk analysis threshold, the in-cabinet risk is larger, and then an in-cabinet high risk signal is generated; if the risk analysis value FM in the cabinet does not exceed the preset risk analysis threshold value FM in the cabinet, the internal risk of the intelligent power distribution cabinet is smaller, and a low risk signal in the cabinet is generated.
Further, the specific analysis process of the in-cabinet risk tube analysis is as follows: acquiring real-time temperature and real-time humidity of corresponding detection points in the intelligent power distribution cabinet, performing difference calculation on the real-time temperature compared with a median value corresponding to a preset proper temperature range, and taking an absolute value to obtain a temperature value of the points in the cabinet, and acquiring the humidity value of the points in the cabinet in a similar way; respectively comparing the temperature value of the point in the cabinet with the humidity value of the point in the cabinet with a preset temperature threshold value of the point in the cabinet and a preset humidity threshold value of the point in the cabinet, and marking the corresponding detection point as a danger analysis point if the temperature value of the point in the cabinet or the humidity value of the point in the cabinet exceeds the corresponding preset threshold value, which indicates that the potential safety hazard existing in the corresponding detection point is larger;
the noise data and the vibration data generated by the intelligent power distribution cabinet during operation are collected and marked as an intra-cabinet operation noise value and an intra-cabinet operation vibration value respectively, wherein the noise data is a data value representing the noise decibel value generated by the intelligent power distribution cabinet during operation, and the vibration data is a data value representing the sum of the vibration amplitude and the vibration frequency generated by the intelligent power distribution cabinet during operation; marking the number of dangerous analysis points in the intelligent power distribution cabinet as a cabinet internal point measurement value;
carrying out numerical calculation on the in-cabinet noise running value FY, the in-cabinet vibration running value FW and the in-cabinet point measurement value FK through a formula FX=ty 1, FY+ty2, FW+ty3 to obtain an in-cabinet risk table value FX, wherein FY1, FY2 and FY3 are preset proportionality coefficients, and the values of FY1, FY2 and FY3 are all larger than zero; moreover, the larger the numerical value of the risk table value FX in the cabinet is, the larger the internal risk of the intelligent power distribution cabinet at the corresponding moment is; comparing the numerical value of the in-cabinet risk table value FX with a preset in-cabinet risk table threshold value, and marking the corresponding in-cabinet risk table value as an in-cabinet risk condition value if the in-cabinet risk table value FX exceeds the preset in-cabinet risk table threshold value, which indicates that the potential safety hazard in the intelligent power distribution cabinet at the corresponding moment is large;
acquiring the number of the risk condition values in the cabinet in the detection period, calculating the ratio of the number of the risk condition values to the number of the risk table values in the cabinet to obtain an abnormal value of the risk in the cabinet, summing all the risk table values in the detection period, calculating and taking an average value to obtain a sign value of the risk in the cabinet; carrying out numerical calculation on the risk abnormal value FP and the risk symptom value FZ in the cabinet to obtain an risk analysis value FM in the cabinet through a formula FM=wq1, FP+wq2 and FZ/wq 1; wherein, wq1 and wq2 are preset proportionality coefficients, and wq1 is more than wq2 is more than 0; and moreover, the larger the numerical value of the risk analysis value FM in the cabinet is, the larger the internal potential safety hazard of the intelligent power distribution cabinet in the detection period is.
The in-cabinet risk comprehensive detection module sends low-risk signals in the cabinet to the component displacement detection module through the on-line monitoring platform, the component displacement detection module analyzes the displacement conditions of corresponding components in the power distribution cabinet, marks the corresponding components as high-displacement components or low-displacement components through analysis, generates displacement detection failure signals or displacement detection qualified signals, sends the displacement detection failure signals to the background management and control end through the on-line monitoring platform, and sends corresponding early warning when the background management and control end receives the displacement detection failure signals, so that management personnel can make corresponding treatment measures in time to further reduce the running risk of the intelligent power distribution cabinet; the specific operation process of the component displacement detection module is as follows:
acquiring a component (such as a breaker, a contactor and the like) which is required to be subjected to displacement monitoring in the intelligent power distribution cabinet, and acquiring the actual displacement of the corresponding component, wherein the actual displacement is a data value representing the deviation distance of the current position of the corresponding component compared with the preset position of the corresponding component; comparing the actual displacement with a corresponding preset actual displacement threshold value, and marking the corresponding part as a high displacement part if the actual displacement exceeds the preset actual displacement threshold value, which indicates that the displacement degree of the corresponding part is large; if the intelligent power distribution cabinet has a high-displacement component, generating a displacement detection failure signal;
if the high displacement component does not exist, acquiring a displacement acceleration value of the corresponding component in unit time, wherein the displacement acceleration value is a data value representing the magnitude of the displacement increment of the corresponding component in unit time, and the larger the value of the displacement acceleration value is, the more serious the displacement condition of the corresponding component in unit time is; performing numerical calculation on the actual displacement WF and the displacement acceleration value WY of the corresponding component by using a formula wx=hy1 xwf+hy2 xwy to obtain a displacement analysis value WX; wherein, hy1 and hy2 are preset weight coefficients, and hy2 > hy1 > 0; and, the larger the value of the displacement analysis value WX, the larger the displacement risk of the corresponding component is indicated in the comprehensive aspect;
comparing the displacement analysis value WX with a corresponding preset displacement analysis threshold value, and marking the corresponding part as a displacement risk part if the displacement analysis value WX exceeds the preset displacement analysis threshold value, which indicates that the displacement risk of the corresponding part is large; marking the number of the displacement risk-saving components as component displacement risk measurement values, wherein the larger the number of the component displacement detection values is, the worse the integral displacement condition of the components in the intelligent power distribution cabinet is, comparing the component displacement risk measurement values with preset component displacement risk measurement thresholds, and if the component displacement risk measurement values exceed the preset component displacement risk measurement thresholds, indicating that the integral displacement condition of the components in the intelligent power distribution cabinet is worse, and not beneficial to ensuring the safe and stable operation of the intelligent power distribution cabinet, generating a displacement detection disqualification signal; and if the component displacement risk measurement value does not exceed the preset component displacement risk measurement threshold value, indicating that the overall displacement condition of the components in the intelligent power distribution cabinet is good, generating a displacement detection qualified signal.
Embodiment two: as shown in fig. 2, the difference between the embodiment and embodiment 1 is that the online monitoring platform is in communication connection with the cabinet body supervision and classification module, the cabinet body supervision and classification module collects the production date of the intelligent power distribution cabinet, marks the interval duration between the production date and the current date as the detection value when the cabinet body is produced, and collects the total duration of the operation of the intelligent power distribution cabinet in the interval duration between the production date and the current date and marks the total duration as the detection value when the cabinet body is operated; the larger the detection value during the production of the cabinet body and the numerical value of the detection value during the operation of the cabinet body, the worse the service life condition of the intelligent power distribution cabinet is;
respectively comparing the detection value during cabinet production and the detection value during cabinet operation with a preset cabinet production detection threshold value and a preset cabinet operation detection threshold value, and if the detection value during cabinet production or the detection value during cabinet operation exceeds the corresponding preset threshold value, indicating that the service life of the intelligent power distribution cabinet is poor, and generating a strong supervision signal of the intelligent power distribution cabinet if the service life needs to be strengthened;
if the detection value of the cabinet body during production and the detection value of the cabinet body during operation do not exceed the corresponding preset threshold values, setting a supervision period, wherein the supervision period is preferably ten days; the method comprises the steps that the times of generating an electric power parameter abnormal signal, the times of generating an electric power parameter adjustment early warning signal, the times of generating an in-cabinet high risk signal and the times of generating a displacement detection unqualified signal of an intelligent power distribution cabinet in a supervision period are collected and marked as an electric power parameter abnormal frequency analysis value, an electric power parameter frequency analysis value, an in-cabinet risk frequency analysis value and a displacement detection frequency analysis value respectively;
carrying out numerical calculation on the power parameter abnormal frequency analysis value GY, the power parameter frequency analysis value GK, the risk frequency analysis value GF in the cabinet and the displacement detection frequency analysis value GW through a formula GX= (a1+a2+GK+a3+a4+GW)/4 to obtain a cabinet supervision evaluation value GX, wherein a1, a2, a3 and a4 are preset proportionality coefficients, and the values of a1, a2, a3 and a4 are all larger than zero; and the larger the numerical value of the cabinet supervision evaluation value GX is, the worse the running condition of the intelligent power distribution cabinet is, and the more the running supervision of the intelligent power distribution cabinet is required to be enhanced;
comparing the cabinet supervision evaluation value GX with a preset cabinet supervision evaluation threshold value, and if the cabinet supervision evaluation value GX exceeds the preset cabinet supervision evaluation threshold value, indicating that the operation condition of the intelligent power distribution cabinet is poor, generating a strong supervision signal of the intelligent power distribution cabinet; if the cabinet supervision evaluation value GX does not exceed the preset cabinet supervision evaluation threshold, indicating that the operation condition of the intelligent power distribution cabinet is good, generating a weak supervision signal of the intelligent power distribution cabinet; and the strong supervision signals or the weak supervision signals of the intelligent power distribution cabinet are sent to the background management and control end through the on-line monitoring platform, corresponding early warning is sent when the background management and control end receives the strong supervision signals, and a manager reasonably formulates subsequent supervision planning when receiving the corresponding early warning, so that the operation supervision of the intelligent power distribution cabinet is enhanced, and the safe and stable operation of the intelligent power distribution cabinet is further ensured.
Embodiment III: as shown in fig. 3, the difference between the present embodiment and embodiments 1 and 2 is that the data on-line monitoring method based on the intelligent power distribution cabinet provided by the present invention includes the following steps:
step one, monitoring power parameters of an intelligent power distribution cabinet and judging whether the power parameters exist or not, and generating a power parameter normal signal or a power parameter abnormal signal according to the power parameters;
step two, when generating an abnormal signal of the power parameter, the parameter self-adjusting module automatically adjusts the risk parameter so as to meet the corresponding requirement;
detecting and analyzing the internal risk condition of the intelligent power distribution cabinet, and generating a high risk signal in the cabinet or a low risk signal in the cabinet through analysis;
and fourthly, when the low risk signal in the power distribution cabinet is generated, analyzing the displacement condition of the corresponding component in the power distribution cabinet, and generating a displacement detection unqualified signal or a displacement detection qualified signal through analysis.
The working principle of the invention is as follows: when the intelligent power distribution cabinet is used, the power parameter detection module is used for monitoring the power parameter of the intelligent power distribution cabinet and judging whether the power parameter exists, a power parameter normal signal or a power parameter abnormal signal is generated according to the power parameter normal signal or the power parameter abnormal signal, the power parameter is automatically adjusted by the parameter self-adjusting module when the power parameter abnormal signal is generated so as to meet corresponding requirements, and the adjustment efficiency condition of the parameter self-adjusting module is detected and evaluated by the power parameter detection module so as to judge whether the power parameter adjustment early warning signal is generated or not, so that the safe and stable operation of the intelligent power distribution cabinet is effectively ensured; and detecting and analyzing the internal risk condition of the intelligent power distribution cabinet through the in-cabinet risk comprehensive detection module, generating an in-cabinet high risk signal or an in-cabinet low risk signal through analysis, analyzing the displacement condition of the corresponding component in the power distribution cabinet through the component displacement detection module when generating the in-cabinet low risk signal, and marking the corresponding component as a high displacement component or a low displacement component through analysis, thereby further reducing the operation risk of the intelligent power distribution cabinet.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (10)
1. The data online monitoring system based on the intelligent power distribution cabinet is characterized by comprising an online monitoring platform, an electric power parameter detection module, a parameter self-adjusting module, an in-cabinet risk comprehensive detection module, a component displacement detection module and a background management and control end; the power parameter detection module monitors the power parameters of the intelligent power distribution cabinet and judges whether the power parameters exist or not, a power parameter normal signal or a power parameter abnormal signal is generated according to the power parameters, and the power parameter abnormal signal and the power parameters are sent to the parameter self-adjusting module and the background management and control end through the online monitoring platform; when the parameter self-adjusting module receives the power parameter abnormal signal, the risk saving parameter is automatically adjusted to meet the corresponding requirement;
the in-cabinet risk comprehensive detection module detects and analyzes the internal risk condition of the intelligent power distribution cabinet, generates an in-cabinet high risk signal or an in-cabinet low risk signal through analysis, sends the in-cabinet high risk signal to a background management and control end through an on-line monitoring platform, and sends the in-cabinet low risk signal to the component displacement detection module through the on-line monitoring platform; the component displacement detection module analyzes the displacement condition of the corresponding component in the power distribution cabinet, marks the corresponding component as a high-displacement component or a low-displacement component through analysis, generates a displacement detection unqualified signal or a displacement detection qualified signal, and sends the displacement detection unqualified signal to a background management and control end through the online monitoring platform; and the background control receives the abnormal signal of the power parameter, and sends out corresponding early warning when the high risk signal or the displacement detection disqualification signal in the cabinet.
2. The intelligent power distribution cabinet-based data online monitoring system according to claim 1, wherein the specific operation process of the power parameter detection module comprises:
acquiring power parameters required to be monitored of the intelligent power distribution cabinet, and marking the corresponding power parameters as i, wherein i is a natural number larger than 1; acquiring real-time parameter data of the power parameter i, and marking the corresponding power parameter i as a risk parameter if the real-time parameter data does not meet the corresponding preset real-time parameter data requirement; if the existence parameter does not exist, generating a power parameter normal signal; if the existence of the risk parameter exists, generating a power parameter abnormality signal.
3. The intelligent power distribution cabinet-based data online monitoring system according to claim 1, wherein when generating an abnormal signal of the power parameter, the power parameter detection module marks the deviation value of the real-time parameter data corresponding to the risk parameter as a power parameter value compared with the deviation value required by the corresponding preset real-time parameter data, the power parameter value is compared with a corresponding preset power parameter threshold value in a numerical manner, and if the power parameter value exceeds the corresponding preset power parameter threshold value, the corresponding risk parameter is marked as a high-risk parameter;
marking the number of the risk parameters in the intelligent power distribution cabinet as a risk parameter value, and marking the ratio of the number of the high risk parameters to the risk parameter deviation value as a high risk parameter value; carrying out weighted summation on the high risk parameter detection value and the risk parameter detection value to obtain a power parameter correction value, presetting a plurality of groups of preset power parameter correction value ranges, wherein each group of preset power parameter correction value ranges corresponds to a group of preset adjustment time periods, and comparing the power parameter correction value with all the preset power parameter correction value ranges one by one to determine the preset adjustment time periods matched with the power parameter correction value ranges and marking the preset adjustment time periods as set time periods;
when the parameter self-adjusting module adjusts the risk storage parameters of the intelligent power distribution cabinet, the moment that the parameter self-adjusting module receives the power parameter abnormal signal is obtained and is used as a time starting point to time, so that the real-time adjusting time length of the parameter self-adjusting module is collected, when the real-time adjusting time length reaches the set time length and the parameter adjustment of the intelligent power distribution cabinet is not completed, the adjustment condition of the parameter self-adjusting module is judged to be poor, a power parameter adjustment early warning signal is generated, the power parameter adjustment early warning signal is sent to a background management and control end through an online monitoring platform, and the background management and control end sends corresponding early warning when receiving the power parameter adjustment early warning signal.
4. The intelligent power distribution cabinet-based data online monitoring system according to claim 1, wherein the specific operation process of the in-cabinet risk comprehensive inspection module comprises:
acquiring smoke concentration data of a plurality of detection points in an intelligent power distribution cabinet, marking the smoke concentration data with the largest numerical value as a smoke detection value in the cabinet, comparing the smoke detection value in the cabinet with a preset smoke detection threshold value in the cabinet, and generating a high risk signal in the cabinet if the smoke detection value in the cabinet exceeds the preset smoke detection threshold value in the cabinet; if the in-cabinet smoke detection value does not exceed the preset in-cabinet smoke detection threshold, acquiring an in-cabinet risk analysis value of the intelligent power distribution cabinet through in-cabinet risk pipe analysis, and if the in-cabinet risk analysis value exceeds the preset in-cabinet risk analysis threshold, generating an in-cabinet high risk signal; and if the risk analysis value in the cabinet does not exceed the preset risk analysis threshold value in the cabinet, generating a low risk signal in the cabinet.
5. The intelligent power distribution cabinet-based data online monitoring system according to claim 4, wherein the specific analysis process of the in-cabinet risk management analysis is as follows:
acquiring real-time temperature and real-time humidity of corresponding detection points in the intelligent power distribution cabinet, performing difference calculation on the real-time temperature compared with a median value corresponding to a preset proper temperature range, and taking an absolute value to obtain a temperature value of the points in the cabinet, and acquiring the humidity value of the points in the cabinet in a similar way; if the temperature value of the point in the cabinet or the humidity value of the point in the cabinet exceeds the corresponding preset threshold value, marking the corresponding detection point as a risk analysis point;
the noise data and the vibration data generated by the intelligent power distribution cabinet during operation are collected and marked as an in-cabinet operation noise value and an in-cabinet operation vibration value respectively, and the number of dangerous analysis points in the intelligent power distribution cabinet is marked as an in-cabinet point measurement value; carrying out numerical calculation on the in-cabinet noise operation value, the in-cabinet vibration operation value and the in-cabinet point measurement value to obtain an in-cabinet risk table value, and marking the corresponding in-cabinet risk table value as an in-cabinet risk condition value if the in-cabinet risk table value exceeds a preset in-cabinet risk table threshold value;
acquiring the number of the risk condition values in the cabinet in the detection period, calculating the ratio of the number of the risk condition values to the number of the risk table values in the cabinet to obtain an abnormal value of the risk in the cabinet, summing all the risk table values in the detection period, calculating and taking an average value to obtain a sign value of the risk in the cabinet; and carrying out numerical calculation on the risk abnormal value and the risk sign value to obtain a risk analysis value.
6. The intelligent power distribution cabinet-based data online monitoring system according to claim 1, wherein the specific operation process of the component displacement detection module comprises:
acquiring a component needing to be subjected to displacement monitoring in the intelligent power distribution cabinet, acquiring the actual displacement of a corresponding component, comparing the actual displacement with a corresponding preset actual displacement threshold value, and marking the corresponding component as a high-displacement component if the actual displacement exceeds the preset actual displacement threshold value; and if the intelligent power distribution cabinet is internally provided with a high-displacement component, generating a displacement detection failure signal.
7. The intelligent power distribution cabinet-based data online monitoring system according to claim 6, wherein if no high-displacement component exists in the intelligent power distribution cabinet, acquiring a displacement acceleration value of the corresponding component in unit time, and performing numerical calculation on the actual displacement quantity and the displacement acceleration value of the corresponding component to obtain a displacement analysis value; comparing the displacement analysis value with a corresponding preset displacement analysis threshold value, and marking the corresponding part as a displacement risk part if the displacement analysis value exceeds the preset displacement analysis threshold value;
marking the number of the displacement risk components as component displacement risk measurement values, and generating a displacement detection failure signal if the component displacement risk measurement values exceed a preset component displacement risk measurement threshold value; and if the component displacement risk measurement value does not exceed the preset component displacement risk measurement threshold value, generating a displacement detection qualified signal.
8. The online data monitoring system based on the intelligent power distribution cabinet according to claim 1, wherein the online monitoring platform is in communication connection with the cabinet body supervision and grading module, the cabinet body supervision and grading module collects the production date of the intelligent power distribution cabinet, marks the interval duration between the production date and the current date as a cabinet body production time check value, and collects the total duration of the operation of the intelligent power distribution cabinet in the interval duration between the production date and the current date and marks the total duration as a cabinet body operation time check value; and if the detection value during the production of the cabinet body or the detection value during the operation of the cabinet body exceeds a corresponding preset threshold value, generating a strong supervision signal of the intelligent power distribution cabinet.
9. The intelligent power distribution cabinet-based data online monitoring system according to claim 8, wherein if the detection value during cabinet production and the detection value during cabinet operation do not exceed the corresponding preset thresholds, a supervision period is set, and the number of times the intelligent power distribution cabinet generates an abnormal power parameter signal, the number of times the intelligent power parameter adjustment early warning signal is generated, the number of times the intelligent power distribution cabinet generates a high risk signal and the number of times the intelligent power distribution cabinet generates a displacement detection failure signal in the supervision period are collected and marked as an electric power parameter analysis value, an intra-cabinet risk analysis value and a displacement detection analysis value respectively;
performing numerical calculation on the electric power parameter frequency analysis value, the in-cabinet risk frequency analysis value and the displacement detection frequency analysis value to obtain a cabinet body supervision evaluation value, and generating a strong supervision signal of the intelligent power distribution cabinet if the cabinet body supervision evaluation value exceeds a preset cabinet body supervision evaluation threshold value; if the cabinet supervision evaluation value does not exceed the preset cabinet supervision evaluation threshold, generating a weak supervision signal of the intelligent power distribution cabinet; and the strong supervision signals or the weak supervision signals of the intelligent power distribution cabinet are sent to the background management and control end through the on-line monitoring platform.
10. An online data monitoring method based on an intelligent power distribution cabinet is characterized in that the online data monitoring method adopts the online data monitoring system based on the intelligent power distribution cabinet as claimed in any one of claims 1-9.
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