CN116470637B - Weak current equipment power supply monitoring system based on data analysis - Google Patents
Weak current equipment power supply monitoring system based on data analysis Download PDFInfo
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- 238000007405 data analysis Methods 0.000 title claims abstract description 16
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
Abstract
The invention discloses a weak current equipment power supply monitoring system based on data analysis, which belongs to the field of weak current and is used for solving the problem that a monitoring result of power supply monitoring of weak current equipment is limited to single data analysis.
Description
Technical Field
The invention belongs to the field of weak current equipment, relates to a power supply monitoring technology, and in particular relates to a weak current equipment power supply monitoring system based on data analysis.
Background
Weak current generally refers to direct current circuits or audio, video, network, telephone lines, and alternating current voltages generally within 36V. The household appliances such as telephone, computer and television signal input (cable television line) and sound equipment (output end line) are weak current electric equipment. Strong and weak currents are conceptually easy to distinguish, with the main differences being the differences in use. Strong electricity is used as a power source, weak electricity is used as a signal electricity, and voltage is not a method for distinguishing strong electricity from weak electricity.
When the weak current equipment is monitored by power supply, the adaptive monitoring criteria are not set according to the factors such as equipment, environment and the like, the monitoring result is limited to single data analysis, and misjudgment, missed judgment and the like are easy to cause.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a weak current equipment power supply monitoring system based on data analysis.
The technical problems to be solved by the invention are as follows:
(1) How to set the differential monitoring standard by combining the used time length of the equipment, the use frequency of the equipment and the working environment of the equipment.
(2) How to obtain more accurate analysis results by analyzing multiple data, and reduce the problems of erroneous judgment or missed judgment.
(3) How to judge the problem of abnormal source information causing abnormal power supply by analyzing a plurality of data.
The aim of the invention can be achieved by the following technical scheme:
the weak current equipment power supply monitoring system based on data analysis comprises an equipment group management module, a data acquisition module, a weak current signal analysis module, a signal database, a power supply quality verification module, an equipment state analysis module, a monitoring terminal, an abnormal source detection module and a server, wherein the equipment group management module is used for carrying out group division on weak current equipment in an application place to obtain an effective data set and sending the effective data set to the server; the data acquisition module is used for acquiring equipment state data of weak current equipment and weak current signal real-time data in the effective data set and sending the data to the server, and the server sends the equipment state data to the equipment state analysis module and the abnormal source detection module and sends the weak current signal real-time data to the weak current signal analysis module; the signal database is used for storing weak current signal standard data of different weak current devices;
the weak current signal analysis module is used for analyzing weak current signals of weak current equipment in the effective data set, and obtaining equipment power supply quality abnormal coefficients of the weak current equipment in the effective data set and sending the equipment power supply quality abnormal coefficients to the power supply quality verification module through the server; the device state analysis module is used for analyzing the device state conditions of the weak current devices in the effective data set, obtaining the device abnormal risk coefficients of the weak current devices in the effective data set, and sending the device abnormal risk coefficients to the power supply quality verification module through the server;
the power supply quality verification module is used for setting the power supply abnormality risk level of the weak current equipment in the effective data set, obtaining power supply abnormality risk level feedback to the server, and the server sets a corresponding number of detection comparison groups for the weak current equipment in the effective data set according to the power supply abnormality risk level and sends the detection comparison groups to the abnormality source detection module; the data acquisition module is used for acquiring abnormal source data of the weak current equipment in the effective data set, corresponding to the detection control set in an abnormal operation state, and sending the abnormal source data to the abnormal source detection module through the server; the abnormal source detection module is used for detecting equipment abnormal source data of weak current equipment in the effective data set, generating equipment power supply abnormal signals or equipment power supply normal signals and feeding the equipment power supply abnormal signals back to the server, if the server receives the equipment power supply normal signals, no operation is performed, if the server receives the equipment power supply abnormal signals, the equipment power supply abnormal signals are sent to the monitoring terminal, and the monitoring terminal is used for checking appointed weak current equipment after receiving the equipment power supply abnormal signals.
Further, the equipment state data are equipment continuous use time length, element real-time temperature, dust accumulation degree, element real-time current, element real-time voltage and element real-time resistance of weak current equipment in the effective data set;
the weak current signal real-time data are the abnormal times of the power supply quality of weak current equipment in the effective data set, the duration of the abnormal power supply quality when the power supply quality is abnormal each time and the abnormal power supply quality time;
the weak current signal standard data are the abnormal times of the power supply quality standard of the weak current equipment, the standard duration time when the power supply quality is abnormal each time and the abnormal time node of the power supply quality standard;
the abnormal source data is an element abnormal current value, an element abnormal voltage value and an element abnormal resistance value when weak current equipment in the effective data set is correspondingly detected to be in an abnormal operation state of the control group.
Further, the weak current signal analysis module has the following analysis process;
acquiring abnormal times of the power supply quality of weak current equipment in an effective data set;
obtaining the abnormal time of the power supply quality of the weak current equipment in the effective data set, and calculating the difference value of adjacent abnormal time of the power supply quality to obtain the abnormal interval duration of the power supply quality of the weak current equipment in the effective data set;
finally, obtaining the power supply quality abnormality duration of the weak current equipment in the effective data set when the power supply quality of each weak current equipment is abnormal, and adding and summing the power supply quality abnormality duration of each weak current equipment when the power supply quality of each weak current equipment is abnormal to obtain the power supply quality abnormality duration of the weak current equipment in the effective data set;
calculating a stable device power supply quality value of weak current devices in the effective data set;
and comparing the stable value of the equipment power supply quality with the stable threshold value of the equipment power supply quality to obtain the abnormal coefficient of the equipment power supply quality of the weak current equipment in the effective data set.
Further, the stable value of the power supply quality of the equipment is in direct proportion to the abnormal coefficient of the power supply quality of the equipment, namely, the larger the stable value of the power supply quality of the equipment is, the larger the abnormal coefficient of the power supply quality of the equipment is.
Further, the analysis process of the equipment state analysis module is specifically as follows;
acquiring the continuous use time of the equipment of each weak current equipment in the effective data set, and then acquiring the real-time temperature of the element of each weak current equipment in the effective data set, and subtracting the absolute value from the element real-time temperature and the element standard temperature to obtain the real-time temperature difference value of the equipment of each weak current equipment in the effective data set;
acquiring the equipment dust accumulation degree of each weak current equipment in the effective data set, and calculating the equipment abnormal risk value of the weak current equipment in the effective data set;
and comparing the equipment abnormality risk values with the equipment abnormality risk threshold values to obtain equipment abnormality risk coefficients of weak current equipment in the effective data set.
Further, the equipment abnormal risk value is in direct proportion to the equipment abnormal risk coefficient, namely, the larger the value of the equipment abnormal risk value is, the larger the value of the equipment abnormal risk coefficient is.
Further, the setting process of the power supply quality verification module specifically includes the following steps:
acquiring an equipment abnormal risk coefficient and an equipment power supply quality abnormal coefficient, and calculating a power supply abnormal risk value of weak current equipment in an effective data set;
and then acquiring a power supply abnormality risk threshold stored in the server, comparing the power supply abnormality risk threshold with the power supply abnormality risk value of each weak current device in the effective data set, and judging that the power supply abnormality risk level of the weak current device in the effective data set is a third power supply abnormality risk level, a second power supply abnormality risk level or a first power supply abnormality risk level.
Further, the power supply abnormality risk threshold includes a first power supply abnormality risk threshold and a second power supply abnormality risk threshold, and the first power supply abnormality risk threshold is smaller than the second power supply abnormality risk threshold;
the third power supply abnormality risk level is lower than the second power supply abnormality risk level, which is lower than the first power supply abnormality risk level.
Further, if the power supply risk is the first power supply abnormality risk level, the number of the detection control groups is the number of the first detection control groups;
if the power supply is at the second abnormal power supply risk level, the number of the detection control groups is the number of the second detection control groups;
if the power supply is at the third abnormal power supply risk level, the number of the detection control groups is the number of the third detection control groups;
wherein, the value of the first detection control group number is larger than the value of the second detection control group number, and the value of the second detection control group number is larger than the value of the third detection control group number.
Further, the detection method of the abnormal source detection module specifically comprises the following steps:
acquiring a detection comparison group of the appointed number of weak current devices in an effective data group;
then obtaining an element abnormal current value, an element abnormal voltage value and an element abnormal resistance value of the weak current equipment corresponding detection control group in the effective data group;
traversing and comparing the element abnormal current values of the corresponding detection control group of the weak current devices in the effective data group to obtain element abnormal power minimum values and element abnormal power minimum values of the corresponding detection control group of the weak current devices in the effective data group, wherein the element abnormal power minimum values and the element abnormal power minimum values jointly form an element abnormal current interval of the detection control group;
similarly, an element abnormal voltage interval and an element abnormal resistance interval of the detection control group are obtained;
acquiring element real-time current, element real-time voltage and element real-time resistance of weak current equipment in an effective data set;
if any one of the element real-time current in the element abnormal current interval, the element real-time voltage in the element abnormal voltage interval or the element real-time resistance in the element abnormal resistance interval is met, generating an equipment power supply abnormal signal;
and if all the items that the element real-time current is not in the element abnormal current interval, the element real-time voltage is not in the element abnormal voltage interval and the element real-time resistance is not in the element abnormal resistance interval are satisfied, generating an equipment power supply abnormal signal.
Compared with the prior art, the invention has the beneficial effects that:
the invention divides weak current equipment into groups through an equipment group management module to obtain an effective data group, then analyzes weak current signals of the weak current equipment in the effective data group through a weak current signal analysis module to obtain equipment power supply quality abnormality coefficients of the weak current equipment in the effective data group, analyzes equipment state conditions of the weak current equipment in the effective data group through an equipment state analysis module to obtain equipment abnormality risk coefficients of the weak current equipment in the effective data group, sends the equipment power supply quality abnormality coefficients and the equipment abnormality risk coefficients to a power supply quality verification module, sets the power supply abnormality risk level of the weak current equipment in the effective data group to obtain the power supply abnormality risk level, sets a corresponding number of detection contrast groups for the weak current equipment in the effective data group according to the power supply abnormality risk level, and finally detects the equipment abnormality source data of the weak current equipment in the effective data group through an abnormality source detection module to generate equipment power supply abnormality signals or equipment power supply normal signals.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
Fig. 1 is an overall system block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, 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.
In an embodiment, referring to fig. 1, a weak current device power supply monitoring system based on data analysis is provided, and the system is applied to monitoring weak current devices in residential communities and industrial parks, and is not limited herein;
in specific implementation, the system comprises an equipment group management module, a data acquisition module, a weak current signal analysis module, a signal database, a power supply quality verification module, an equipment state analysis module, a monitoring terminal, an abnormal source detection module and a server, wherein a plurality of monitoring terminals are connected with the server;
specifically, the monitoring terminal is a main control screen of a power supply monitoring center in the application place;
the device group management module is used for dividing weak current devices in an application place into effective data groups and invalid data groups based on factors such as service life and service frequency of the weak current devices, and sending the effective data groups to a server, wherein one group of weak current devices possibly exist in the effective data groups, and multiple groups of weak current devices possibly exist in the effective data groups;
it can be understood that the weak current devices are divided into the invalid data groups through the device group management module, and the data information of the weak current devices does not have referential property, so that only the valid data groups need to be sent to the server;
the data acquisition module is used for acquiring equipment state data and weak current signal real-time data of weak current equipment in the effective data set, and sending the equipment state data and the weak current signal real-time data to the server, the server sends the equipment state data to the equipment state analysis module and the abnormal source detection module, and the server sends the weak current signal real-time data to the weak current signal analysis module;
the specific explanation is that the equipment state data is the equipment continuous use time length, the element real-time temperature, the dust accumulation degree, the element real-time current, the element real-time voltage, the element real-time resistance and the like of the weak current equipment in the effective data set; the weak current signal real-time data are the abnormal times of the power supply quality of weak current equipment in the effective data set, the duration of the abnormal power supply quality when the power supply quality is abnormal each time, the abnormal power supply quality time and the like;
specifically, the data acquisition module may be a weak current signal monitor, an ammeter, a voltmeter, a resistance meter, etc. on a weak current device, or may be a thermometer, a dust accumulation monitor, etc., which are not specifically limited and described herein;
in this embodiment, the weak current signal analysis module is further connected with a signal database, where the signal database is used to store weak current signal standard data of different weak current devices;
the weak current signal standard data is the abnormal times of the power supply quality standard of the weak current equipment, the standard duration time when the power supply quality is abnormal each time and the abnormal time node of the power supply quality standard;
the weak current signal analysis module is used for analyzing weak current signals of weak current equipment in the effective data set, and the analysis process is specifically as follows;
step one: acquiring the abnormal times of the power supply quality of the weak current equipment in the effective data set, and taking the abnormal times of the power supply quality DETu, u=1, 2, … …, z and z as positive integers, wherein u represents the serial numbers of the weak current equipment in the effective data set;
step two: then acquiring the abnormal time of the power supply quality of the weak current equipment in the effective data set, and calculating the difference value of adjacent abnormal time of the power supply quality to obtain the abnormal interval duration DJTu of the power supply quality of the weak current equipment in the effective data set;
step three: finally, the power supply quality abnormality duration when the power supply quality of the weak current equipment is abnormal each time in the effective data set is obtained, and the power supply quality abnormality duration DCTu of the weak current equipment in the effective data set is obtained by adding and summing the power supply quality abnormality durations when the power supply quality of the weak current equipment is abnormal each time;
step four: according to the formulaCalculating to obtain a stable device power supply quality value DWu of weak current devices in the effective data set, wherein a1, a2 and a3 are proportionality coefficients of fixed values, and the values of a1, a2 and a3 are all larger than zero;
step five: if DWu is less than X1, the abnormal device power supply quality coefficient of weak current devices in the effective data set is q1;
if X1 is less than or equal to DWu and less than X2, the abnormal device power supply quality coefficient of weak current devices in the effective data set is q2;
if X2 is less than or equal to DWu, the abnormal device power supply quality coefficient of weak current devices in the effective data set is q3; wherein X1 and X2 are equipment power supply quality stable thresholds with fixed values, X1 is smaller than X2, and q1, q2 and q3 are positive integers with fixed values, and q1 is smaller than q2 and smaller than q3;
it can be understood that the stable value of the equipment power supply quality is in direct proportion to the abnormal coefficient of the equipment power supply quality, namely, the larger the value of the stable value of the equipment power supply quality is, the larger the value of the abnormal coefficient of the equipment power supply quality is;
the weak current signal analysis module feeds back the abnormal device power supply quality coefficient of the weak current device in the effective data set to the server, and the server sends the abnormal device power supply quality coefficient of the weak current device in the effective data set to the power supply quality verification module;
in this embodiment, the device state analysis module is configured to analyze a device state of a weak current device in the effective data set, where an analysis process is specifically as follows;
step S1: acquiring the continuous use time length of the weak current equipment in the effective data set, and acquiring the continuous use time length STu of the weak current equipment in the effective data set;
step S2: acquiring the real-time temperature of the element of the weak current equipment in the effective data set, and subtracting the absolute value from the standard temperature of the element to obtain the real-time temperature difference SCu of the weak current equipment in the effective data set;
step S3: acquiring the equipment dust accumulation degree of each weak current equipment in the effective data set, and marking the equipment dust accumulation degree as SDu;
step S4: calculating to obtain an equipment abnormality risk value SYFu of weak current equipment in an effective data set according to a formula SYFu= STu ×b1+SCu×b2+SDu×b3, wherein b1, b2 and b3 are proportionality coefficients with fixed values, and the values of b1, b2 and b3 are all larger than zero;
step S5: if SYFu is less than Y1, the equipment abnormality risk coefficient of weak current equipment in the effective data set is r1;
if Y1 is less than or equal to SYFu and less than Y2, the equipment abnormality risk coefficient of weak current equipment in the effective data set is r2;
if Y2 is less than or equal to SYFu, the equipment abnormality risk coefficient of weak current equipment in the effective data set is r3; wherein Y1 and Y2 are equipment abnormality risk thresholds with fixed values, Y1 is smaller than Y2, and simultaneously, r1, r2 and r3 are positive integers with fixed values, and r1 is smaller than r2 and r3;
it can be understood that the equipment abnormal risk value is in direct proportion to the equipment abnormal risk coefficient, namely, the larger the value of the equipment abnormal risk value is, the larger the value of the equipment abnormal risk coefficient is;
the device state analysis module feeds back the device abnormality risk coefficient of the weak current device in the effective data set to the server, and the server sends the device abnormality risk coefficient of the weak current device in the effective data set to the power supply quality verification module;
the power supply quality verification module is used for setting the power supply abnormality risk level of the weak current equipment in the effective data set, and the setting process is specifically as follows:
step Q1: acquiring the calculated equipment abnormal risk coefficient and equipment power supply quality abnormal coefficient, and marking the equipment abnormal risk coefficient and the equipment power supply quality abnormal coefficient as DRxu and DQxu;
step Q2: calculating according to a formula ERu =DRXc1+DQXu×c2 to obtain a power supply abnormality risk value ERu of weak current equipment in the effective data set; wherein, c1 and c2 are weight coefficients with fixed values, and the values of c1 and c2 are larger than zero, and c1+c2=1;
step Q3: acquiring a power supply abnormality risk threshold stored in a server, and comparing the power supply abnormality risk threshold with a power supply abnormality risk value of each weak current device in an effective data set;
the power supply abnormality risk threshold comprises a first power supply abnormality risk threshold and a second power supply abnormality risk threshold, and the first power supply abnormality risk threshold is smaller than the second power supply abnormality risk threshold;
step Q4: if the power supply abnormality risk value is smaller than the first power supply abnormality risk threshold value, the power supply abnormality risk level of the weak current equipment in the effective data set is a third power supply abnormality risk level;
if the power supply abnormality risk value is greater than or equal to the first power supply abnormality risk threshold and smaller than the second power supply abnormality risk threshold, the power supply abnormality risk level of the weak current equipment in the effective data set is the second power supply abnormality risk level;
if the power supply abnormality risk value is greater than or equal to the second power supply abnormality risk threshold value, the power supply abnormality risk level of the weak current equipment in the effective data set is a first power supply abnormality risk level;
it can be understood that the level of the third power supply abnormality risk level is lower than the level of the second power supply abnormality risk level, the level of the second power supply abnormality risk level is lower than the level of the first power supply abnormality risk level, and the higher the power supply abnormality risk level is, the higher the possibility that the power supply abnormality risk of the weak current equipment is represented;
the power supply quality verification module feeds back the power supply abnormality risk level to the server, the server sets a corresponding number of detection comparison groups for weak current equipment in the effective data set according to the power supply abnormality risk level, and sends the corresponding number of detection comparison groups to the abnormality source detection module, specifically:
if the power supply is at the first power supply abnormality risk level, the number of the detection control groups is the number of the first detection control groups;
if the power supply is at the second abnormal power supply risk level, the number of the detection control groups is the number of the second detection control groups;
if the power supply is at the third abnormal power supply risk level, the number of the detection control groups is the number of the third detection control groups;
it can be understood that if the risk level of abnormal power supply is different, the number of the detection control groups is correspondingly changed, that is, the value of the first detection control group is larger than the value of the second detection control group, and the value of the second detection control group is larger than the value of the third detection control group;
the data acquisition module is used for acquiring abnormal source data of the weak current equipment in the effective data set, which corresponds to the detection control set and is in an abnormal operation state, and sending the abnormal source data to the server, and the server sends the abnormal source data to the abnormal source detection module;
the abnormal source data is an element abnormal current value, an element abnormal voltage value, an element abnormal resistance value and the like when the weak current equipment in the effective data set corresponds to the detection control set in an abnormal operation state, wherein the element can be a power supply, a small transformer and the like in the weak current equipment corresponding to the detection control set;
the abnormal source detection module is used for detecting equipment abnormal source data of weak current equipment in the effective data set, and the detection method specifically comprises the following steps:
step T1: acquiring a detection comparison group of the appointed number of weak current devices in an effective data group;
step T2: acquiring an element abnormal current value, an element abnormal voltage value and an element abnormal resistance value of weak current equipment corresponding detection control group in an effective data group;
step T3: traversing and comparing the element abnormal current values of the corresponding detection control group of the weak current devices in the effective data group to obtain element abnormal power minimum values and element abnormal power minimum values of the corresponding detection control group of the weak current devices in the effective data group, wherein the element abnormal power minimum values and the element abnormal power minimum values jointly form an element abnormal current interval of the detection control group;
similarly, an element abnormal voltage interval and an element abnormal resistance interval of the detection control group are obtained according to the method;
step T4: acquiring element real-time current, element real-time voltage and element real-time resistance of weak current equipment in an effective data set;
step T5: if any one of the element real-time current in the element abnormal current interval, the element real-time voltage in the element abnormal voltage interval or the element real-time resistance in the element abnormal resistance interval is met, generating an equipment power supply abnormal signal;
if all the items that the element real-time current is not in the element abnormal current interval, the element real-time voltage is not in the element abnormal voltage interval and the element real-time resistance is not in the element abnormal resistance interval are met, generating an equipment power supply abnormal signal;
the abnormal source detection module feeds back the equipment power supply abnormal signal or the equipment power supply normal signal to the server, if the server receives the equipment power supply normal signal, no operation is performed, if the server receives the equipment power supply abnormal signal, the equipment power supply abnormal signal is sent to the monitoring terminal, and the monitoring terminal is used for checking the appointed weak current equipment after receiving the equipment power supply abnormal signal.
The above formulas are all dimensionality-removed and numerical calculations, such as weight coefficients, proportion coefficients and the like, and the set size is a result value obtained by quantizing each parameter, and the size of the weight coefficients and the proportion coefficients is only required to be not influenced as long as the proportion relation between the parameters and the result value is not influenced.
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 (7)
1. The weak current equipment power supply monitoring system based on data analysis is characterized by comprising an equipment group management module, a data acquisition module, a weak current signal analysis module, a signal database, a power supply quality verification module, an equipment state analysis module, a monitoring terminal, an abnormal source detection module and a server, wherein the equipment group management module is used for dividing weak current equipment in an application place into groups, dividing the weak current equipment into an effective data group and an ineffective data group based on the service life and the service frequency of the weak current equipment, and transmitting the effective data group to the server; the data acquisition module is used for acquiring equipment state data of weak current equipment and weak current signal real-time data in the effective data set and sending the data to the server, and the server sends the equipment state data to the equipment state analysis module and the abnormal source detection module and sends the weak current signal real-time data to the weak current signal analysis module; the signal database is used for storing weak current signal standard data of different weak current devices;
the weak current signal analysis module is used for analyzing weak current signals of weak current equipment in the effective data set, and the analysis process is specifically as follows;
acquiring the abnormal times of the power supply quality of the weak current equipment in the effective data set, and taking the abnormal times of the power supply quality DETu, u=1, 2, … …, z and z as positive integers, wherein u represents the serial numbers of the weak current equipment in the effective data set;
then acquiring the abnormal time of the power supply quality of the weak current equipment in the effective data set, and calculating the difference value of adjacent abnormal time of the power supply quality to obtain the abnormal interval duration DJTu of the power supply quality of the weak current equipment in the effective data set;
finally, the power supply quality abnormality duration when the power supply quality of the weak current equipment is abnormal each time in the effective data set is obtained, and the power supply quality abnormality duration DCTu of the weak current equipment in the effective data set is obtained by adding and summing the power supply quality abnormality durations when the power supply quality of the weak current equipment is abnormal each time;
according to the formulaCalculating to obtain a stable device power supply quality value DWu of weak current devices in the effective data set, wherein a1, a2 and a3 are proportionality coefficients of fixed values, and the values of a1, a2 and a3 are all larger than zero;
if DWu is less than X1, the abnormal device power supply quality coefficient of weak current devices in the effective data set is q1;
if X1 is less than or equal to DWu and less than X2, the abnormal device power supply quality coefficient of weak current devices in the effective data set is q2;
if X2 is less than or equal to DWu, the abnormal device power supply quality coefficient of weak current devices in the effective data set is q3; wherein X1 and X2 are equipment power supply quality stable thresholds with fixed values, X1 is smaller than X2, and q1, q2 and q3 are positive integers with fixed values, and q1 is smaller than q2 and smaller than q3;
the weak current signal analysis module sends the abnormal device power supply quality coefficient of the weak current device in the effective data set to the power supply quality verification module through the server; the equipment state analysis module is used for analyzing the equipment state condition of weak current equipment in the effective data set, and the analysis process is specifically as follows;
acquiring the continuous use time length of the weak current equipment in the effective data set, and acquiring the continuous use time length STu of the weak current equipment in the effective data set;
acquiring the real-time temperature of the element of the weak current equipment in the effective data set, and subtracting the absolute value from the standard temperature of the element to obtain the real-time temperature difference SCu of the weak current equipment in the effective data set;
acquiring the equipment dust accumulation degree of each weak current equipment in the effective data set, and marking the equipment dust accumulation degree as SDu;
calculating to obtain an equipment abnormality risk value SYFu of weak current equipment in an effective data set according to a formula SYFu= STu ×b1+SCu×b2+SDu×b3, wherein b1, b2 and b3 are proportionality coefficients with fixed values, and the values of b1, b2 and b3 are all larger than zero;
if SYFu is less than Y1, the equipment abnormality risk coefficient of weak current equipment in the effective data set is r1;
if Y1 is less than or equal to SYFu and less than Y2, the equipment abnormality risk coefficient of weak current equipment in the effective data set is r2;
if Y2 is less than or equal to SYFu, the equipment abnormality risk coefficient of weak current equipment in the effective data set is r3; wherein Y1 and Y2 are equipment abnormality risk thresholds with fixed values, Y1 is smaller than Y2, and simultaneously, r1, r2 and r3 are positive integers with fixed values, and r1 is smaller than r2 and r3;
the device state analysis module sends the device abnormality risk coefficient of the weak current device in the effective data set to the power supply quality verification module through the server;
the power supply quality verification module is used for setting the power supply abnormality risk level of the weak current equipment in the effective data set, and the setting process is specifically as follows:
acquiring an equipment abnormal risk coefficient and an equipment power supply quality abnormal coefficient, and marking the equipment abnormal risk coefficient and the equipment power supply quality abnormal coefficient as DRXu and DQXu;
calculating according to a formula ERu =DRXc1+DQXu×c2 to obtain a power supply abnormality risk value ERu of weak current equipment in the effective data set; wherein, c1 and c2 are weight coefficients with fixed values, and the values of c1 and c2 are larger than zero, and c1+c2=1;
acquiring a power supply abnormality risk threshold stored in a server, and comparing the power supply abnormality risk threshold with a power supply abnormality risk value of each weak current device in an effective data set;
the power supply abnormality risk threshold comprises a first power supply abnormality risk threshold and a second power supply abnormality risk threshold, and the first power supply abnormality risk threshold is smaller than the second power supply abnormality risk threshold;
if the power supply abnormality risk value is smaller than the first power supply abnormality risk threshold value, the power supply abnormality risk level of the weak current equipment in the effective data set is a third power supply abnormality risk level;
if the power supply abnormality risk value is greater than or equal to the first power supply abnormality risk threshold and smaller than the second power supply abnormality risk threshold, the power supply abnormality risk level of the weak current equipment in the effective data set is the second power supply abnormality risk level;
if the power supply abnormality risk value is greater than or equal to the second power supply abnormality risk threshold value, the power supply abnormality risk level of the weak current equipment in the effective data set is a first power supply abnormality risk level;
the power supply quality verification module feeds back the power supply abnormality risk level to the server, and the server sets a corresponding quantity of detection comparison groups for weak current equipment in the effective data set according to the power supply abnormality risk level and sends the detection comparison groups to the abnormality source detection module; the data acquisition module is used for acquiring abnormal source data of the weak current equipment in the effective data set, corresponding to the detection control set in an abnormal operation state, and sending the abnormal source data to the abnormal source detection module through the server; the abnormal source detection module is used for detecting equipment abnormal source data of weak current equipment in the effective data set, generating equipment power supply abnormal signals or equipment power supply normal signals and feeding the equipment power supply abnormal signals back to the server, if the server receives the equipment power supply normal signals, no operation is performed, if the server receives the equipment power supply abnormal signals, the equipment power supply abnormal signals are sent to the monitoring terminal, and the monitoring terminal is used for checking appointed weak current equipment after receiving the equipment power supply abnormal signals.
2. The weak current equipment power supply monitoring system based on data analysis according to claim 1, wherein the equipment state data is equipment continuous use duration, element real-time temperature, dust accumulation degree, element real-time current, element real-time voltage and element real-time resistance of weak current equipment in the effective data set;
the weak current signal real-time data are the abnormal times of the power supply quality of weak current equipment in the effective data set, the duration of the abnormal power supply quality when the power supply quality is abnormal each time and the abnormal power supply quality time;
the weak current signal standard data are the abnormal times of the power supply quality standard of the weak current equipment, the standard duration time when the power supply quality is abnormal each time and the abnormal time node of the power supply quality standard;
the abnormal source data is an element abnormal current value, an element abnormal voltage value and an element abnormal resistance value when weak current equipment in the effective data set is correspondingly detected to be in an abnormal operation state of the control group.
3. The weak current equipment power supply monitoring system based on data analysis according to claim 1, wherein the equipment power supply quality stable value is in direct proportion to the equipment power supply quality abnormal coefficient, namely, the larger the value of the equipment power supply quality stable value is, the larger the value of the equipment power supply quality abnormal coefficient is.
4. The weak current equipment power supply monitoring system based on data analysis according to claim 1, wherein the equipment abnormality risk value is in direct proportion to the equipment abnormality risk coefficient, that is, the larger the value of the equipment abnormality risk value is, the larger the value of the equipment abnormality risk coefficient is.
5. The weak electric device power supply monitoring system based on data analysis of claim 1, wherein the power supply abnormality risk threshold comprises a first power supply abnormality risk threshold and a second power supply abnormality risk threshold, and the first power supply abnormality risk threshold is less than the second power supply abnormality risk threshold;
the third power supply abnormality risk level is lower than the second power supply abnormality risk level, which is lower than the first power supply abnormality risk level.
6. The weak current equipment power supply monitoring system based on data analysis of claim 1, wherein the number of detection control groups is the first number of detection control groups if the first power supply abnormality risk level is;
if the power supply is at the second abnormal power supply risk level, the number of the detection control groups is the number of the second detection control groups;
if the power supply is at the third abnormal power supply risk level, the number of the detection control groups is the number of the third detection control groups;
wherein, the value of the first detection control group number is larger than the value of the second detection control group number, and the value of the second detection control group number is larger than the value of the third detection control group number.
7. The weak current equipment power supply monitoring system based on data analysis according to claim 6, wherein the detection method of the abnormality source detection module is specifically as follows:
acquiring a detection comparison group of the appointed number of weak current devices in an effective data group;
then obtaining an element abnormal current value, an element abnormal voltage value and an element abnormal resistance value of the weak current equipment corresponding detection control group in the effective data group;
traversing and comparing the element abnormal current values of the corresponding detection control group of the weak current devices in the effective data group to obtain element abnormal power minimum values and element abnormal power minimum values of the corresponding detection control group of the weak current devices in the effective data group, wherein the element abnormal power minimum values and the element abnormal power minimum values jointly form an element abnormal current interval of the detection control group;
similarly, an element abnormal voltage interval and an element abnormal resistance interval of the detection control group are obtained;
acquiring element real-time current, element real-time voltage and element real-time resistance of weak current equipment in an effective data set;
if any one of the element real-time current in the element abnormal current interval, the element real-time voltage in the element abnormal voltage interval or the element real-time resistance in the element abnormal resistance interval is met, generating an equipment power supply abnormal signal;
and if all the items that the element real-time current is not in the element abnormal current interval, the element real-time voltage is not in the element abnormal voltage interval and the element real-time resistance is not in the element abnormal resistance interval are satisfied, generating an equipment power supply abnormal signal.
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| CN114819758A (en) * | 2022-06-27 | 2022-07-29 | 深圳市博硕科技股份有限公司 | Die-cutting machine product thickness abnormity detection system |
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| CN114819758A (en) * | 2022-06-27 | 2022-07-29 | 深圳市博硕科技股份有限公司 | Die-cutting machine product thickness abnormity detection system |
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