CN117060594B - Power distribution operation monitoring system based on Internet of things - Google Patents
Power distribution operation monitoring system based on Internet of things Download PDFInfo
- Publication number
- CN117060594B CN117060594B CN202311307748.1A CN202311307748A CN117060594B CN 117060594 B CN117060594 B CN 117060594B CN 202311307748 A CN202311307748 A CN 202311307748A CN 117060594 B CN117060594 B CN 117060594B
- Authority
- CN
- China
- Prior art keywords
- value
- risk
- preset
- signal
- evaluation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000009826 distribution Methods 0.000 title claims abstract description 108
- 238000012544 monitoring process Methods 0.000 title claims abstract description 31
- 238000011156 evaluation Methods 0.000 claims abstract description 147
- 238000004458 analytical method Methods 0.000 claims abstract description 53
- 238000012423 maintenance Methods 0.000 claims abstract description 17
- 230000005540 biological transmission Effects 0.000 claims description 62
- 238000012502 risk assessment Methods 0.000 claims description 41
- 230000007613 environmental effect Effects 0.000 claims description 17
- 238000010606 normalization Methods 0.000 claims description 14
- 238000000034 method Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 13
- 230000001154 acute effect Effects 0.000 claims description 6
- 230000007306 turnover Effects 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 238000012937 correction Methods 0.000 claims description 3
- 238000005336 cracking Methods 0.000 claims description 3
- 238000004146 energy storage Methods 0.000 claims description 3
- 238000009423 ventilation Methods 0.000 claims description 3
- 230000010354 integration Effects 0.000 abstract description 3
- 230000000694 effects Effects 0.000 description 13
- 238000004891 communication Methods 0.000 description 6
- 238000005457 optimization Methods 0.000 description 4
- 238000007689 inspection Methods 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000010921 in-depth analysis Methods 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
Classifications
-
- 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
- H02J13/00001—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 the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
-
- 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
Abstract
The invention relates to the technical field of power distribution operation monitoring, in particular to a power distribution operation monitoring system based on the Internet of things, which comprises a monitoring platform, a data acquisition unit, an operation supervision unit, an operation and maintenance management unit, a delay feedback unit, an alarm display unit, a self-checking analysis unit and a management evaluation unit, wherein the monitoring platform is used for monitoring the power distribution operation of the power distribution system; according to the invention, the distribution equipment is analyzed in a whole-to-scattered manner, namely, the distribution equipment is firstly subjected to operation state monitoring evaluation analysis in a whole manner so as to reasonably manage the distribution equipment, so that the operation safety of the distribution equipment is improved, the early warning equipment is subjected to operation self-checking feedback evaluation analysis in a scattered manner so as to ensure the timeliness and effectiveness of early warning of the distribution equipment, and in-depth pipe control alarm analysis is performed in a data integration manner, so that the accuracy of analysis evaluation results is improved, and the distribution equipment is subjected to reasonable and accurate early warning management according to different feedback information, and the early warning manner and the early warning level are timely changed in combination with delay conditions.
Description
Technical Field
The invention relates to the technical field of power distribution operation monitoring, in particular to a power distribution operation monitoring system based on the Internet of things.
Background
The power distribution room is a facility for receiving, distributing, controlling and protecting electric energy, life and work of people are not separated from electric power in modern society, higher requirements are put on safety and stability of a power grid, the power distribution room is an important component of the power grid, and the power distribution room is an important link for connecting a power grid side and a user side and is an important link for operation and maintenance of the power grid;
the traditional operation and maintenance management mode of the power distribution room cannot meet the requirements of user demands and refined management of the power grid, the traditional operation and maintenance mode adopts manual inspection, the requirement on the configuration quantity of personnel is high, the requirement on the professional performance is high, the inspection personnel must watch on duty beside the power distribution room, inspection and recording of equipment operation data are performed at regular time, time and labor are wasted, however, in the prior art, the problem that analysis errors of operation and early warning conditions of the power distribution equipment are large exists when the power distribution equipment is monitored, and further the management precision of the power distribution equipment is reduced, and the early warning mode, the early warning level and the management operation cannot be changed in time in combination with the early warning delay condition, so that the power distribution equipment is improper in management and poor in management effect are caused;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a distribution operation monitoring system based on the Internet of things, which solves the technical defects of the prior art, the distribution equipment is analyzed in a whole-to-loose mode, namely, the distribution equipment is firstly subjected to operation state monitoring evaluation analysis in a whole mode so as to reasonably manage the distribution equipment, the operation safety of the distribution equipment is improved, the early warning equipment is subjected to operation self-checking feedback evaluation analysis in a loose mode so as to judge whether the early warning equipment normally warns, the timeliness and the effectiveness of early warning of the distribution equipment are ensured, the interference data of the distribution equipment which does not receive the signal early warning is subjected to early warning interference supervision evaluation operation in an information feedback mode, the equipment does not receive the risk signal and is influenced by the interference data so as to timely carry out management and control adjustment, the early warning data of the received risk signal is subjected to deep analysis so as to timely carry out management and control adjustment on the distribution equipment, the accuracy of analysis evaluation results is improved, and the early warning equipment is reasonably and accurately managed according to different feedback information so as to improve the rationality of early warning and management of the distribution equipment.
The aim of the invention can be achieved by the following technical scheme: the power distribution operation monitoring system based on the Internet of things comprises a monitoring platform, a data acquisition unit, an operation supervision unit, an operation and maintenance management unit, a delay feedback unit, an alarm display unit, a self-checking analysis unit and a management evaluation unit;
when the monitoring platform generates a management command, the management command is sent to the data acquisition unit, the data acquisition unit immediately acquires operation data of the power distribution equipment after receiving the management command, the operation data comprises an environmental influence value, an equipment representation value and an operation value, the operation data is sent to the operation monitoring unit, the operation monitoring unit immediately monitors, evaluates and analyzes the operation state of the operation data after receiving the operation data, and sends an obtained risk signal to the operation and maintenance management unit and the delay feedback unit;
the delay feedback unit immediately acquires early warning data of early warning equipment after receiving the risk signal, wherein the early warning data comprises a response value and an equipment evaluation value, and performs self-checking feedback evaluation analysis on the early warning data to obtain a delay risk evaluation coefficient W, a fault signal and a delay instruction, the obtained fault signal is sent to the alarm display unit and the self-checking analysis unit, and the obtained delay instruction is sent to the management evaluation unit;
the self-checking analysis unit immediately acquires interference data of the power distribution equipment after receiving the fault signal, wherein the interference data comprises a signal Zhou Zhuaizhi and a transmission risk value, performs early warning interference supervision and evaluation operation on the interference data, and sends an obtained optimized signal to the alarm display unit through the management evaluation unit;
and after receiving the delay instruction, the management evaluation unit immediately carries out deep management alarm analysis on the delay risk evaluation coefficient W corresponding to the delay instruction, and sends the obtained primary management signal and risk signal or the next primary management signal and risk signal to the alarm display unit.
Preferably, the operation state monitoring, evaluating and analyzing process of the operation supervision unit is as follows:
s1: acquiring the duration of the power distribution equipment in a period of time, marking the duration as a time threshold, dividing the time threshold into i sub-time nodes, wherein i is a natural number larger than zero, acquiring environment influence values of the power distribution equipment in each sub-time node, wherein the environment influence values represent the total number of the equipment in which the operating temperature, the internal environment humidity and the ventilation quantity in unit time are respectively larger than corresponding preset values, acquiring equipment representation values of the power distribution equipment in each sub-time node, wherein the equipment representation values represent the total number of the equipment abnormal sound values, the equipment vibration amplitude and the like which are respectively larger than the corresponding preset values, acquiring the operating values of the power distribution equipment in each sub-time node, wherein the operating values represent product values obtained by carrying out data normalization processing on the average operating voltage and the fault frequency of the power distribution equipment in each sub-time node, and marking the environment influence values, the equipment representation values and the operating values as HYi, SBi and YXi;
s2: according to a formula, obtaining an operation health evaluation coefficient Pi of power distribution equipment in each sub-time node, taking the number of sub-time nodes as an X axis, taking the operation health evaluation coefficient Pi as a Y axis, establishing a rectangular coordinate system, drawing an operation health evaluation coefficient curve in a dot drawing mode, drawing a preset operation health evaluation coefficient threshold curve in the coordinate system, further obtaining an acute angle degree formed by first intersecting the operation health evaluation coefficient curve and the preset operation health evaluation coefficient threshold curve from the coordinate system, marking the acute angle degree as a risk angle, simultaneously obtaining the length of a line segment corresponding to a line segment of the operation health evaluation coefficient curve above the preset operation health evaluation coefficient threshold curve, marking the length of the line segment as an influence length and a risk line segment value, marking the product value obtained by carrying out data normalization on the influence length and the risk line segment value as a risk evaluation value, and comparing the risk angle and the risk evaluation value with a preset risk angle threshold value and a preset risk evaluation value stored in the risk angle threshold and the risk evaluation value to analyze the risk angle threshold value:
if the risk angle is smaller than the preset risk angle threshold value and the risk evaluation value is smaller than the preset risk evaluation value threshold value, no signal is generated;
and if the risk angle is greater than or equal to a preset risk angle threshold value or the risk evaluation value is greater than or equal to a preset risk evaluation value threshold value, generating a risk signal.
Preferably, the operation self-checking feedback evaluation analysis process of the delay feedback unit is as follows:
obtaining a response value of the power distribution equipment in the time threshold, wherein the response value represents the time length between the moment when the operation supervision unit generates the risk signal and the moment when the operation and maintenance management unit receives the risk signal, and performing discriminant analysis on the response:
if the response value is equal to zero, generating a fault signal;
and if the response value is not equal to zero, generating a feedback instruction.
Preferably, when the delay feedback unit generates a feedback instruction:
t1: acquiring a device evaluation value of early warning device in a time threshold, wherein the device evaluation value represents a product value obtained by carrying out data normalization processing on a time length from the moment when the early warning device receives a risk signal to the moment when an early warning operation is carried out and an operation span value, wherein the operation span value represents a difference value between an operation power maximum value and an operation power maximum value of the early warning device in the time threshold, and comparing the device evaluation value with a stored preset device evaluation value threshold, if the device evaluation value is larger than the preset device evaluation value threshold, marking a part of the device evaluation value larger than the preset device evaluation value threshold as a risk early warning value, acquiring an environmental impact value from an operation supervision unit, further constructing a set A of the environmental impact value, further acquiring a mean value of the set A, marking the mean value of the set A as an environmental interference value, and respectively marking a response value, the risk early warning value and the environmental interference value as XZ, FY and HG;
t2: according to the formulaObtaining a delay risk assessment coefficient, wherein f1, f2 and f3 are preset weight factor coefficients of a response value, a risk early warning value and an environment interference value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset correction factor coefficient, the value is 3.221, W is the delay risk assessment coefficient, and the delay risk assessment coefficient W is compared with a preset delay risk assessment coefficient threshold value recorded and stored in the delay risk assessment coefficient W:
if the ratio between the delay risk assessment coefficient W and the preset delay risk assessment coefficient threshold is smaller than 1, no signal is generated;
if the ratio between the delay risk assessment coefficient W and the preset delay risk assessment coefficient threshold is greater than 1, generating a delay instruction.
Preferably, the early warning interference supervision and evaluation operation process of the self-checking analysis unit is as follows:
TT1: acquiring a signal turnover value of power distribution equipment in a time threshold, wherein a signal Zhou Zhuaizhi represents the product value obtained by carrying out data normalization processing on the time length exceeding a preset time length between the time when a signal transceiver in the power distribution equipment receives the signal and the time when the signal is transmitted and the power supply fluctuation value, and the power supply fluctuation value represents the total time corresponding to the fluctuation amplitude exceeding the preset fluctuation amplitude threshold of the solar energy storage battery in a sub-time period;
TT2: acquiring a transmission risk value of the power distribution equipment in a time threshold, wherein the transmission risk value represents a ratio of the total cracking length of a transmission line in the power distribution equipment to the port contact area obtained after data normalization processing, comparing the transmission risk value with a stored preset transmission risk value threshold for analysis, and if the transmission risk value is larger than the preset transmission risk value threshold, marking a part of the transmission risk value larger than the preset transmission risk value threshold with a transmission power value;
comparing the signal Zhou Zhuaizhi with a preset signal turnover value threshold value and a preset transmission power value threshold value which are recorded and stored in the signal Zhou Zhuaizhi and the transmission power value to analyze the signal:
if the signal Zhou Zhuaizhi is less than the preset signal Zhou Zhuaizhi threshold and the transmission power value is less than the preset transmission power value threshold, no signal is generated;
if the signal Zhou Zhuaizhi is greater than or equal to the preset signal Zhou Zhuaizhi threshold, or the transmission power value is greater than or equal to the preset transmission power value threshold, an optimization signal is generated.
Preferably, the in-depth management alarm analysis process of the management evaluation unit is as follows:
acquiring a part of the delay risk assessment coefficient W which is larger than a preset delay risk assessment coefficient threshold value, marking the part of the delay risk assessment coefficient W which is larger than the preset delay risk assessment coefficient threshold value as a delay value, simultaneously calling a signal rotation value and a transmission power value from a self-checking analysis unit, and respectively marking the delay value, the signal Zhou Zhuaizhi and the transmission power value as YZ, ZZ and CB;
according to the formulaObtaining a control evaluation coefficient, wherein v1, v2 and v3 are respectively delay values, signals Zhou Zhuaizhi and preset influence factor coefficients of transmission power values, v1, v2 and v3 are positive numbers larger than zero, v4 is a preset compensation factor coefficient, the value is 2.296, G is the control evaluation coefficient, and the control evaluation coefficient G is compared with a preset control evaluation coefficient threshold value recorded and stored in the control evaluation coefficient G:
if the management and control evaluation coefficient G is smaller than a preset management and control evaluation coefficient threshold value, generating a first-level management signal;
and if the management and control evaluation coefficient G is greater than or equal to a preset management and control evaluation coefficient threshold value, generating a next-stage management signal.
The beneficial effects of the invention are as follows:
(1) According to the invention, the distribution equipment is analyzed in a whole-to-loose mode, namely, the operation state of the distribution equipment is monitored, evaluated and analyzed in a whole mode, so that the operation state of the distribution equipment is known, the distribution equipment is managed reasonably, the operation safety of the distribution equipment is improved, and the early warning equipment is subjected to operation self-checking feedback evaluation and analysis in a loose mode, so that whether the early warning equipment normally warns or not is judged, early warning optimization treatment is performed timely, and the timeliness and effectiveness of early warning of the distribution equipment are guaranteed;
(2) According to the invention, the interference data of the power distribution equipment which does not receive the signal early warning is subjected to early warning interference supervision and evaluation operation in an information feedback mode, whether the equipment does not receive the risk signal is influenced by the interference data or not is judged, so that the early warning effect of the power distribution equipment is guaranteed, the early warning data of the early warning equipment which receives the risk signal is subjected to deep analysis, whether the early warning equipment early warning has a delay problem or not is judged, so that the early warning equipment is subjected to the deep supervision and adjustment in time, the analysis of deep supervision and alarm is carried out in a data integration mode, the accuracy of analysis and evaluation results is improved, the power distribution equipment is reasonably and accurately subjected to early warning management according to different feedback information, the early warning mode and the early warning level are timely changed in combination with the delay condition, the early warning effect and the management rationality of the power distribution equipment are improved, and the management effect of the power distribution equipment is improved on the side.
Drawings
FIG. 1 is a flow chart of the system of the present invention;
fig. 2 is a partial analysis reference diagram 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:
referring to fig. 1 to 2, the invention discloses a power distribution operation monitoring system based on the internet of things, which comprises a monitoring platform, a data acquisition unit, an operation supervision unit, an operation maintenance management unit, a delay feedback unit, an alarm display unit, a self-checking analysis unit and a management evaluation unit, wherein the monitoring platform is in unidirectional communication connection with the data acquisition unit, the data acquisition unit is in unidirectional communication connection with the operation supervision unit, the operation supervision unit is in unidirectional communication connection with the operation maintenance management unit and the delay feedback unit, the delay feedback unit is in unidirectional communication connection with the alarm display unit, the self-checking analysis unit and the management evaluation unit, the self-checking analysis unit is in unidirectional communication connection with the management evaluation unit, and the management evaluation unit is in unidirectional communication connection with the alarm display unit;
when the monitoring platform generates a management command and sends the management command to the data acquisition unit, the data acquisition unit immediately acquires operation data of the power distribution equipment after receiving the management command, the operation data comprises an environmental influence value, an equipment representation value and an operation value, and sends the operation data to the operation monitoring unit, and the operation monitoring unit immediately monitors, evaluates and analyzes the operation state of the operation data after receiving the operation data so as to know the operation state of the power distribution equipment, so that the power distribution equipment is managed reasonably, the operation safety of the power distribution equipment is improved, and the specific operation state monitoring, evaluating and analyzing process is as follows:
acquiring the duration of the operation of the power distribution equipment for a period of time, marking the duration as a time threshold, dividing the time threshold into i sub-time nodes, i is a natural number larger than zero, acquiring environment influence values of the power distribution equipment in each sub-time node, wherein the environment influence values represent the total number of the equipment, such as the operation temperature, the internal environment humidity, the ventilation quantity in unit time and the like, which are respectively larger than corresponding preset values, simultaneously acquiring equipment representation values of the power distribution equipment in each sub-time node, wherein the equipment representation values represent the total number of the equipment abnormal sound values, the equipment vibration amplitude and the like which are respectively larger than corresponding preset values, acquiring operation values of the power distribution equipment in each sub-time node, wherein the operation values represent the integrated values of the average operation voltage and the failure frequency of the equipment in the sub-time nodes, and respectively label the environment influence values as HYi, SBi and YXi;
according to the formulaObtaining operation health evaluation coefficients of power distribution equipment in each sub-time node, wherein a1, a2 and a3 are respectively preset scale factor coefficients of environment influence values, equipment representation values and operation values, the scale factor coefficients are used for correcting deviation of various parameters in a formula calculation process, so that calculation results are more accurate, a1, a2 and a3 are positive numbers larger than zero, a4 is a preset fault tolerance factor coefficient, the value is 1.768, pi is the operation health evaluation coefficient of the power distribution equipment in each sub-time node, the number of sub-time nodes is X-axis, and the operation health evaluation coefficient Pi is Y-axis to establish a straight lineThe system comprises an angular coordinate system, wherein an operation health evaluation coefficient curve is drawn in a dot drawing mode, a preset operation health evaluation coefficient threshold curve is drawn in the coordinate system at the same time, further, an acute angle degree formed by the first intersection of the operation health evaluation coefficient curve and the preset operation health evaluation coefficient threshold curve is obtained from the coordinate system, the acute angle degree is marked as a risk angle, the time length and the line length corresponding to a line segment of the operation health evaluation coefficient curve above the preset operation health evaluation coefficient threshold curve are obtained, the time length and the line segment length are respectively marked as an influence time length and a risk line segment value, the product value obtained by carrying out data normalization on the influence time length and the risk line segment value is marked as a risk evaluation value, and the risk angle and the risk evaluation value are compared with a preset risk angle threshold and a preset risk evaluation value which are recorded and stored in the risk angle and the risk evaluation value are analyzed:
if the risk angle is smaller than the preset risk angle threshold value and the risk evaluation value is smaller than the preset risk evaluation value threshold value, no signal is generated;
if the risk angle is greater than or equal to a preset risk angle threshold value or the risk evaluation value is greater than or equal to a preset risk evaluation value threshold value, generating a risk signal, and sending the risk signal to an operation and maintenance management unit and a delay feedback unit, wherein the operation and maintenance management unit immediately makes a preset early warning operation corresponding to the risk signal after receiving the risk signal so as to remind an operation and maintenance staff to timely manage and maintain the power distribution equipment, so that the operation safety and the supervision early warning effect of the power distribution equipment are improved;
the delay feedback unit immediately acquires early warning data of early warning equipment after receiving the risk signal, wherein the early warning data comprises a response value and an equipment evaluation value, and performs operation self-checking feedback evaluation analysis on the early warning data to judge whether the early warning equipment normally early warning so as to perform optimization processing in time, so as to ensure timeliness and effectiveness of early warning of the power distribution equipment, and the specific operation self-checking feedback evaluation analysis process is as follows:
obtaining a response value of the power distribution equipment in the time threshold, wherein the response value represents the time length between the moment when the operation supervision unit generates the risk signal and the moment when the operation and maintenance management unit receives the risk signal, and performing discriminant analysis on the response:
if the response value is equal to zero, generating a fault signal, and sending the fault signal to an alarm display unit and a self-checking analysis unit, wherein the alarm display unit immediately displays preset early warning characters corresponding to the fault signal after receiving the fault signal, so that the power distribution equipment is maintained in time, and the timeliness and the effectiveness of early warning of the power distribution equipment are ensured;
if the response value is not equal to zero, generating a feedback instruction, when the feedback instruction is generated, acquiring a device evaluation value of the early warning device in a time threshold, wherein the device evaluation value represents a product value obtained by carrying out data normalization processing on a time length from the moment when the early warning device receives a risk signal to the moment when the early warning device executes an early warning operation, the operation span value represents a difference value between an operation power maximum value and an operation power maximum value of the early warning device in the time threshold, the device evaluation value is compared with a stored preset device evaluation value threshold, if the device evaluation value is larger than the preset device evaluation value threshold, a part of the device evaluation value which is larger than the preset device evaluation value threshold is marked as a risk early warning value, meanwhile, an environmental impact value is acquired from an operation supervision unit, a set A of the environmental impact value is further constructed, an average value of the set A is acquired, the average value of the set A is marked as an environmental interference value, the response value, the risk value and the environmental interference value are respectively marked as XZ, FY and HG, and the fact that the larger the response value, the risk early warning value and the corresponding value and the environmental interference value are needed is, if the larger, the early warning device is larger, and the larger the risk is unfavorable to manage and the risk and delay result is caused by the larger;
according to the formulaObtaining a delay risk assessment coefficient, wherein f1, f2 and f3 are preset weight factor coefficients of a response value, a risk early warning value and an environment interference value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset correction factor coefficient, the value is 3.221, W is the delay risk assessment coefficient, and the delay risk assessment coefficient W and the preset delay risk assessment coefficient which is recorded and stored in the delay risk assessment coefficient are obtainedThreshold value comparison analysis:
if the ratio between the delay risk assessment coefficient W and the preset delay risk assessment coefficient threshold is smaller than 1, no signal is generated;
if the ratio between the deferred risk assessment coefficient W and the preset deferred risk assessment coefficient threshold is greater than 1, generating a deferred instruction, and sending the deferred instruction to the management assessment unit.
Embodiment two:
the self-checking analysis unit immediately collects interference data of the power distribution equipment after receiving the fault signal, the interference data comprise a signal Zhou Zhuaizhi and a transmission risk value, and performs early warning interference supervision and evaluation operation on the interference data, and judges whether the operation and maintenance management unit does not receive the influence of the signal Zhou Zhuaizhi and the transmission risk value, so that management and control adjustment can be performed timely to ensure the early warning effect of the power distribution equipment, and the specific early warning interference supervision and evaluation operation process is as follows:
acquiring a signal turnover value of power distribution equipment in a time threshold, wherein a signal Zhou Zhuaizhi represents a product value obtained by carrying out data normalization processing on the time length from the time point of receiving the signal to the time point of sending the signal by a signal transceiver in the power distribution equipment and a power supply fluctuation value, the power supply fluctuation value represents the total time length corresponding to the time period when the fluctuation amplitude of a solar energy storage battery exceeds a preset fluctuation amplitude threshold, and the larger the value of a signal Zhou Zhuaizhi is, the larger the risk of abnormal operation is;
acquiring a transmission risk value of the power distribution equipment in a time threshold, wherein the transmission risk value represents a ratio of the total cracking length of a transmission line in the power distribution equipment to the port contact area obtained after data normalization processing, and comparing the transmission risk value with a stored preset transmission risk value threshold for analysis, and if the transmission risk value is larger than the preset transmission risk value threshold, marking a part of the transmission risk value larger than the preset transmission risk value threshold with a transmission power value, wherein the transmission power value is an influence parameter reflecting the signal transmission of the power distribution equipment;
comparing the signal Zhou Zhuaizhi with a preset signal turnover value threshold value and a preset transmission power value threshold value which are recorded and stored in the signal Zhou Zhuaizhi and the transmission power value to analyze the signal:
if the signal Zhou Zhuaizhi is less than the preset signal Zhou Zhuaizhi threshold and the transmission power value is less than the preset transmission power value threshold, no signal is generated;
if the signal Zhou Zhuaizhi is greater than or equal to a preset signal Zhou Zhuaizhi threshold value or the transmission multiplying power value is greater than or equal to a preset transmission multiplying power value threshold value, generating an optimized signal, sending the optimized signal to an alarm display unit through a management evaluation unit, and immediately displaying preset early warning characters corresponding to the optimized signal by the alarm display unit after receiving the optimized signal, so that early warning equipment is managed and adjusted in time to ensure the early warning effect of the power distribution equipment;
after receiving the delay instruction, the management evaluation unit immediately carries out deep management control alarm analysis on the delay risk evaluation coefficient W corresponding to the delay instruction so as to improve the early warning effect of the power distribution equipment, and meanwhile, the management effect on the power distribution equipment is improved by the side face, and the specific deep management control alarm analysis process is as follows:
acquiring a part of the delay risk assessment coefficient W which is larger than a preset delay risk assessment coefficient threshold value, marking the part of the delay risk assessment coefficient W which is larger than the preset delay risk assessment coefficient threshold value as a delay value, simultaneously calling a signal rotation value and a transmission power value from a self-checking analysis unit, and respectively marking the delay value, the signal Zhou Zhuaizhi and the transmission power value as YZ, ZZ and CB;
according to the formulaObtaining a control evaluation coefficient, wherein v1, v2 and v3 are respectively delay values, signals Zhou Zhuaizhi and preset influence factor coefficients of transmission power values, v1, v2 and v3 are positive numbers larger than zero, v4 is a preset compensation factor coefficient, the value is 2.296, G is the control evaluation coefficient, and the control evaluation coefficient G is compared with a preset control evaluation coefficient threshold value recorded and stored in the control evaluation coefficient G:
if the management and control evaluation coefficient G is smaller than a preset management and control evaluation coefficient threshold value, generating a first-level management signal;
if the management and control evaluation coefficient G is greater than or equal to a preset management and control evaluation coefficient threshold value, generating a next-level management signal, and sending the next-level management signal and the risk signal or the next-level management signal and the risk signal to an alarm display unit, wherein after the alarm display unit receives the first-level management signal and the risk signal or the next-level management signal and the risk signal, the alarm display unit immediately displays preset early warning characters corresponding to the first-level management signal and the risk signal or the next-level management signal and the risk signal respectively, reasonably and accurately manages the power distribution equipment according to different feedback information, and timely changes an early warning mode and an early warning level in combination with a delay condition so as to improve the early warning effect and management rationality of the power distribution equipment, and meanwhile, the alarm display unit is beneficial to improving the management effect of the power distribution equipment on the side;
in summary, the power distribution equipment is analyzed in a whole-to-loose manner, namely, the power distribution equipment is monitored, evaluated and analyzed in an operation state so as to know the operation state of the power distribution equipment, the power distribution equipment is managed reasonably, the operation safety of the power distribution equipment is improved, the early warning equipment is subjected to operation self-checking feedback evaluation analysis in a loose manner so as to judge whether the early warning equipment normally warns or not, the early warning optimization processing is performed timely, the timeliness and effectiveness of the early warning of the power distribution equipment are guaranteed, the interference data of the power distribution equipment which does not receive the signal early warning are subjected to early warning interference supervision and evaluation operation in an information feedback manner, whether the equipment does not receive the risk signal is influenced by the interference data is judged, so as to timely perform control adjustment, the early warning data of the received risk signal are subjected to in-depth analysis, whether the early warning equipment has a delay problem or not is judged, the early warning equipment is subjected to control adjustment timely, the early warning analysis is performed in a data integration manner so as to help to improve the accuracy of analysis result, the early warning and the early warning effect is improved according to different feedback information, the reasonable management and the delay management of the power distribution equipment is reasonably performed, and the early warning management effect is improved at the same time.
The size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected.
The above formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and coefficients in the formulas are set by a person skilled in the art according to practical situations, and the above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art is within the technical scope of the present invention, and the technical scheme and the inventive concept according to the present invention are equivalent to or changed and are all covered in the protection scope of the present invention.
Claims (1)
1. The power distribution operation monitoring system based on the Internet of things is characterized by comprising a monitoring platform, a data acquisition unit, an operation supervision unit, an operation and maintenance management unit, a delay feedback unit, an alarm display unit, a self-checking analysis unit and a management evaluation unit;
when the monitoring platform generates a management command, the management command is sent to the data acquisition unit, the data acquisition unit immediately acquires operation data of the power distribution equipment after receiving the management command, the operation data comprises an environmental influence value, an equipment representation value and an operation value, the operation data is sent to the operation monitoring unit, the operation monitoring unit immediately monitors, evaluates and analyzes the operation state of the operation data after receiving the operation data, and sends an obtained risk signal to the operation and maintenance management unit and the delay feedback unit;
the delay feedback unit immediately acquires early warning data of early warning equipment after receiving the risk signal, wherein the early warning data comprises a response value and an equipment evaluation value, and performs self-checking feedback evaluation analysis on the early warning data to obtain a delay risk evaluation coefficient W, a fault signal and a delay instruction, the obtained fault signal is sent to the alarm display unit and the self-checking analysis unit, and the obtained delay instruction is sent to the management evaluation unit;
the self-checking analysis unit immediately acquires interference data of the power distribution equipment after receiving the fault signal, wherein the interference data comprises a signal Zhou Zhuaizhi and a transmission risk value, performs early warning interference supervision and evaluation operation on the interference data, and sends an obtained optimized signal to the alarm display unit through the management evaluation unit;
after receiving the delay instruction, the management evaluation unit immediately carries out deep management control alarm analysis on a delay risk evaluation coefficient W corresponding to the delay instruction, and sends an obtained primary management signal and risk signal or a next primary management signal and risk signal to an alarm display unit;
the operation state monitoring, evaluating and analyzing process of the operation supervision unit is as follows:
s1: acquiring the duration of the power distribution equipment in a period of time, marking the duration as a time threshold, dividing the time threshold into i sub-time nodes, wherein i is a natural number larger than zero, acquiring environment influence values of the power distribution equipment in each sub-time node, wherein the environment influence values represent the total number of the equipment, such as the running temperature, the internal environment humidity, the ventilation quantity in unit time and the like, which are respectively larger than corresponding preset values, simultaneously acquiring equipment representation values of the power distribution equipment in each sub-time node, wherein the equipment representation values represent the total number of the equipment abnormal sound values, the equipment vibration amplitude and the like which are respectively larger than corresponding preset values, acquiring the running values of the power distribution equipment in each sub-time node, wherein the running values represent product values obtained by carrying out data normalization processing on the average running voltage and the fault frequency of the equipment in the sub-time node, and marking the environment influence values, the equipment representation values and the running values as HYi, SBi and YXi;
s2: according to the formulaObtaining operation health evaluation coefficients Pi of power distribution equipment in each sub-time node, wherein a1, a2 and a3 are preset scale factor coefficients of an environmental impact value, an equipment representation value and an operation value respectively, a1, a2 and a3 are positive numbers larger than zero, and a4 is a preset numberSetting a fault tolerance factor coefficient, namely 1.768, setting the number of sub-time nodes as an X axis, setting an orthogonal coordinate system with an operation health evaluation coefficient Pi as a Y axis, drawing an operation health evaluation coefficient curve in a dot drawing mode, drawing a preset operation health evaluation coefficient threshold curve in the coordinate system, further acquiring an acute angle degree formed by first intersection of the operation health evaluation coefficient curve and the preset operation health evaluation coefficient threshold curve from the coordinate system, marking the acute angle degree as a risk angle, simultaneously acquiring a duration and a line length corresponding to a line segment of the operation health evaluation coefficient curve above the preset operation health evaluation coefficient threshold curve, marking the duration and the line segment length as an influence duration and a risk line segment value respectively, marking the product value obtained by carrying out data normalization on the influence duration and the risk line segment value as a risk evaluation value, and comparing the risk angle and the risk evaluation value with a preset risk angle threshold value and a preset risk evaluation value stored in the internal record of the risk angle and the risk evaluation value:
if the risk angle is smaller than the preset risk angle threshold value and the risk evaluation value is smaller than the preset risk evaluation value threshold value, no signal is generated;
if the risk angle is greater than or equal to a preset risk angle threshold value or the risk assessment value is greater than or equal to a preset risk assessment value threshold value, generating a risk signal;
the operation self-checking feedback evaluation analysis process of the delay feedback unit is as follows:
obtaining a response value of the power distribution equipment in the time threshold, wherein the response value represents the time length between the moment when the operation supervision unit generates the risk signal and the moment when the operation and maintenance management unit receives the risk signal, and performing discriminant analysis on the response:
if the response value is equal to zero, generating a fault signal;
if the response value is not equal to zero, generating a feedback instruction;
when the delay feedback unit generates a feedback instruction:
t1: acquiring a device evaluation value of early warning device in a time threshold, wherein the device evaluation value represents a product value obtained by carrying out data normalization processing on a time length from the moment when the early warning device receives a risk signal to the moment when an early warning operation is carried out and an operation span value, wherein the operation span value represents a difference value between an operation power maximum value and an operation power maximum value of the early warning device in the time threshold, and comparing the device evaluation value with a stored preset device evaluation value threshold, if the device evaluation value is larger than the preset device evaluation value threshold, marking a part of the device evaluation value larger than the preset device evaluation value threshold as a risk early warning value, acquiring an environmental impact value from an operation supervision unit, further constructing a set A of the environmental impact value, further acquiring a mean value of the set A, marking the mean value of the set A as an environmental interference value, and respectively marking a response value, the risk early warning value and the environmental interference value as XZ, FY and HG;
t2: according to the formulaObtaining a delay risk assessment coefficient, wherein f1, f2 and f3 are preset weight factor coefficients of a response value, a risk early warning value and an environment interference value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset correction factor coefficient, the value is 3.221, W is the delay risk assessment coefficient, and the delay risk assessment coefficient W is compared with a preset delay risk assessment coefficient threshold value recorded and stored in the delay risk assessment coefficient W:
if the ratio between the delay risk assessment coefficient W and the preset delay risk assessment coefficient threshold is smaller than 1, no signal is generated;
if the ratio between the delay risk assessment coefficient W and the preset delay risk assessment coefficient threshold is greater than 1, generating a delay instruction;
the early warning interference supervision and evaluation operation process of the self-checking analysis unit is as follows:
TT1: acquiring a signal turnover value of power distribution equipment in a time threshold, wherein a signal Zhou Zhuaizhi represents the product value obtained by carrying out data normalization processing on the time length exceeding a preset time length between the time when a signal transceiver in the power distribution equipment receives the signal and the time when the signal is transmitted and the power supply fluctuation value, and the power supply fluctuation value represents the total time corresponding to the fluctuation amplitude exceeding the preset fluctuation amplitude threshold of the solar energy storage battery in a sub-time period;
TT2: acquiring a transmission risk value of the power distribution equipment in a time threshold, wherein the transmission risk value represents a ratio of the total cracking length of a transmission line in the power distribution equipment to the port contact area obtained after data normalization processing, comparing the transmission risk value with a stored preset transmission risk value threshold for analysis, and if the transmission risk value is larger than the preset transmission risk value threshold, marking a part of the transmission risk value larger than the preset transmission risk value threshold with a transmission power value;
comparing the signal Zhou Zhuaizhi with a preset signal turnover value threshold value and a preset transmission power value threshold value which are recorded and stored in the signal Zhou Zhuaizhi and the transmission power value to analyze the signal:
if the signal Zhou Zhuaizhi is less than the preset signal Zhou Zhuaizhi threshold and the transmission power value is less than the preset transmission power value threshold, no signal is generated;
if the signal Zhou Zhuaizhi is greater than or equal to the preset signal Zhou Zhuaizhi threshold or the transmission power value is greater than or equal to the preset transmission power value threshold, generating an optimized signal;
the deep management control alarm analysis process of the management evaluation unit is as follows:
acquiring a part of the delay risk assessment coefficient W which is larger than a preset delay risk assessment coefficient threshold value, marking the part of the delay risk assessment coefficient W which is larger than the preset delay risk assessment coefficient threshold value as a delay value, simultaneously calling a signal rotation value and a transmission power value from a self-checking analysis unit, and respectively marking the delay value, the signal Zhou Zhuaizhi and the transmission power value as YZ, ZZ and CB;
according to the formulaObtaining a control evaluation coefficient, wherein v1, v2 and v3 are respectively delay values, signals Zhou Zhuaizhi and preset influence factor coefficients of transmission power values, v1, v2 and v3 are positive numbers larger than zero, v4 is a preset compensation factor coefficient, the value is 2.296, G is the control evaluation coefficient, and the control evaluation coefficient G is compared with a preset control evaluation coefficient threshold value recorded and stored in the control evaluation coefficient G:
if the management and control evaluation coefficient G is smaller than a preset management and control evaluation coefficient threshold value, generating a first-level management signal;
and if the management and control evaluation coefficient G is greater than or equal to a preset management and control evaluation coefficient threshold value, generating a next-stage management signal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311307748.1A CN117060594B (en) | 2023-10-11 | 2023-10-11 | Power distribution operation monitoring system based on Internet of things |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311307748.1A CN117060594B (en) | 2023-10-11 | 2023-10-11 | Power distribution operation monitoring system based on Internet of things |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117060594A CN117060594A (en) | 2023-11-14 |
| CN117060594B true CN117060594B (en) | 2024-01-26 |
Family
ID=88669555
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311307748.1A Active CN117060594B (en) | 2023-10-11 | 2023-10-11 | Power distribution operation monitoring system based on Internet of things |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117060594B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117491787A (en) * | 2023-11-16 | 2024-02-02 | 上海创芯致锐互联网络有限公司 | Electromagnetic interference detection system of chip production equipment |
| CN117279017B (en) * | 2023-11-17 | 2024-01-30 | 深圳通诚无限科技有限公司 | Wireless communication intelligent monitoring and early warning system based on 5G network |
| CN117278425B (en) * | 2023-11-20 | 2024-02-02 | 广东省信息工程有限公司 | Information technology operation and maintenance management method and system |
| CN117268455B (en) * | 2023-11-22 | 2024-01-26 | 河北建设集团股份有限公司 | Monitoring system of engineering construction quality detection equipment |
| CN117291316B (en) * | 2023-11-24 | 2024-02-02 | 山东朝辉自动化科技有限责任公司 | Cabin positioning system for ship unloader based on laser scanner |
| CN117408641B (en) * | 2023-12-11 | 2024-02-20 | 无锡芯感智半导体有限公司 | Pressure sensor production line processing operation supervision system based on data analysis |
| CN117524444B (en) * | 2024-01-05 | 2024-03-12 | 遂宁市中心医院 | Anesthetic agent storage environment monitoring management system based on data analysis |
| CN117590822B (en) * | 2024-01-19 | 2024-03-22 | 无锡芯感智半导体有限公司 | MEMS gas pressure sensor dispensing processing supervision system based on Internet of things |
| CN117706413B (en) * | 2024-02-02 | 2024-04-19 | 青岛元通电子有限公司 | Standard power module operation self-checking system based on data analysis |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106209432A (en) * | 2016-06-30 | 2016-12-07 | 中国人民解放军国防科学技术大学 | Network equipment subhealth state method for early warning based on dynamic threshold and device |
| CN111289812A (en) * | 2018-12-07 | 2020-06-16 | 国网浙江省电力有限公司 | Power transmission and transformation equipment state monitoring and management method and system |
| WO2020147349A1 (en) * | 2019-01-14 | 2020-07-23 | 中国电力科学研究院有限公司 | Power distribution network operation aided decision-making analysis system and method |
| WO2021108537A1 (en) * | 2019-11-27 | 2021-06-03 | Sentient Technology Holdings, LLC | Systems and methods for power line fault detection |
| CN115719998A (en) * | 2022-11-17 | 2023-02-28 | 宁波天仑电气股份有限公司 | Intelligent switch cabinet supervision method and system and storage medium |
| WO2023061039A1 (en) * | 2021-10-13 | 2023-04-20 | 中通服和信科技有限公司 | Tailing pond risk monitoring and early-warning system based on internet of things |
| CN116365711A (en) * | 2023-04-13 | 2023-06-30 | 明峰医疗系统股份有限公司 | Intelligent monitoring system for power supply and distribution of vehicle-mounted shelter based on Internet of things |
| CN116566050A (en) * | 2023-05-09 | 2023-08-08 | 南昌市科迪电气设备有限公司 | Comprehensive power distribution management system based on artificial intelligence |
| CN116820050A (en) * | 2023-06-30 | 2023-09-29 | 广西兵将自动化科技有限公司 | Automatic control system for production line based on industrial Internet |
| CN116859857A (en) * | 2023-07-31 | 2023-10-10 | 安徽中恒电喷系统有限公司 | Intelligent management system of fuel pump assembly production line based on remote control |
-
2023
- 2023-10-11 CN CN202311307748.1A patent/CN117060594B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106209432A (en) * | 2016-06-30 | 2016-12-07 | 中国人民解放军国防科学技术大学 | Network equipment subhealth state method for early warning based on dynamic threshold and device |
| CN111289812A (en) * | 2018-12-07 | 2020-06-16 | 国网浙江省电力有限公司 | Power transmission and transformation equipment state monitoring and management method and system |
| WO2020147349A1 (en) * | 2019-01-14 | 2020-07-23 | 中国电力科学研究院有限公司 | Power distribution network operation aided decision-making analysis system and method |
| WO2021108537A1 (en) * | 2019-11-27 | 2021-06-03 | Sentient Technology Holdings, LLC | Systems and methods for power line fault detection |
| WO2023061039A1 (en) * | 2021-10-13 | 2023-04-20 | 中通服和信科技有限公司 | Tailing pond risk monitoring and early-warning system based on internet of things |
| CN115719998A (en) * | 2022-11-17 | 2023-02-28 | 宁波天仑电气股份有限公司 | Intelligent switch cabinet supervision method and system and storage medium |
| CN116365711A (en) * | 2023-04-13 | 2023-06-30 | 明峰医疗系统股份有限公司 | Intelligent monitoring system for power supply and distribution of vehicle-mounted shelter based on Internet of things |
| CN116566050A (en) * | 2023-05-09 | 2023-08-08 | 南昌市科迪电气设备有限公司 | Comprehensive power distribution management system based on artificial intelligence |
| CN116820050A (en) * | 2023-06-30 | 2023-09-29 | 广西兵将自动化科技有限公司 | Automatic control system for production line based on industrial Internet |
| CN116859857A (en) * | 2023-07-31 | 2023-10-10 | 安徽中恒电喷系统有限公司 | Intelligent management system of fuel pump assembly production line based on remote control |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117060594A (en) | 2023-11-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117060594B (en) | Power distribution operation monitoring system based on Internet of things | |
| CN116859857B (en) | Intelligent management system of fuel pump assembly production line based on remote control | |
| CN117092578B (en) | Wire harness conduction intelligent detection system based on data acquisition and processing | |
| CN116800517A (en) | Data acquisition intelligent management system based on data analysis | |
| CN116739384A (en) | Mining equipment operation management system based on 5G wireless communication | |
| CN115102290A (en) | Real-time safety early warning system of smart power grids | |
| CN116649987A (en) | Electrocardiogram abnormality real-time monitoring system based on Internet | |
| CN116365716B (en) | Electricity inspection system based on internet of things platform | |
| CN116660672B (en) | Power grid equipment fault diagnosis method and system based on big data | |
| CN117279017B (en) | Wireless communication intelligent monitoring and early warning system based on 5G network | |
| CN115473331B (en) | Digital twin power grid electricity consumption monitoring system based on dynamic modeling | |
| CN116614525A (en) | Big data analysis-based land parcel soil environment rapid monitoring system | |
| CN117497162A (en) | Abnormal operation feedback early warning system of oral cavity laser therapeutic instrument based on data analysis | |
| CN115657631A (en) | Intelligent monitoring system for industrial control equipment operation field environment | |
| CN117268455B (en) | Monitoring system of engineering construction quality detection equipment | |
| CN117057513A (en) | Intelligent park is with control management system based on internet | |
| CN117032004A (en) | Industrial production automatic control platform based on Internet of things | |
| CN117664281B (en) | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of Things | |
| CN110992205A (en) | State detection method and system for generator winding of wind turbine generator and related components | |
| CN212895016U (en) | Aluminum electrolysis cell condition diagnosis system based on LoRa wireless measurement and control technology | |
| CN111160598A (en) | Energy prediction and energy consumption control method and system based on dynamic energy consumption benchmark | |
| CN117474318A (en) | Current transformer station valve hall operation supervisory systems based on portable infrared temperature measurement technique | |
| CN117193203A (en) | Alloy material processing production line monitoring system based on data analysis | |
| CN116934162A (en) | Agricultural machinery equipment operation management and control system based on data analysis | |
| CN209055131U (en) | The detection system of more ginseng enviromental monitoring equipments |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |