CN117040138A - Power distribution cabinet operation dynamic safety evaluation system - Google Patents
Power distribution cabinet operation dynamic safety evaluation system Download PDFInfo
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- 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
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- 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
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
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Abstract
The invention belongs to the technical field of power distribution cabinet supervision, in particular to a power distribution cabinet operation dynamic safety evaluation system which comprises a processor, a power distribution cabinet acquisition and distribution module, a multi-component item-by-item monitoring module, a power distribution cabinet integral decision module and a background visual early warning terminal, wherein the processor is used for acquiring a power distribution cabinet; according to the invention, the power distribution cabinet collecting and dividing module is used for analyzing and judging whether the scrapping signal of the corresponding power distribution cabinet is generated, so that a manager can timely discard the corresponding power distribution cabinet, the subsequent operation risk is reduced, the potential safety hazard is reduced, the operation conditions of all parts in the power distribution cabinet which do not generate the scrapping signal are analyzed one by one, the multi-part monitoring qualified signal or the multi-part monitoring unqualified signal is generated, and the power distribution cabinet corresponding to the multi-part monitoring qualified signal is subjected to overall decision analysis, so that the decision normal signal or the decision abnormal signal is generated, the dynamic safety of the power distribution cabinet is evaluated in all aspects, the accuracy of the evaluation result is high, and the operation safety and stability of the power distribution cabinet are effectively ensured.
Description
Technical Field
The invention relates to the technical field of power distribution cabinet supervision, in particular to a power distribution cabinet operation dynamic safety evaluation system.
Background
The power distribution cabinet is a final-stage device of the power distribution system and can be divided into a power distribution cabinet, an illumination power distribution cabinet and a metering cabinet according to different application occasions, and the main function of the power distribution cabinet is to receive and distribute the electric energy of the upper-stage power distribution equipment, provide protection, monitoring and control for loads and ensure reasonable distribution and safe use of the electric energy; with the continuous development of the power grid, the function of the power distribution cabinet in the power system is increasingly important;
traditionally, the safety evaluation of a power distribution cabinet mainly depends on regular inspection and test, and the method has the advantages that although problems can be found and solved to a certain extent, the method has large workload and lower efficiency, real-time monitoring and early warning cannot be realized, the dynamic safety of the power distribution cabinet cannot be evaluated in all aspects, the accuracy of an evaluation result is poor, and the operation safety and the operation stability of the power distribution cabinet are difficult to effectively ensure;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a dynamic safety assessment system for operation of a power distribution cabinet, which solves the problems that the workload is large, the efficiency is low, real-time monitoring and early warning cannot be realized, the dynamic safety of the power distribution cabinet cannot be assessed in all aspects, the accuracy of assessment results is poor, and the operation safety and the operation stability of the power distribution cabinet are difficult to effectively guarantee in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a dynamic safety evaluation system for operation of a power distribution cabinet comprises a processor, a power distribution cabinet acquisition module, a multi-component item-by-item monitoring module, a power distribution cabinet integral decision module and a background visual early warning terminal; the power distribution cabinet acquisition and distribution module acquires a power distribution cabinet needing supervision, and marks the corresponding power distribution cabinet as i, wherein i is a natural number which is more than or equal to 1; the power distribution cabinet collecting and dividing module is used for judging whether to generate scrapping signals corresponding to the power distribution cabinet i through analysis, and transmitting the scrapping signals corresponding to the power distribution cabinet i to the background visual early warning terminal through the processor;
if no scrapping signal is generated, the corresponding power distribution cabinet i is sent to a multi-component item-by-item monitoring module through a processor; the multi-component item-by-item monitoring module analyzes the running condition of each component in the corresponding power distribution cabinet, so that the corresponding power distribution cabinet component is marked as a high-risk component, a medium-risk component or a low-risk component, a multi-component monitoring qualified signal or a multi-component monitoring unqualified signal is generated through analysis, the multi-component monitoring unqualified signal is sent to the background visual early warning module through the processor, and the multi-component monitoring qualified signal is sent to the power distribution cabinet integral decision module through the processor;
when receiving the multi-component monitoring qualified signal, the overall decision module of the power distribution cabinet performs overall decision analysis on the corresponding power distribution cabinet, so as to generate a decision normal signal or a decision abnormal signal, and the decision abnormal signal is sent to the background visual early warning module through the processor; and the background visual early warning module sends out corresponding early warning when receiving the scrapping signal, the multi-component monitoring unqualified signal or the decision abnormal signal.
Further, the specific operation process of the multi-component item-by-item monitoring module comprises the following steps:
acquiring a part to be controlled in a corresponding power distribution cabinet, marking the corresponding power distribution cabinet part as a target part m, wherein m is a natural number greater than or equal to 1; acquiring items to be monitored of the target component m, marking the items to be monitored as monitoring items, acquiring real-time data of the monitoring items corresponding to the target component m in a detection period, calling a preset numerical value requirement of the corresponding monitoring items, marking the monitoring items with the real-time data which do not meet the preset numerical value requirement as management and control items, and marking the deviation values of the real-time data of the management and control items compared with the corresponding preset numerical value requirements as actual measurement differences of the corresponding management and control items;
the method comprises the steps of calling a preset risk coefficient of a corresponding management and control item, and performing product calculation on an actual measurement difference value of the corresponding management and control item and the corresponding preset risk coefficient to obtain an actual measurement influence value; obtaining the number of management and control items of a target component m and the actual measurement influence value of each group of management and control items, summing all the actual measurement influence values to obtain an actual measurement total risk value, calculating the ratio of the number of the management and control items to the number of items to be monitored to obtain a risk table value, and calculating the value of the risk table and the actual measurement total risk value to obtain a component analysis value;
comparing the component analysis value with a corresponding preset component analysis value range, and marking the monitoring target i as a high-risk component if the component analysis value exceeds the maximum value of the preset component analysis value range; if the component analysis value is within the preset component analysis value range, marking the monitoring target i as a stroke risk component; if the component analysis value does not exceed the minimum value of the preset component analysis value range, the monitoring target i is marked as a low risk component.
Further, if the high-risk components exist in the power distribution cabinet, generating a multi-component monitoring failure signal, and if the high-risk components do not exist in the power distribution cabinet, calculating the ratio of the number of the high-risk components to the number of the low-risk components in the power distribution cabinet to obtain a monitoring output value; comparing the monitoring output value with a preset monitoring output threshold value in a numerical value mode, and generating a multi-component monitoring disqualification signal if the monitoring output value exceeds the preset monitoring output threshold value; and if the monitoring output value does not exceed the preset monitoring output threshold value, generating a multi-component monitoring qualified signal.
Further, the concrete operation process of the power distribution cabinet collecting and separating module comprises the following steps:
the method comprises the steps of obtaining a production date and a service date of a power distribution cabinet i, respectively calculating time differences of the current date and the production date and the service date to obtain a production time length and a service time length, obtaining maintenance times and maintenance time lengths of the power distribution cabinet i in the service time length, summing the maintenance time lengths of each maintenance time to obtain a maintenance total time value, and carrying out numerical calculation on the production time length, the service time length, the maintenance times and the maintenance total time value to obtain a scrapped primary analysis value; and comparing the scrapped primary analysis value of the power distribution cabinet i with a preset scrapped primary analysis threshold value, and generating a scrapped signal of the power distribution cabinet i if the scrapped primary analysis value exceeds the preset scrapped primary analysis threshold value.
Further, if the scrapped primary analysis value does not exceed the preset scrapped primary analysis threshold value, collecting the frequency of faults occurring in unit time of the power distribution cabinet i, marking the frequency as a fault coefficient, obtaining the maintenance duration and the maintenance cost of the corresponding faults, respectively carrying out numerical comparison on the maintenance duration and the maintenance cost and the preset maintenance duration threshold value and the preset maintenance cost threshold value, and marking the faults with the maintenance duration exceeding the preset maintenance duration threshold value or the maintenance cost exceeding the preset maintenance cost threshold value as high-impact faults;
calculating the ratio of the frequency of high-impact faults in unit time to the fault coefficient to obtain a high-event frequency value, calculating the numerical value of the high-event frequency value to the fault coefficient to obtain a fault representation value, and subtracting the scrapped primary analysis value from a preset scrapped primary analysis threshold value to obtain a scrapped primary analysis value; and carrying out numerical calculation on the discard primary analysis difference value and the fault representation value to obtain a discard re-analysis value, carrying out numerical comparison on the discard re-analysis value and a preset discard re-analysis threshold value, and generating a discard signal of the power distribution cabinet i if the discard re-analysis value exceeds the preset discard re-analysis threshold value.
Further, the specific operation process of the overall decision module of the power distribution cabinet comprises the following steps:
marking a circle with a radius of R1 by taking a corresponding power distribution cabinet i as a circle center, marking the corresponding circular area as a management and control area, acquiring the environment parameters of the management and control area corresponding to the power distribution cabinet i, acquiring real-time detection data of the corresponding environment parameters, marking the environment parameters which are not in a corresponding data range as risk parameters, and generating a decision abnormal signal of the power distribution cabinet i if the risk parameters exist in the corresponding management and control area;
if no risk parameter exists in the corresponding management and control area, the change rate of all the environmental parameters in the corresponding management and control area in unit time is collected and marked as the parameter quick change coefficient of the corresponding environmental parameters, the parameter quick change coefficient is compared with the preset parameter quick change coefficient threshold value of the corresponding environmental parameters in a numerical mode, and if the environmental parameters of which the parameter quick change coefficient exceeds the corresponding preset parameter quick change coefficient threshold value exist, a decision abnormal signal of the power distribution cabinet i is generated.
Further, if no environment parameter of which the parameter speed change coefficient exceeds the corresponding preset parameter speed change coefficient threshold value exists, acquiring the operation voltage and the operation current of the power distribution cabinet i, respectively comparing the operation voltage and the operation current with a preset operation voltage range and a preset operation current range in numerical values, and if the operation voltage or the operation current is not in the corresponding preset range, judging that the power distribution cabinet i is in an electric unstable state at the corresponding moment;
acquiring total duration and maximum duration of the power distribution cabinet i in an electric power unstable state in unit time, and marking the total duration and the maximum duration as electric power unstable total duration and electric power unstable high-duration respectively; and carrying out numerical calculation on the total power unstable duration and the high power unstable duration to obtain a power analysis coefficient, carrying out numerical comparison on the power analysis coefficient and a preset power analysis coefficient threshold value, and generating a decision abnormal signal of the power distribution cabinet i if the power analysis coefficient exceeds the preset power analysis coefficient threshold value.
Further, if the power analysis coefficient does not exceed a preset power analysis coefficient threshold value, setting a plurality of detection time points in unit time, collecting noise data and vibration data of the power distribution cabinet i at the detection time points, respectively comparing the noise data and the vibration data with a preset noise data range and a preset vibration data range in a numerical mode, and if the noise data or the vibration data is not in a corresponding preset range, marking the corresponding detection time points as abnormal time points;
establishing a noise set from the noise data of all the detection time points, carrying out mean value calculation on the noise set to obtain a noise coefficient, and obtaining a vibration coefficient in a similar way; summing the maximum value and the minimum value of the preset noise data range, taking the average value to obtain a noise judgment value, carrying out difference value calculation on the noise coefficient and the noise judgment value, taking the absolute value to obtain a noise analysis value, and obtaining a vibration analysis value in the same way; carrying out normalization calculation on the number of the abnormal time points, the noise analysis value and the vibration analysis value to obtain a comprehensive decision value, carrying out numerical comparison on the comprehensive decision value and a preset comprehensive decision threshold, generating a decision abnormal signal of the power distribution cabinet i if the comprehensive decision value exceeds the preset comprehensive decision threshold, and generating a decision normal signal of the power distribution cabinet i if the comprehensive decision value does not exceed the preset comprehensive decision threshold.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the power distribution cabinet splitting module is used for analyzing and judging whether the scrapping signal corresponding to the power distribution cabinet i is generated, so that a manager can timely discard the corresponding power distribution cabinet i, the follow-up safe and stable operation is ensured, the follow-up operation risk is reduced, and the potential safety hazard is reduced; the operation conditions of all parts in the power distribution cabinet which do not generate scrapped signals are analyzed one by one, so that corresponding power distribution cabinet parts are marked as high-risk parts, medium-risk parts or low-risk parts, and multi-part monitoring qualified signals or multi-part monitoring unqualified signals are generated through analysis, so that management staff can timely conduct reason investigation and check and maintain the corresponding power distribution cabinet i, and safe and stable operation of the corresponding power distribution cabinet i can be guaranteed;
2. according to the invention, the power distribution cabinet corresponding to the multi-component monitoring qualified signal is subjected to overall decision analysis through the power distribution cabinet overall decision module, so that a decision normal signal or a decision abnormal signal is generated, so that a manager can timely conduct reason investigation and check and maintain the corresponding power distribution cabinet i, the safe and stable operation of the corresponding power distribution cabinet i is further ensured, the comprehensive assessment of the dynamic safety of the power distribution cabinet is realized, the accuracy of the assessment result is high, and the operation safety and the operation stability of the power distribution cabinet can be effectively ensured.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
fig. 1 is an overall system block 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: as shown in FIG. 1, the power distribution cabinet operation dynamic safety evaluation system provided by the invention comprises a processor, a power distribution cabinet acquisition module, a multi-component item-by-item monitoring module and a background visual early warning terminal; the power distribution cabinet acquisition and distribution module acquires a power distribution cabinet needing supervision, and marks the corresponding power distribution cabinet as i, wherein i is a natural number which is more than or equal to 1; the power distribution cabinet collecting and dividing module analyzes and judges whether to generate a scrapping signal corresponding to the power distribution cabinet i, the scrapping signal corresponding to the power distribution cabinet i is sent to the background visual early warning terminal through the processor, and the background visual early warning module sends corresponding early warning when receiving the scrapping signal, so that a manager can timely discard the corresponding power distribution cabinet i, the follow-up safe and stable operation is ensured, the follow-up operation risk is reduced, and the potential safety hazard is reduced; the concrete operation process of the power distribution cabinet collecting and dividing module is as follows:
the method comprises the steps of obtaining a production date and a service date of a power distribution cabinet i, respectively calculating time differences of the current date and the production date and the service date to obtain a production time length and a running time length, obtaining maintenance times and maintenance time length of the power distribution cabinet i in the running time length, and summing the maintenance time lengths of each maintenance time to obtain a maintenance total value;
numerical calculation is carried out on the production duration WSi, the operation duration QSi, the maintenance times WYI and the maintenance total time value WZi through a formula Bxi= (a1+a2) QSi)/(a3+a4) WZi to obtain a scrapped primary analysis value Bxi; wherein a1, a2, a3 and a4 are preset proportionality coefficients, and the values of a1, a2, a3 and a4 are all larger than zero; and the larger the number of the scrapped primary analysis value Bxi is, the worse the life state of the power distribution cabinet i is; and comparing the scrapped primary analysis value BXi of the power distribution cabinet i with a preset scrapped primary analysis threshold value, and generating a scrapped signal of the power distribution cabinet i if the scrapped primary analysis value BXi exceeds the preset scrapped primary analysis threshold value.
Further, if the rejection preliminary analysis value BXi does not exceed the preset rejection preliminary analysis threshold, collecting the frequency of faults occurring in unit time of the power distribution cabinet i, marking the frequency as a fault coefficient, obtaining the maintenance duration and the maintenance cost of the corresponding faults, respectively comparing the maintenance duration and the maintenance cost with a preset maintenance duration threshold and a preset maintenance cost threshold in numerical values, and marking the faults with the maintenance duration exceeding the preset maintenance duration threshold or the maintenance cost exceeding the preset maintenance cost threshold as high-impact faults;
calculating the ratio of the frequency of high-impact faults in unit time to the fault coefficient to obtain a high-event frequency value, and calculating the value of the high-event frequency value Gwi and the fault coefficient GRi to obtain a fault representation value GTi through a formula GTi=b1 x Gwi+b2 x GRi, wherein b1 and b2 are preset proportional coefficients, and the values of b1 and b2 are both larger than zero; the larger the value of the fault representation value GTi is, the worse the fault representation of the power distribution cabinet i is; subtracting the discard primary analysis value from a preset discard primary analysis threshold value to obtain a discard primary analysis difference value BCi;
carrying out numerical calculation on the scrapped primary analysis difference value BCi and the fault representation value GTi through a formula BZi=b3/BCi+b4 to obtain a scrapped secondary analysis value BZi, wherein b3 and b4 are preset proportionality coefficients, and the values of b3 and b4 are both larger than zero; moreover, the larger the number of the scrapping re-analysis value BZi is, the more the power distribution cabinet i needs to be scrapped in time; comparing the scrapping re-analysis value BZi with a preset scrapping re-analysis threshold value, and generating a scrapping signal of the power distribution cabinet i if the scrapping re-analysis value BZi exceeds the preset scrapping re-analysis threshold value, which indicates that the power distribution cabinet i needs to be scrapped in time; if the discard re-analysis value BZi does not exceed the preset discard re-analysis threshold, the power distribution cabinet i does not need to be discarded, and a discard signal of the power distribution cabinet i is not generated.
If no scrapping signal is generated, the corresponding power distribution cabinet i is sent to a multi-component item-by-item monitoring module through a processor; the multi-component item-by-item monitoring module analyzes the running condition of each component in the corresponding power distribution cabinet, so that the corresponding power distribution cabinet component is marked as a high-risk component, a medium-risk component or a low-risk component, a multi-component monitoring qualified signal or a multi-component monitoring unqualified signal is generated through analysis, the multi-component monitoring unqualified signal is sent to the background visual early warning module through the processor, and the background visual early warning module sends out corresponding early warning when receiving the multi-component monitoring unqualified signal, so that a manager timely performs cause investigation and performs inspection maintenance on the corresponding power distribution cabinet i, and the safe and stable running of the corresponding power distribution cabinet i is guaranteed; the specific operation process of the multi-component item-by-item monitoring module is as follows:
acquiring a part to be controlled in a corresponding power distribution cabinet, marking the corresponding power distribution cabinet part as a target part m, wherein m is a natural number greater than or equal to 1; acquiring items to be monitored of a target component m, marking the items to be monitored as monitoring items, acquiring real-time data of the monitoring items corresponding to the target component m in a detection period, calling a preset numerical requirement of the corresponding monitoring items, marking the monitoring items with the real-time data which do not meet the preset numerical requirement as control items, marking the real-time data of the control items as actual measurement differences of the corresponding control items compared with deviation values of the corresponding preset numerical requirement, wherein the monitoring items comprise, but are not limited to, current values, voltage values, temperature values, humidity values, vibration frequencies and the like, the monitoring content of the monitoring items is determined according to the corresponding use situation of the target component, and the monitoring items are generated by a body when the corresponding component works, for example, the current values and the voltage values included in the monitoring items are actual current values and voltage values when the target component works;
the preset risk coefficients of the corresponding management and control items are called, and the values of the preset risk coefficients are larger than zero, the values are recorded in advance by a manager and stored in a processor, and the larger the numerical value of the preset risk coefficient is, the larger the adverse effect of deviation of the corresponding management and control items on the operation safety of the power distribution cabinet is; carrying out product calculation on the actual measurement difference value of the corresponding management and control item and the corresponding preset risk coefficient to obtain an actual measurement influence value;
obtaining the number of management items of a target component m and the actual measurement influence value of each group of management items, summing all the actual measurement influence values to obtain an actual measurement total risk value, calculating the ratio of the number of the management items to the number of items to be monitored to obtain a risk table value, and carrying out numerical calculation on the risk table value FBim and the actual measurement total risk value SXim through a formula GXim=c1 x FBim+c2 x SXim to obtain a component analysis value GXim; wherein c1 and c2 are preset weight coefficients, and the values of c1 and c2 are both larger than zero; and, the larger the value of the component analysis value GXim, the greater the running risk of the target component m, the worse the running state;
comparing the component analysis value GXim with a corresponding preset component analysis range in a numerical mode, and if the component analysis value GXim exceeds the maximum value of the preset component analysis value range, indicating that the running risk of the target component m is large, marking the monitoring target i as a high-risk component; if the component analysis value GXim is in the preset component analysis value range, indicating that the running risk of the target component m is moderate, marking the monitoring target i as a risk component; if the component analysis value GXim does not exceed the minimum value of the preset component analysis value range, indicating that the running risk of the target component m is small, marking the monitoring target i as a low risk component.
Further, if the high-risk components exist in the corresponding power distribution cabinet, generating a multi-component monitoring failure signal of the corresponding power distribution cabinet, and if the high-risk components do not exist in the power distribution cabinet, calculating the ratio of the number of the high-risk components to the number of the low-risk components in the power distribution cabinet to obtain a monitoring output value; comparing the monitoring output value with a preset monitoring output threshold value, and generating a multi-component monitoring disqualification signal corresponding to the power distribution cabinet if the monitoring output value exceeds the preset monitoring output threshold value; and if the monitoring output value does not exceed the preset monitoring output threshold value, generating a multi-component monitoring qualified signal corresponding to the power distribution cabinet.
Embodiment two: as shown in fig. 1, the difference between the embodiment and the embodiment 1 is that the processor is in communication connection with the overall decision module of the power distribution cabinet, the multi-component item-by-item monitoring module sends the multi-component monitoring qualified signal to the overall decision module of the power distribution cabinet through the processor, and the overall decision module of the power distribution cabinet performs overall decision analysis on the corresponding power distribution cabinet when receiving the multi-component monitoring qualified signal, so as to generate a decision normal signal or a decision abnormal signal, and sends the decision abnormal signal to the background visual early warning module through the processor; the background visual early warning module sends out corresponding early warning when receiving the decision abnormal signal, so that a manager can timely conduct reason investigation and check and maintain the corresponding power distribution cabinet i, and the safe and stable operation of the corresponding power distribution cabinet i is further ensured; the specific operation process of the overall decision module of the power distribution cabinet is as follows:
marking a circle with a radius of R1 by taking a corresponding power distribution cabinet i as a circle center, marking the corresponding circular area as a management and control area, acquiring the environment parameters of the management and control area corresponding to the power distribution cabinet i, acquiring real-time detection data of the corresponding environment parameters, comparing the real-time detection data with corresponding data ranges of the corresponding environment parameters, marking the environment parameters which are not in the corresponding data ranges as risk parameters, and generating decision abnormal signals of the power distribution cabinet i if the risk parameters exist in the corresponding management and control area;
it should be noted that: in the operation process of the power distribution cabinet, the corresponding environment parameter conditions can influence the safe and stable operation of the power distribution cabinet, and the real-time detection data of the environment parameters (such as temperature, smoke concentration and the like, wherein the temperature is the environment temperature) required to be monitored by the power distribution cabinet are in a corresponding preset range, otherwise, potential safety hazards can be brought; for example, the smoke concentration data of the environment of the power distribution cabinet indicate that fire possibly exists if the smoke concentration data exceeds the corresponding range; therefore, when the real-time detection data of the corresponding environment parameter is not in the corresponding data range, the environment parameter is indicated to be abnormal and is required to be marked as a risk parameter;
if no risk parameter exists in the corresponding management and control area, acquiring the change rate of all the environmental parameters in the corresponding management and control area in unit time and marking the change rate as a parameter quick change coefficient of the corresponding environmental parameters, wherein the larger the numerical value of the parameter quick change coefficient is, the greater the possibility that the corresponding environmental parameters are abnormal, and the greater the safety risk is brought; comparing the parameter speed change coefficient with a preset parameter speed change coefficient threshold value corresponding to the environment parameter, and generating a decision abnormal signal of the power distribution cabinet i if the environment parameter of which the parameter speed change coefficient exceeds the corresponding preset parameter speed change coefficient threshold value exists;
if the parameter quick change coefficient does not exist and exceeds the environment parameter corresponding to the preset parameter quick change coefficient threshold value, acquiring the operation voltage and the operation current of the power distribution cabinet i, wherein the operation voltage and the operation current of the power distribution cabinet i are the integral voltage and the integral current of the power distribution cabinet i when in operation and are different from the current value and the voltage value of the target part monitoring item, respectively carrying out numerical comparison on the operation voltage and the operation current with a preset operation voltage range and a preset operation current range, and if the operation voltage or the operation current is not in the corresponding preset range, indicating that the power condition of the corresponding power distribution cabinet i at the corresponding moment is poor, judging that the power distribution cabinet i is in an electric unstable state at the corresponding moment;
acquiring total duration and maximum duration of the power distribution cabinet i in an electric power unstable state in unit time, and marking the total duration and the maximum duration as electric power unstable total duration and electric power unstable high-duration respectively; performing numerical calculation on the total power unstable duration LWi and the high power unstable duration LGi through a formula LXi =eq1: LWi +eq2:lgi to obtain a power analysis coefficient LXi, wherein eq1 and eq2 are preset weight coefficients, and eq2 > eq1 > 0; and, the larger the value of the power analysis coefficient LXi is, the worse the power performance condition of the power distribution cabinet i is indicated; comparing the power analysis coefficient LXi with a preset power analysis coefficient threshold value, and generating a decision abnormal signal of the power distribution cabinet i if the power analysis coefficient LXi exceeds the preset power analysis coefficient threshold value;
if the power analysis coefficient LXi does not exceed the preset power analysis coefficient threshold, a plurality of detection time points are set in unit time, noise data and vibration data of the power distribution cabinet i at the detection time points are acquired, the noise data and the vibration data are respectively compared with a preset noise data range and a preset vibration data range in numerical value, if the noise data or the vibration data are not in the corresponding preset range, the operation performance condition of the power distribution cabinet i at the corresponding detection time points is poor, the corresponding detection time points are marked as abnormal time points, the noise data and the vibration data are decibel values and vibration frequency of the power distribution cabinet during operation, the decibel values of the noise data are acquired by a sound sensor, and the vibration frequency of the vibration data is acquired by a vibration sensor.
Establishing a noise set from the noise data of all the detection time points, carrying out mean value calculation on the noise set to obtain a noise coefficient, and obtaining a vibration coefficient in a similar way; summing the maximum value and the minimum value of the preset noise data range, taking the average value to obtain a noise judgment value, carrying out difference value calculation on the noise coefficient and the noise judgment value, taking the absolute value to obtain a noise analysis value, and obtaining a vibration analysis value in the same way;
normalizing the number CYi of the abnormal time points, the noise analysis value ZHi and the vibration analysis value ZWi through a formula QKi =ep1× CYi +ep2× ZHi +ep3× ZWi to obtain an overall decision value QKi, wherein ep1, ep2 and ep3 are preset proportionality coefficients, and values of ep1, ep2 and ep3 are all larger than zero; and, the larger the value of the overall decision value QKi is, the worse the running condition of the power distribution cabinet i is indicated; and (3) carrying out numerical comparison on the comprehensive decision value QKi and a preset comprehensive decision threshold, if the comprehensive decision value QKi exceeds the preset comprehensive decision threshold, generating a decision abnormal signal of the power distribution cabinet i, and if the comprehensive decision value QKi does not exceed the preset comprehensive decision threshold, generating a decision normal signal of the power distribution cabinet i.
The working principle of the invention is as follows: when the power distribution cabinet is used, the power distribution cabinet splitting module is used for analyzing and judging whether the scrapping signal corresponding to the power distribution cabinet i is generated or not, so that a manager can timely discard the corresponding power distribution cabinet i, the follow-up safe and stable operation is ensured, the follow-up operation risk is reduced, and the potential safety hazard is reduced; the multi-component item-by-item monitoring module analyzes the running conditions of all the internal components of the power distribution cabinet without generating scrapped signals one by one, so that corresponding power distribution cabinet components are marked as high-risk components, medium-risk components or low-risk components, and multi-component monitoring qualified signals or multi-component monitoring unqualified signals are generated through analysis, so that a manager can timely conduct reason investigation and check and maintain the corresponding power distribution cabinet i, and the safe and stable running of the corresponding power distribution cabinet i can be guaranteed; and when receiving the multi-component monitoring qualified signal, the whole decision module of the power distribution cabinet performs whole decision analysis on the corresponding power distribution cabinet so as to generate a decision normal signal or a decision abnormal signal, so that a manager can timely conduct reason investigation and check and maintain the corresponding power distribution cabinet i, and the safe and stable operation of the corresponding power distribution cabinet i is further ensured.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (10)
1. The power distribution cabinet operation dynamic safety evaluation system is characterized by comprising a processor, a power distribution cabinet acquisition and distribution module, a multi-component item-by-item monitoring module, a power distribution cabinet integral decision module and a background visual early warning terminal; the power distribution cabinet acquisition and distribution module acquires a power distribution cabinet needing supervision, and marks the corresponding power distribution cabinet as i, wherein i is a natural number which is more than or equal to 1; the power distribution cabinet collecting and dividing module is used for judging whether to generate scrapping signals corresponding to the power distribution cabinet i through analysis, and transmitting the scrapping signals corresponding to the power distribution cabinet i to the background visual early warning terminal through the processor;
if no scrapping signal is generated, the corresponding power distribution cabinet i is sent to a multi-component item-by-item monitoring module through a processor; the multi-component item-by-item monitoring module analyzes the running condition of each component in the corresponding power distribution cabinet, so that the corresponding power distribution cabinet component is marked as a high-risk component, a medium-risk component or a low-risk component, a multi-component monitoring qualified signal or a multi-component monitoring unqualified signal is generated through analysis, the multi-component monitoring unqualified signal is sent to the background visual early warning module through the processor, and the multi-component monitoring qualified signal is sent to the power distribution cabinet integral decision module through the processor;
when receiving the multi-component monitoring qualified signal, the overall decision module of the power distribution cabinet performs overall decision analysis on the corresponding power distribution cabinet, so as to generate a decision normal signal or a decision abnormal signal, and the decision abnormal signal is sent to the background visual early warning module through the processor; and the background visual early warning module sends out corresponding early warning when receiving the scrapping signal, the multi-component monitoring unqualified signal or the decision abnormal signal.
2. The power distribution cabinet operation dynamic safety assessment system according to claim 1, wherein the specific operation process of the multi-component item-by-item monitoring module comprises:
acquiring a part to be controlled in a corresponding power distribution cabinet, marking the corresponding power distribution cabinet part as a target part m, wherein m is a natural number greater than or equal to 1; acquiring items to be monitored of the target component m, marking the items to be monitored as monitoring items, acquiring real-time data of the monitoring items corresponding to the target component m in a detection period, calling a preset numerical value requirement of the corresponding monitoring items, marking the monitoring items with the real-time data which do not meet the preset numerical value requirement as management and control items, and marking the deviation values of the real-time data of the management and control items compared with the corresponding preset numerical value requirements as actual measurement differences of the corresponding management and control items;
the method comprises the steps of calling a preset risk coefficient of a corresponding management and control item, and performing product calculation on an actual measurement difference value of the corresponding management and control item and the corresponding preset risk coefficient to obtain an actual measurement influence value; obtaining the number of management and control items of a target component m and the actual measurement influence value of each group of management and control items, summing all the actual measurement influence values to obtain an actual measurement total risk value, calculating the ratio of the number of the management and control items to the number of items to be monitored to obtain a risk table value, and calculating the value of the risk table and the actual measurement total risk value to obtain a component analysis value;
comparing the component analysis value with a corresponding preset component analysis value range, and marking the monitoring target i as a high-risk component if the component analysis value exceeds the maximum value of the preset component analysis value range; if the component analysis value is within the preset component analysis value range, marking the monitoring target i as a stroke risk component; if the component analysis value does not exceed the minimum value of the preset component analysis value range, the monitoring target i is marked as a low risk component.
3. The dynamic safety evaluation system for operation of a power distribution cabinet according to claim 2, wherein if high-risk components exist in the power distribution cabinet, a multi-component monitoring failure signal is generated, and if no high-risk components exist in the power distribution cabinet, the number of medium-risk components and the number of low-risk components in the power distribution cabinet are subjected to ratio calculation to obtain a monitoring output value; comparing the monitoring output value with a preset monitoring output threshold value in a numerical value mode, and generating a multi-component monitoring disqualification signal if the monitoring output value exceeds the preset monitoring output threshold value; and if the monitoring output value does not exceed the preset monitoring output threshold value, generating a multi-component monitoring qualified signal.
4. The power distribution cabinet operation dynamic safety evaluation system according to claim 1, wherein the specific operation process of the power distribution cabinet mining module comprises:
the method comprises the steps of obtaining a production date and a service date of a power distribution cabinet i, respectively calculating time differences of the current date and the production date and the service date to obtain a production time length and a service time length, obtaining maintenance times and maintenance time lengths of the power distribution cabinet i in the service time length, summing the maintenance time lengths of each maintenance time to obtain a maintenance total time value, and carrying out numerical calculation on the production time length, the service time length, the maintenance times and the maintenance total time value to obtain a scrapped primary analysis value; and comparing the scrapped primary analysis value of the power distribution cabinet i with a preset scrapped primary analysis threshold value, and generating a scrapped signal of the power distribution cabinet i if the scrapped primary analysis value exceeds the preset scrapped primary analysis threshold value.
5. The system for dynamically evaluating the operation safety of a power distribution cabinet according to claim 4, wherein if the discard primary analysis value does not exceed a preset discard primary analysis threshold value, the frequency of faults occurring in unit time of the power distribution cabinet i is collected and marked as a fault coefficient, the maintenance time and the maintenance cost of the corresponding faults are obtained, the maintenance time and the maintenance cost are respectively compared with a preset maintenance time threshold value and a preset maintenance cost threshold value in a numerical mode, and the faults with the maintenance time exceeding the preset maintenance time threshold value or the maintenance cost exceeding the preset maintenance cost threshold value are marked as high-impact faults;
calculating the ratio of the frequency of high-impact faults in unit time to the fault coefficient to obtain a high-event frequency value, calculating the numerical value of the high-event frequency value to the fault coefficient to obtain a fault representation value, and subtracting the scrapped primary analysis value from a preset scrapped primary analysis threshold value to obtain a scrapped primary analysis value; and carrying out numerical calculation on the discard primary analysis difference value and the fault representation value to obtain a discard re-analysis value, carrying out numerical comparison on the discard re-analysis value and a preset discard re-analysis threshold value, and generating a discard signal of the power distribution cabinet i if the discard re-analysis value exceeds the preset discard re-analysis threshold value.
6. The power distribution cabinet operation dynamic safety assessment system according to claim 1, wherein the specific operation process of the power distribution cabinet overall decision module comprises:
marking a circle with a radius of R1 by taking a corresponding power distribution cabinet i as a circle center, marking the corresponding circular area as a management and control area, acquiring the environment parameters of the management and control area corresponding to the power distribution cabinet i, acquiring real-time detection data of the corresponding environment parameters, marking the environment parameters which are not in a corresponding data range as risk parameters, and generating a decision abnormal signal of the power distribution cabinet i if the risk parameters exist in the corresponding management and control area;
if no risk parameter exists in the corresponding management and control area, the change rate of all the environmental parameters in the corresponding management and control area in unit time is collected and marked as the parameter quick change coefficient of the corresponding environmental parameters, the parameter quick change coefficient is compared with the preset parameter quick change coefficient threshold value of the corresponding environmental parameters in a numerical mode, and if the environmental parameters of which the parameter quick change coefficient exceeds the corresponding preset parameter quick change coefficient threshold value exist, a decision abnormal signal of the power distribution cabinet i is generated.
7. The system according to claim 6, wherein if there is no environmental parameter whose parameter speed change coefficient exceeds a threshold value corresponding to a preset parameter speed change coefficient, acquiring an operation voltage and an operation current of the power distribution cabinet i, respectively comparing the operation voltage and the operation current with a preset operation voltage range and a preset operation current range, and if the operation voltage or the operation current is not in the corresponding preset range, judging that the power distribution cabinet i is in an electric unstable state at a corresponding moment;
acquiring total duration and maximum duration of the power distribution cabinet i in an electric power unstable state in unit time, and marking the total duration and the maximum duration as electric power unstable total duration and electric power unstable high-duration respectively; and carrying out numerical calculation on the total power unstable duration and the high power unstable duration to obtain a power analysis coefficient, carrying out numerical comparison on the power analysis coefficient and a preset power analysis coefficient threshold value, and generating a decision abnormal signal of the power distribution cabinet i if the power analysis coefficient exceeds the preset power analysis coefficient threshold value.
8. The system according to claim 7, wherein if the power analysis coefficient does not exceed the preset power analysis coefficient threshold, the number of the abnormal time points, the noise analysis value and the vibration analysis value are obtained through analysis, the number of the abnormal time points, the noise analysis value and the vibration analysis value are normalized to obtain a comprehensive decision value, the comprehensive decision value is compared with a preset comprehensive decision threshold, if the comprehensive decision value exceeds the preset comprehensive decision threshold, a decision abnormality signal of the power distribution cabinet i is generated, and if the comprehensive decision value does not exceed the preset comprehensive decision threshold, a decision normal signal of the power distribution cabinet i is generated.
9. The system for dynamically evaluating the safety of operation of a power distribution cabinet according to claim 8, wherein the method for analyzing and acquiring the number of the abnormal time points is specifically as follows:
and setting a plurality of detection time points in unit time, acquiring noise data and vibration data of the power distribution cabinet i at the detection time points, respectively comparing the noise data and the vibration data with a preset noise data range and a preset vibration data range in numerical value, and marking the corresponding detection time points as abnormal time points if the noise data or the vibration data are not in the corresponding preset range.
10. The system for dynamic safety assessment of power distribution cabinet operation according to claim 8, wherein the method for analyzing and acquiring the noise analysis value and the vibration analysis value comprises the following steps:
establishing a noise set from the noise data of all detection time points, carrying out mean value calculation on the noise set to obtain a noise coefficient, and obtaining a vibration coefficient in a similar way; and carrying out summation calculation on the maximum value and the minimum value of the preset noise data range, taking the average value to obtain a noise judgment value, carrying out difference calculation on the noise coefficient and the noise judgment value, taking the absolute value to obtain a noise analysis value, and obtaining the vibration analysis value in the same way.
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