CN117518922A - Automatic flushing control system of intelligent closestool - Google Patents
Automatic flushing control system of intelligent closestool Download PDFInfo
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- 238000011010 flushing procedure Methods 0.000 title claims abstract description 165
- 230000002159 abnormal effect Effects 0.000 claims abstract description 42
- 230000005856 abnormality Effects 0.000 claims abstract description 38
- 238000012544 monitoring process Methods 0.000 claims abstract description 33
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000003745 diagnosis Methods 0.000 claims abstract description 19
- 230000008569 process Effects 0.000 claims abstract description 9
- 230000005540 biological transmission Effects 0.000 claims abstract description 8
- 239000002245 particle Substances 0.000 claims description 50
- 238000001514 detection method Methods 0.000 claims description 30
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- 238000004364 calculation method Methods 0.000 claims description 21
- 238000013075 data extraction Methods 0.000 claims description 15
- 230000005611 electricity Effects 0.000 claims description 15
- 238000004422 calculation algorithm Methods 0.000 claims description 10
- 230000004927 fusion Effects 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 6
- 238000006467 substitution reaction Methods 0.000 claims description 6
- 239000000284 extract Substances 0.000 claims description 5
- 238000000605 extraction Methods 0.000 claims description 3
- 230000013016 learning Effects 0.000 claims description 3
- 238000012806 monitoring device Methods 0.000 claims description 3
- 230000009326 social learning Effects 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims description 3
- 238000012546 transfer Methods 0.000 claims description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 11
- 238000004140 cleaning Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
- G05B19/0423—Input/output
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
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- Bidet-Like Cleaning Device And Other Flush Toilet Accessories (AREA)
Abstract
The invention discloses an intelligent automatic toilet flushing control system, which relates to the field of data control and comprises a monitoring module, wherein the monitoring module is used for background monitoring of a toilet flushing power supply control system by background management personnel and sending abnormal data to professionals for judgment; according to the integrated closestool flushing power supply control system of the data center, the processed data are monitored in real time through the data state monitoring module, the data diagnosis is carried out on the data with abnormality through the data abnormality diagnosis module, so that the abnormal data can be detected in real time through the data center, the data diagnosis can be carried out on the abnormal data, the cause of the abnormality is judged, meanwhile, the loss of the closestool flushing power supply on the circuit after the completion of switching is predicted through the closestool flushing power supply loss prediction module, the minimum loss of the circuit on the circuit in the process of the closestool flushing power supply transmission can be ensured, the closestool flushing power supply loss is reduced, meanwhile, the circuit condition can be monitored in real time through the data abnormality diagnosis module, and the fault position is positioned.
Description
Technical Field
The invention relates to a data control technology, in particular to an automatic flushing control system of an intelligent closestool.
Background
The conventional toilet bowl is characterized in that a single fixed water amount is used for flushing after a user activates a flushing valve, no matter the user is large or small, so that the flushing mode is easy to waste water and is dirty for people, and a valve control mechanism capable of performing two sections of different water amounts according to the large or small water amounts is developed and implemented for a long time.
However, in recent years, the global water resource has become more and more valuable, and the two-stage flushing mode has become increasingly undesirable. In addition, the conventional flushing valve control is to operate the flushing valve by a user's hand after the toilet is used up, and in case the user is stained with excrement during the cleaning process using the toilet paper and then operates the flushing switch by the stained hand, the next user may be infected with diseases, so that the automatic flushing device of the toilet is also developed one by one.
However, the existing automatic flushing equipment for the closestool controls the water outlet pressure of the water outlet driven by different voltages through the main control system when flushing, so that the voltage of the water outlet is influenced due to the complexity of a circuit, particularly, the more complex voltage of the circuit is, the larger the loss generated when the circuit passes through the circuit is, so that the actual water outlet voltage is lower than the water outlet voltage set by the main control system, and the water outlet pressure is lower than the target water outlet pressure.
Disclosure of Invention
The invention aims to provide an automatic flushing control system of an intelligent closestool, which aims to solve the problems in the prior art.
In order to achieve the above object, the present invention provides the following technical solutions: an intelligent toilet automatic flush control system comprising:
the monitoring module is used for background monitoring of the toilet flushing power supply control system by a background manager and sending abnormal data to professionals for judgment;
a data center, the data center comprising:
the data extraction module is used for acquiring the flushing power supply data of the closestool;
the data processing module processes the data after the data is obtained from the data extraction module, the data processing module processes the data and comprises data preprocessing, data feature extraction and data fusion, wherein the data fusion is the feature information fusion applied to the data processing and toilet flushing power supply distribution stage, and the data preprocessing method of the data processing module comprises the following steps:
s1, initializing a sequence and the weight of the sequence, wherein the weight is a number which is arbitrarily larger than 0;
s2, calculating a generation rule according to the sequence and the weight of the sequence;
s3, evaluating the difference degree of the two generation rules according to the Euclidean distance, and ending the flow if the rule obtained at this time is unchanged from the rule obtained at the previous time;
s4, adjusting the weight of each sequence according to the rule obtained in the S3 and the difference between each sequence, wherein the larger the difference is, the smaller the weight is, and the larger the opposite is;
the data state monitoring module monitors the data state of the data processing module in real time;
the data abnormality diagnosis module is used for diagnosing abnormality when abnormality is detected according to the monitoring result in the data state monitoring module, and evaluating the cause and severity of the abnormality;
the toilet flushing power system abnormality detection module is used for detecting abnormal states of the toilet flushing power system in real time;
the toilet flushing power supply line switching module is used for receiving the abnormal state of the toilet flushing power supply system abnormality detection module and judging whether the toilet flushing power supply line switching is needed or not;
the device comprises a toilet flushing power supply loss prediction module, a control module and a control module, wherein the toilet flushing power supply loss prediction module is used for predicting the toilet flushing power supply loss transmitted by the current line and selecting a line with low toilet flushing power supply loss for toilet flushing power supply transmission;
the closestool flushing power supply distribution module is used for distributing the closestool flushing power supply in the closestool flushing power supply transmission system to the electricity utilization end;
the power utilization end load module is used for each power utilization unit of the power utilization end;
the electricity consumption end detection module is used for detecting toilet flushing power supply information of the electricity consumption end electricity consumption module.
Further, the specific working method of the toilet flushing power supply control system is as follows:
the method comprises the steps of C1, detecting the abnormal state of a toilet flushing power supply system in real time through a toilet flushing power supply system abnormal detection module, sending the abnormal state of the toilet flushing power supply system to a monitoring module, and sending the abnormal state to professionals for judgment by a background manager;
c2, judging whether a toilet flushing power supply circuit switching module needs to be started by a professional;
if the judgment in the step C2 is yes, starting a toilet flushing power supply line switching module, and if the judgment in the step C2 is no, not starting the toilet flushing power supply line switching module;
c4, predicting the loss of the flushing power supply of the toilet on the line after the circuit switching is finished through a flushing power supply loss prediction module of the toilet;
c5, judging whether the current line is the line with the minimum loss;
c6, if the judgment result of the step C5 is yes, the toilet flushing power supply on the circuit is distributed to the power end load module for use through the toilet flushing power supply distribution module, the toilet flushing power supply information is detected in real time through the power end detection module, and if the judgment result of the step C5 is no, the step C3 is returned to carry out circuit switching again;
c7, the data center extracts the toilet flushing power supply information of the electricity consumption end detection module through the data extraction module;
c8, performing data processing on the data extracted by the data extraction module through a data processing module in the data center;
c9, monitoring the processed data in real time through a data state monitoring module;
and C10, carrying out data diagnosis on the data with the abnormality through a data abnormality diagnosis module.
Further, the specific working method of the toilet flushing power consumption prediction module comprises the following steps:
a1, inputting information, namely arranging user voltage and current data, power, W number, user identity and other user data obtained by an intelligent electric meter, typical user node harmonic data, transformer and line impedance parameters and network topology into input data, wherein the power consumption data of the user is obtained by the intelligent electric meter, typical day data is input for tide calculation, and the user node harmonic data is obtained by an electric power user harmonic monitoring device and takes typical values;
a2, carrying out power flow calculation, namely carrying out power flow calculation by using a decoupling algorithm because the harmonic content of the power distribution network is low and the influence of harmonic waves on fundamental waves is negligible, carrying out three-phase fundamental wave power flow calculation by using a forward-push back substitution method by using user, transformer and line and topology data, simultaneously carrying out three-phase harmonic wave power flow calculation by using user node harmonic data and a forward-push back substitution method, calculating current from a user node to a root node, and then calculating voltage from the root node to each branch end until iteration errors are smaller than a set value;
a3, calculating line loss, namely calculating the basic loss of each branch by using data obtained by power flow calculation, simultaneously calculating the additional loss of each branch by combining an additional loss calculation model, and finally obtaining the total loss and loss rate;
and A4, processing and outputting line loss results, calculating the proportion of various losses in the total loss, and analyzing the influence factors on the additional loss.
Further, the specific working method of the abnormality detection module of the toilet flushing power supply system is as follows:
b1, initializing parameters. The parameter settings include the number of particles N, the solution space dimension d, the maximum iteration number T, and the related parameters: individual learning factor c 1 Social learning factor c 2 Particle velocity v max And particle velocity v min ；
B2, initializing a particle swarm, and randomly assigning values to the particles X and the particles V;
b3, calculating the fitness of the initial particle group, obtaining the corresponding switch state of each particle and calculating the fitness,obtaining initial individual extremum P i And global extremum P g ；
B4, iterating the particle swarm, iterating the particles in the initial state, updating the speed and the position according to the BPSO algorithm, calculating the fitness, and updating the individual extremum P i And global extremum P g ；
B5, judging the state of the particle swarm, when the iteration number K of the particles is greater than 3, calculating the optimal solution f of the particle swarm, wherein when f is greater than or equal to 0 and less than or equal to 1, separating out a part of particles to be converted into a search state, updating the speed and the position of the particles according to a search state updating formula, updating the rest according to the step 4, and otherwise updating all the particles according to the step 4;
and B6, ending the iteration cycle when the iteration times reach the maximum iteration times set in the step 1, wherein the found global optimal solution is the actual running state of each toilet flushing power supply system section of the network.
Furthermore, the abnormality detection module of the toilet flushing power supply system combines a BBPSO algorithm to construct a corresponding fitness function, a fault line can be accurately positioned through an exclusive OR logic change-over switch function, and finally line fault simulation verification is carried out on the fault line according to a power supply and distribution network, the exclusive OR logic is obviously superior to OR logic through a simulation result, a plurality of faults can be positioned, a local optimal state can be well eliminated, and an optimal solution can be quickly and effectively searched.
Compared with the prior art, the intelligent automatic flushing control system for the closestool provided by the invention has the advantages that the processed data are monitored in real time through the data state monitoring module, the data diagnosis is carried out on the abnormal data through the data abnormality diagnosis module, so that the abnormal data can be detected in real time through the data center, the data diagnosis can be carried out on the abnormal data, the cause of the abnormality can be judged, meanwhile, the loss of the closestool flushing power supply on the circuit after the switching is predicted through the closestool flushing power supply loss prediction module, the minimum loss of the circuit on the circuit in the process of transmitting the closestool flushing power supply can be ensured, the closestool flushing power supply loss is reduced, the circuit condition can be monitored in real time through the data abnormality diagnosis module, and the fault position is positioned.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
Fig. 1 is a schematic diagram of an overall structure according to an embodiment of the present invention.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the present invention will be further described in detail with reference to the accompanying drawings.
Referring to fig. 1, an automatic flushing control system of an intelligent toilet, comprising:
the monitoring module is used for background monitoring of the toilet flushing power supply control system by a background manager and sending abnormal data to professionals for judgment;
a data center, the data center comprising:
the data extraction module is used for acquiring the flushing power supply data of the closestool;
the data processing module processes the data after the data is obtained from the data extraction module, the data processing module processes the data and comprises data preprocessing, data feature extraction and data fusion, wherein the data fusion is the feature information fusion applied to the data processing and toilet flushing power supply distribution stage, and the data preprocessing method of the data processing module comprises the following steps:
s1, initializing a sequence and the weight of the sequence, wherein the weight is any number larger than 0;
s2, calculating a generation rule according to the sequence and the weight of the sequence;
s3, evaluating the difference degree of the two generation rules according to the Euclidean distance, and ending the flow if the rule obtained at this time is unchanged from the rule obtained at the previous time;
s4, adjusting the weight of each sequence according to the rule obtained in the S3 and the difference between each sequence, wherein the larger the difference is, the smaller the weight is, and the larger the opposite is;
the device is arranged in such a way, the data are preprocessed, the difference degree of the two generation rules is evaluated according to the Euclidean distance, whether the line abnormality occurs in the toilet flushing power supply line can be judged, and meanwhile, the importance degree of the toilet flushing power supply line can be updated in real time by adjusting the weight of each sequence.
The data state monitoring module monitors the data state of the data processing module in real time;
the data abnormality diagnosis module is used for diagnosing abnormality when abnormality is detected according to the monitoring result in the data state monitoring module, and evaluating the cause and severity of the abnormality;
the toilet flushing power system abnormality detection module is used for detecting abnormal states of the toilet flushing power system in real time;
the toilet flushing power supply line switching module is used for receiving the abnormal state of the toilet flushing power supply system abnormality detection module and judging whether the toilet flushing power supply line switching is needed or not;
the device comprises a toilet flushing power consumption prediction module, a toilet flushing power consumption prediction module and a control module, wherein the toilet flushing power consumption prediction module is used for predicting the toilet flushing power consumption transmitted by the current line and selecting a line with low toilet flushing power consumption for toilet flushing power transmission;
the closestool flushing power supply distribution module is used for distributing the closestool flushing power supply in the closestool flushing power supply transmission system to the electricity utilization end;
the power utilization end load module is used as each power utilization unit of the power utilization end;
the electricity consumption end detection module is used for detecting toilet flushing power supply information of the electricity consumption end electricity consumption module.
The specific working method of the toilet flushing power supply control system is as follows:
the method comprises the steps of C1, detecting the abnormal state of a toilet flushing power supply system in real time through a toilet flushing power supply system abnormal detection module, sending the abnormal state of the toilet flushing power supply system to a monitoring module, and sending the abnormal state to professionals for judgment by a background manager;
c2, judging whether a toilet flushing power supply circuit switching module needs to be started by a professional;
if the judgment in the step C2 is yes, starting a toilet flushing power supply line switching module, and if the judgment in the step C2 is no, not starting the toilet flushing power supply line switching module;
c4, predicting the loss of the flushing power supply of the toilet on the line after the circuit switching is finished through a flushing power supply loss prediction module of the toilet;
c5, judging whether the current line is the line with the minimum loss;
c6, if the judgment result of the step C5 is yes, the toilet flushing power supply on the circuit is distributed to the power end load module for use through the toilet flushing power supply distribution module, the toilet flushing power supply information is detected in real time through the power end detection module, and if the judgment result of the step C5 is no, the step C3 is returned to carry out circuit switching again;
c7, the data center extracts the toilet flushing power supply information of the electricity consumption end detection module through the data extraction module;
c8, performing data processing on the data extracted by the data extraction module through a data processing module in the data center;
c9, monitoring the processed data in real time through a data state monitoring module;
and C10, carrying out data diagnosis on the data with the abnormality through a data abnormality diagnosis module.
The abnormal state of the toilet flushing power system is detected in real time through the toilet flushing power system abnormal detection module, the abnormal state of the toilet flushing power system is sent to the monitoring module, a background manager sends the abnormal state to a professional to judge, if the professional judges that the toilet flushing power line switching module needs to be started, the toilet flushing power line switching module is started, if the professional judges that the toilet flushing power line switching module does not need to be started, the toilet flushing power line switching module is not started, the loss of the toilet flushing power line after the completion of circuit switching is predicted through the toilet flushing power loss prediction module, whether the current line is the line with the minimum loss is judged, if the judgment result is yes, the toilet flushing power on the line is distributed to the power load module through the toilet flushing power distribution module, the toilet flushing power information is detected in real time through the power end detection module, if the judgment result is no, the line switching is carried out again, the data center extracts the toilet flushing power information of the power line of the power detection module through the data extraction module, the data extracted by the data processing module in the data extraction module carries out data processing on the data after the data processing, the processed data is carried out real-time through the data state monitoring module predicts that the loss of the toilet flushing power loss occurs through the toilet flushing power supply on the line, and the toilet flushing power is judged to be abnormal through the abnormal data can be detected through the data on the real-time, and the abnormal data can be judged when the abnormal data is judged through the real-time diagnosis is arranged on the toilet flushing power on the line, and the abnormal data is not has been judged on the abnormal condition real-time, the circuit loss on the line is minimum in the transmission process of the toilet flushing power supply, the toilet flushing power supply loss is reduced, and meanwhile, the line condition can be monitored in real time through the data abnormality diagnosis module, and the fault position is positioned.
The specific working method of the toilet flushing power supply loss prediction module is as follows:
a1, inputting information, namely arranging user voltage and current data, power, W number, user identity and other user data obtained by an intelligent electric meter, typical user node harmonic data, transformer and line impedance parameters and network topology into input data, wherein the power consumption data of the user is obtained by the intelligent electric meter, typical day data is input for tide calculation, and the user node harmonic data is obtained by an electric power user harmonic monitoring device and takes typical values;
a2, carrying out power flow calculation, namely carrying out power flow calculation by using a decoupling algorithm because the harmonic content of the power distribution network is low and the influence of harmonic waves on fundamental waves is negligible, carrying out three-phase fundamental wave power flow calculation by using a forward-push back substitution method by using user, transformer and line and topology data, simultaneously carrying out three-phase harmonic wave power flow calculation by using user node harmonic data and a forward-push back substitution method, calculating current from a user node to a root node, and then calculating voltage from the root node to each branch end until iteration errors are smaller than a set value;
a3, calculating line loss. Calculating the basic loss of each branch by using data obtained by power flow calculation, simultaneously calculating the additional loss of each branch by combining an additional loss calculation model, and finally obtaining the total loss and loss rate;
and A4, processing and outputting line loss results, calculating the proportion of various losses in the total loss, and analyzing the influence factors on the additional loss.
The specific working method of the abnormality detection module of the toilet flushing power supply system is as follows:
b1, initializing parameters. The parameter settings include the number of particles N, the solution space dimension d, the maximum iteration number T, and the related parameters: individual learning factor c 1 Social learning factor c 2 Particle velocity v max And particle velocity v min ；
B2, initializing a particle swarm, and randomly assigning values to the particles X and the particles V;
b3, calculating the fitness of the initial particle swarm, calculating the corresponding switch state of each particle, and calculating the fitness to obtain an initial individual extremum P i And global extremum P g ；
B4, iterating the particle swarm, iterating the particles in the initial state, updating the speed and the position according to the BPSO algorithm, calculating the fitness, and updating the individual extremum P i And global extremum P g ；
And B5, judging the state of the particle swarm, and calculating the optimal solution f of the particle swarm when the iteration number K of the particle swarm is greater than 3, wherein when f is greater than or equal to 0 and less than or equal to 1, separating out a part of particles to be converted into a search state, updating the speed and the position of the particles according to a search state updating formula, and updating the rest according to the step 4, otherwise, updating all the particles according to the step 4, wherein the judging formula is as follows:
wherein F is pg The fitness of the optimal solution found for the particle swarm is alpha epsilon (0, 1) in order to prevent the denominator from being zero, wherein t is more than or equal to 3;
and B6, ending the iteration cycle when the iteration times reach the maximum iteration times set in the step 1, wherein the found global optimal solution is the actual running state of each toilet flushing power supply system section of the network.
The abnormal detection module of the toilet flushing power system combines a BBPSO algorithm, wherein particles with the input of the BPSO algorithm being in an initial state are obtained according to the initial state of each toilet flushing power system section of the network, a corresponding fitness function is constructed, a fault line can be accurately positioned through an exclusive-or logic transfer switch function, and finally, line fault simulation verification is carried out on the power supply and distribution network according to the power supply and distribution network, the exclusive-or logic is obviously superior to or logic through a simulation result, a plurality of faults can be positioned, the local optimal state can be well eliminated, and the optimal solution can be quickly and effectively searched.
Working principle: when the system is used, the abnormal state of the toilet flushing power supply system is detected in real time through the toilet flushing power supply system abnormal detection module, the abnormal state of the toilet flushing power supply system is sent to the monitoring module, a background manager sends the abnormal state to a professional to judge, the professional judges whether the toilet flushing power supply line switching module needs to be started, if yes, the toilet flushing power supply line switching module is started, if no, the toilet flushing power supply line switching module is not started, after circuit switching is finished, the loss of the toilet flushing power supply on the line after the switching is predicted through the toilet flushing power supply loss prediction module, whether the current line is the line with the minimum loss is judged, if yes, the toilet flushing power supply on the line is distributed to the power utilization end load module through the toilet flushing power supply distribution module, the toilet flushing power supply information on the line is detected in real time through the power utilization end detection module, if no, the line switching is carried out again, the data center extracts the toilet flushing power supply information of the power utilization end detection module through the data extraction module, the data processing module carries out data processing on the data extracted by the data processing module in the data center, and the processed data is monitored through the data state monitoring module in real time.
While certain exemplary embodiments of the present invention have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the invention, which is defined by the appended claims.
Claims (5)
1. An intelligent closestool automatic flushing control system is characterized by comprising,
the monitoring module is used for background monitoring of the toilet flushing power supply control system by a background manager and sending abnormal data to professionals for judgment;
a data center, the data center comprising:
the data extraction module is used for acquiring the flushing power supply data of the closestool;
the data processing module processes the data after the data is obtained from the data extraction module, the data processing module processes the data and comprises data preprocessing, data feature extraction and data fusion, wherein the data fusion is the feature information fusion applied to the data processing and toilet flushing power supply distribution stage, and the data preprocessing method of the data processing module comprises the following steps:
s1, initializing a sequence and the weight of the sequence, wherein the weight is a number which is arbitrarily larger than 0;
s2, calculating a generation rule according to the sequence and the weight of the sequence;
s3, evaluating the difference degree of the two generation rules according to the Euclidean distance, and ending the flow if the rule obtained at this time is unchanged from the rule obtained at the previous time;
s4, adjusting the weight of each sequence according to the rule obtained in the S3 and the difference between each sequence, wherein the larger the difference is, the smaller the weight is, and the larger the opposite is;
the data state monitoring module monitors the data state of the data processing module in real time;
the data abnormality diagnosis module is used for diagnosing abnormality when abnormality is detected according to the monitoring result in the data state monitoring module, and evaluating the cause and severity of the abnormality; the toilet flushing power system abnormality detection module is used for detecting abnormal states of the toilet flushing power system in real time;
the toilet flushing power supply line switching module is used for receiving the abnormal state of the toilet flushing power supply system abnormality detection module and judging whether the toilet flushing power supply line switching is needed or not;
the device comprises a toilet flushing power supply loss prediction module, a control module and a control module, wherein the toilet flushing power supply loss prediction module is used for predicting the toilet flushing power supply loss transmitted by the current line and selecting a line with low toilet flushing power supply loss for toilet flushing power supply transmission;
the closestool flushing power supply distribution module is used for distributing the closestool flushing power supply in the closestool flushing power supply transmission system to the electricity utilization end;
the power utilization end load module is used for each power utilization unit of the power utilization end;
the electricity consumption end detection module is used for detecting toilet flushing power supply information of the electricity consumption end electricity consumption module.
2. The automatic flush control system of an intelligent toilet according to claim 1, wherein the specific working method of the toilet flush power control system is as follows:
the method comprises the steps of C1, detecting the abnormal state of a toilet flushing power supply system in real time through a toilet flushing power supply system abnormal detection module, sending the abnormal state of the toilet flushing power supply system to a monitoring module, and sending the abnormal state to professionals for judgment by a background manager;
c2, judging whether a toilet flushing power supply circuit switching module needs to be started by a professional;
if the judgment in the step C2 is yes, starting a toilet flushing power supply line switching module, and if the judgment in the step C2 is no, not starting the toilet flushing power supply line switching module;
c4, predicting the loss of the flushing power supply of the toilet on the line after the circuit switching is finished through a flushing power supply loss prediction module of the toilet;
c5, judging whether the current line is the line with the minimum loss;
c6, if the judgment result of the step C5 is yes, the toilet flushing power supply on the circuit is distributed to the power end load module for use through the toilet flushing power supply distribution module, the toilet flushing power supply information is detected in real time through the power end detection module, and if the judgment result of the step C5 is no, the step C3 is returned to carry out circuit switching again;
c7, the data center extracts the toilet flushing power supply information of the electricity consumption end detection module through the data extraction module;
c8, performing data processing on the data extracted by the data extraction module through a data processing module in the data center;
c9, monitoring the processed data in real time through a data state monitoring module;
and C10, carrying out data diagnosis on the data with the abnormality through a data abnormality diagnosis module.
3. The automatic flush control system of an intelligent toilet according to claim 1, wherein the specific working method of the toilet flush power consumption prediction module is as follows:
a1, inputting information, namely arranging user voltage and current data, power, W number, user identity and other user data obtained by an intelligent electric meter, typical user node harmonic data, transformer and line impedance parameters and network topology into input data, wherein the power consumption data of the user is obtained by the intelligent electric meter, typical day data is input for tide calculation, and the user node harmonic data is obtained by an electric power user harmonic monitoring device and takes typical values;
a2, carrying out power flow calculation, namely carrying out power flow calculation by using a decoupling algorithm because the harmonic content of the power distribution network is low and the influence of harmonic waves on fundamental waves is negligible, carrying out three-phase fundamental wave power flow calculation by using a forward-push back substitution method by using user, transformer and line and topology data, simultaneously carrying out three-phase harmonic wave power flow calculation by using user node harmonic data and a forward-push back substitution method, calculating current from a user node to a root node, and then calculating voltage from the root node to each branch end until iteration errors are smaller than a set value;
a3, calculating line loss. Calculating the basic loss of each branch by using data obtained by power flow calculation, simultaneously calculating the additional loss of each branch by combining an additional loss calculation model, and finally obtaining the total loss and loss rate;
and A4, processing and outputting line loss results, calculating the proportion of various losses in the total loss, and analyzing the influence factors on the additional loss.
4. The automatic flushing control system of an intelligent toilet according to claim 1, wherein the specific working method of the abnormality detection module of the toilet flushing power system is as follows:
b1, initializing parameters. The parameter settings include the number of particles N, the solution space dimension d, the maximum iteration number T, and the related parameters: individual learning factor c 1 Social learning factor c 2 Particle velocity v max And particle velocity v min ；
B2, initializing a particle swarm, and randomly assigning values to the particles X and the particles V;
b3, calculating the fitness of the initial particle swarm, calculating the corresponding switch state of each particle, and calculating the fitness to obtain an initial individual extremum P i And global extremum P g ；
B4, particle swarm iteration, initialThe particles in the state are iterated, the speed and the position are updated according to the BPSO algorithm, the fitness is calculated, and the individual extremum P is updated i And global extremum P g ；
B5, judging the state of the particle swarm, when the iteration number K of the particles is greater than 3, calculating the optimal solution f of the particle swarm, wherein when f is greater than or equal to 0 and less than or equal to 1, separating out a part of particles to be converted into a search state, updating the speed and the position of the particles according to a search state updating formula, updating the rest according to the step 4, and otherwise updating all the particles according to the step 4;
and B6, ending the iteration cycle when the iteration times reach the maximum iteration times set in the step 1, wherein the found global optimal solution is the actual running state of each toilet flushing power supply system section of the network.
5. The automatic flushing control system of the intelligent closestool according to claim 4, wherein the abnormality detection module of the closestool flushing power supply system combines a BBPSO algorithm to construct a corresponding fitness function, a fault line can be accurately positioned through an exclusive or logic transfer switch function, finally, line fault simulation verification is carried out on the intelligent closestool according to a power supply and distribution network, the exclusive or logic is obviously superior to or logic through a simulation result, a plurality of faults can be positioned, a local optimal state can be well eliminated, and an optimal solution can be quickly and effectively searched.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105139147A (en) * | 2015-09-18 | 2015-12-09 | 北京北变微电网技术有限公司 | Economic scheduling method for micro-grid system |
| CN108694467A (en) * | 2018-05-22 | 2018-10-23 | 中国电力科学研究院有限公司 | A kind of method and system that Line Loss of Distribution Network System rate is predicted |
| CN110880760A (en) * | 2019-11-29 | 2020-03-13 | 国网辽宁省电力有限公司葫芦岛供电公司 | Low-voltage distribution network line loss and reactive compensation collaborative optimization method |
| CN110910026A (en) * | 2019-11-28 | 2020-03-24 | 国家电网有限公司 | Intelligent management and decision-making method and system for route loss of trans-provincial power transmission line |
| CN113673065A (en) * | 2021-08-12 | 2021-11-19 | 国网浙江义乌市供电有限公司 | Loss reduction method for automatic reconstruction of power distribution network |
| WO2023138240A1 (en) * | 2022-01-19 | 2023-07-27 | 江苏大学 | Multi-model prediction control method for fermentation process of pichia pastoris |
| CN116819230A (en) * | 2023-06-27 | 2023-09-29 | 国网陕西省电力有限公司电力科学研究院 | Low-voltage transformer area line loss calculation method and system of high-density distributed photovoltaic power supply |
| CN116911508A (en) * | 2023-08-03 | 2023-10-20 | 深圳市铱钏科技有限公司 | BMS management system and method based on intelligent algorithm |
-
2023
- 2023-11-21 CN CN202311554627.7A patent/CN117518922A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105139147A (en) * | 2015-09-18 | 2015-12-09 | 北京北变微电网技术有限公司 | Economic scheduling method for micro-grid system |
| CN108694467A (en) * | 2018-05-22 | 2018-10-23 | 中国电力科学研究院有限公司 | A kind of method and system that Line Loss of Distribution Network System rate is predicted |
| CN110910026A (en) * | 2019-11-28 | 2020-03-24 | 国家电网有限公司 | Intelligent management and decision-making method and system for route loss of trans-provincial power transmission line |
| CN110880760A (en) * | 2019-11-29 | 2020-03-13 | 国网辽宁省电力有限公司葫芦岛供电公司 | Low-voltage distribution network line loss and reactive compensation collaborative optimization method |
| CN113673065A (en) * | 2021-08-12 | 2021-11-19 | 国网浙江义乌市供电有限公司 | Loss reduction method for automatic reconstruction of power distribution network |
| WO2023138240A1 (en) * | 2022-01-19 | 2023-07-27 | 江苏大学 | Multi-model prediction control method for fermentation process of pichia pastoris |
| CN116819230A (en) * | 2023-06-27 | 2023-09-29 | 国网陕西省电力有限公司电力科学研究院 | Low-voltage transformer area line loss calculation method and system of high-density distributed photovoltaic power supply |
| CN116911508A (en) * | 2023-08-03 | 2023-10-20 | 深圳市铱钏科技有限公司 | BMS management system and method based on intelligent algorithm |
Non-Patent Citations (1)
| Title |
|---|
| 翁国庆;黄飞腾;南余荣;朱双双;杨晓东;: "计及分布式电源的电能质量监测点优化配置", 电工技术学报, no. 13, 31 December 2017 (2017-12-31) * |
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