CN117197900A - Battery anti-theft identification method and device for battery replacement cabinet - Google Patents
Battery anti-theft identification method and device for battery replacement cabinet Download PDFInfo
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Abstract
The invention relates to the technical field of battery anti-theft identification, and particularly discloses a battery anti-theft identification method and device for a battery replacement cabinet, wherein the method comprises the following steps: according to the invention, the abnormal working state of the battery changing cabinet is monitored, and the automatic registration and management of the battery in the battery changing cabinet are realized by utilizing an RFID technology, so that the efficiency of battery management in the battery changing cabinet and the safety of battery use are improved, the illegal battery entering system is avoided in the identification registration of the battery, the risk of theft of the battery changing cabinet is reduced, meanwhile, the abnormal behaviors of personnel around the battery changing cabinet are identified and early-warned, the damage of the abnormal behaviors of the personnel to the battery changing cabinet is prevented, the risk of battery theft of the battery changing cabinet is effectively reduced, and the use experience of a user to the battery changing cabinet is improved.
Description
Technical Field
The invention relates to the technical field of battery anti-theft identification, in particular to a battery anti-theft identification method and device of a battery replacement cabinet.
Background
With the rising and popularization of electric vehicles, the demand of people for continuous electric quantity is increasing, and the battery changing cabinet is equipment for charging the electric automobile and is usually composed of a plurality of battery modules and a control system, so that the electric automobile can be replaced or charged in a short time, the problem of the charging time of the electric automobile can be rapidly solved by using the battery changing cabinet, the service efficiency and convenience of the electric automobile are improved, and meanwhile, the battery anti-theft identification method of the battery changing cabinet is required to be improved because the battery changing cabinet is high in price and frequent in use, so that the safety of the battery changing cabinet and the use experience of people are improved.
Today, there are also some disadvantages to battery theft identification, specifically in the following several aspects: (1) The battery anti-theft of the current battery exchange cabinet is more prone to physical anti-theft and safety precaution, a means for monitoring battery information in the battery exchange cabinet is lacking, whether the battery in the cabinet is compliant or not cannot be accurately judged, illegal batteries possibly enter a system is increased, the risk of the battery exchange cabinet being stolen is increased, meanwhile, the battery information is ignored to be monitored, the health state and quality problems of the battery are not easy to check, the safety risk of battery use is further increased, and the safety and stability of the battery exchange cabinet are reduced.
(2) The current battery-changing cabinet anti-theft technology lacks monitoring and identification of abnormal behaviors of personnel around the battery-changing cabinet, and timely warning feedback cannot be made on the abnormal behaviors of the personnel, so that the battery anti-theft identification of the battery-changing cabinet has time delay, the abnormal behaviors of the personnel around the battery-changing cabinet can possibly damage the battery-changing cabinet, and the risk of theft of the battery in the battery-changing cabinet is increased.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a battery anti-theft identification method and device for a battery replacement cabinet, which can effectively solve the problems related to the background art.
In order to achieve the above purpose, the invention is realized by the following technical scheme: the first aspect of the invention provides a battery anti-theft identification method of a battery exchange cabinet, comprising the following steps: step one, monitoring and analyzing the working state of the target battery-changing cabinet, and calculating the abnormal index of the working state of the target battery-changing cabinet in each monitoring period.
And secondly, monitoring and analyzing the battery information of the target battery changing cabinet, and calculating the abnormal index of the battery information of the target battery changing cabinet in each monitoring period.
And thirdly, comprehensively calculating an abnormality degree evaluation index of the target battery-changing cabinet in each monitoring period, and carrying out warning feedback on an abnormality result.
And fourthly, monitoring and analyzing the behaviors of the target personnel.
And fifthly, comprehensively calculating an abnormal index of the behavior of the target personnel, and performing early warning feedback on the behavior of the abnormal personnel.
As a further method, the working state of the target battery-changing cabinet is monitored and analyzed, and the specific analysis process is as follows: the working current intensity of the target battery-changing cabinet is monitored by taking the set time interval as a monitoring period and dividing the monitoring time point with the set frequency to obtain the working current I of each monitoring time point of the target battery-changing cabinet in each monitoring period ij Obtaining rated working current I of the target battery-changing cabinet from a battery-changing cabinet database 0 And simultaneously monitoring the current signal of the target battery-changing cabinet in each monitoring period to obtain the current signal waveform of the target battery-changing cabinet in each monitoring period.
Standard current signal waveform generated by rated current of target battery-changing cabinet is obtained from battery-changing cabinet database, and standard current signal waveform length is extractedThe current signal waveform of the target power conversion cabinet in each monitoring period is subjected to overlapping comparison with the standard current signal waveform, so that the overlapping length +.>
Comprehensive calculationCurrent signal abnormality index χ of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein ΔI is expressed as a set allowable deviation operating current, ζ 1 And zeta 2 The current intensity and the duty ratio weight to which the current signal belongs are respectively expressed as a set current intensity and a set duty ratio weight, i is expressed as a number of each monitoring period, i=1, 2, 3.
Monitoring local area network signals accessed by the target battery-changing cabinet to obtain local area network signal intensity B of each monitoring time point of the target battery-changing cabinet in each monitoring period ij Signal connection speed V with lan ij Simultaneously monitoring and obtaining the local area network signal interruption times and interruption duration time T of the target battery-changing cabinet in each monitoring period t 。
Obtaining signal intensity B of reference standard local area network from battery-changing cabinet database 0 And reference standard LAN connection speed V 0 And a single signal interruption maximum critical time T 0 Comprehensively calculating local area network signal abnormality index delta of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein DeltaB and DeltaV are respectively expressed as a set allowable deviation LAN signal strength and an allowable deviation LAN signal connection speed, ψ 1 、ψ 2 Sum phi 3 The signal strength, the connection speed and the interruption time of the local area network are respectively expressed as set local area network signal strength, the local area network signal connection speed and the local area network signal interruption time, t is expressed as the number of each signal interruption, t=1, 2, 3.
Monitoring vibration signals of the battery replacement cabinet to obtain each vibration intensity F of the target battery replacement cabinet in each monitoring period ip The vibration signal waveform of the target battery-changing cabinet in each monitoring period is obtained, and then the target in each monitoring period is obtainedVibration frequency E of battery-changing cabinet i Meanwhile, the critical vibration intensity F of the battery changing cabinet is obtained from the battery changing cabinet database 0 And reference standard vibration frequency E 0 。
Obtaining standard vibration signal waveforms of the target battery-changing cabinet from a battery-changing cabinet database, and extracting the length of the standard vibration signal waveformsThe vibration signal waveform of the target battery-changing cabinet in each monitoring period is subjected to superposition comparison with the standard vibration signal waveform, so that the superposition length of the vibration signal waveform of the target battery-changing cabinet in each monitoring period is obtained>
Comprehensively calculating abnormal index epsilon of vibration signal of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein Δf and Δe are respectively expressed as the set allowable deviation vibration intensity and allowable deviation vibration frequency, ζ 1 、ξ 2 And xi 3 The correction factors corresponding to the set vibration intensity, vibration frequency, and vibration signal waveform overlap length are expressed, p is the number of each vibration, p=1, 2,3,...
As a further method, the working state abnormality index phi of the target battery-changing cabinet in each monitoring period is calculated i The calculation formula is as follows:wherein omega 1 、ω 2 And omega 3 The duty ratio weights of the set current signal, the local area network signal and the vibration signal are respectively expressed, and e is expressed as a natural constant.
As a further method, the battery information of the target battery-changing cabinet is monitored and analyzed, and the specific analysis process is as follows: counting the batteries in the target battery changing cabinet and selectingAcquiring the input use duration T of each battery in the target battery changing cabinet from the battery changing cabinet database r Battery cell And the charge and discharge times N r Battery cell Comprehensively calculating loss characterization values of all batteries in target battery-changing cabinetThe calculation formula is as follows: />Wherein v is 1 And v 2 The long loss factor and the single charge/discharge loss factor are respectively expressed as a set unit time of use, r is expressed as the number of each battery, r=1, 2, 3.
Obtaining a relation curve of the loss characterization value and the preset working voltage from a battery change cabinet database, and obtaining the preset working voltage of each battery in the target battery change cabinet according to the matching of the loss characterization value of each battery in the target battery change cabinetMeanwhile, the voltage of each battery in the target battery changing cabinet is monitored to obtain the voltage of each battery at each monitoring time point of the target battery changing cabinet in each monitoring period>Comprehensively calculating battery voltage abnormality index gamma of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:where Δu is indicated as a set allowable deviation battery voltage, and τ is indicated as a correction factor corresponding to the set battery voltage.
The battery of the battery replacement cabinet is communicated with the battery replacement cabinet in real time through an RFID technology, radio frequency signals sent by the batteries and received by the battery replacement cabinet are monitored, and radio frequency signal power of each battery at each monitoring time point of the target battery replacement cabinet in each monitoring period is obtainedAnd acquiring preset transmitted radio frequency signal power of each battery in the target battery-changing cabinet from the battery-changing cabinet database>Further calculating the power abnormality index eta of the battery radio frequency signal of the target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein ΔP is expressed as the set allowable deviation battery RF signal power, ">And the correction factor is indicated as the correction factor corresponding to the set battery radio frequency signal power.
As a further method, the battery information abnormality index lambda of the target battery-changing cabinet in each monitoring period is calculated i The calculation formula is as follows: lambda (lambda) i ＝ln(γ i *σ 1 +η i *σ 2 +1), wherein σ 1 Sum sigma 2 Respectively expressed as the set battery voltage and the duty ratio weight of the battery radio frequency signal power.
As a further method, the method comprehensively calculates the abnormality degree evaluation index of the target battery-changing cabinet in each monitoring period, and carries out warning feedback on the abnormal result, and the specific process is as follows: comprehensively calculating an abnormality degree evaluation index alpha of a target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein phi is i The abnormal index lambda of the working state of the target battery-changing cabinet in the ith monitoring period i The battery information abnormality index of the target battery-changing cabinet in the ith monitoring period is expressed as +.>And->The duty ratio weights of the set operating state abnormality index and the battery information abnormality index are respectively expressed.
Acquiring a power change cabinet abnormality degree evaluation index threshold value from a power change cabinet database, comparing the abnormality degree evaluation index of the target power change cabinet in each monitoring period with the power change cabinet abnormality degree evaluation index threshold value, and if the abnormality degree evaluation index of the target power change cabinet in a certain monitoring period is higher than the power change cabinet abnormality degree evaluation index threshold value, carrying out feedback warning on the abnormality of the target power change cabinet in the monitoring period.
As a further method, the monitoring analysis is performed on the behaviors of the target personnel, and the specific analysis process is as follows: identifying the position of a person in the setting range of the target battery-changing cabinet through an infrared sensor, marking the person in the setting range of the target battery-changing cabinet as a target person, positioning the person to the position point of each joint of the target person, constructing a joint connecting line of the target person, further carrying out overlapping comparison on the joint connecting line corresponding to various behavior categories stored in a battery-changing cabinet database, and extracting the length of the overlapped joint connecting lineSimultaneously extracting the length of the joint line of the reference joint corresponding to various behavior categories>Calculating the matching degree mu of the target person and each behavior category d The calculation formula is as follows: />
Extracting the behavior class with the highest matching degree as the behavior class of the target person, and obtaining the duration T corresponding to the target person according to the behavior starting time point corresponding to the target person Behavior And meanwhile, extracting a risk abnormality factor theta corresponding to the unit duration time of the behavior category to which the target person belongs from the power conversion cabinet database.
As a further method, the calculationThe target person behavior abnormality index beta has a calculation formula as follows:wherein->The correction factor is indicated as a correction factor corresponding to the set behavioral abnormality index.
As a further method, the early warning feedback is performed on the abnormal personnel behaviors, and the specific analysis process is as follows: and acquiring a personnel behavior abnormality index threshold from the power conversion cabinet database, comparing the target personnel behavior abnormality index with the personnel behavior abnormality index threshold, and if the target personnel behavior abnormality index is higher than the personnel behavior abnormality index threshold, marking the target personnel as abnormal personnel and carrying out feedback warning on the abnormal personnel behavior.
The second aspect of the invention provides a battery anti-theft identification device of a battery exchange cabinet, comprising: a processor, a memory and a network interface connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieves the computer program from the non-volatile memory via the network interface and runs the computer program via the memory to perform the method of any of the above.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
(1) According to the battery anti-theft identification method and device for the battery exchange cabinet, the abnormal working state of the battery exchange cabinet is monitored, meanwhile, the RFID technology is utilized to automatically register and manage the battery inside the battery exchange cabinet, the abnormal behaviors of people around the battery exchange cabinet are identified and early warned, the damage to the battery exchange cabinet caused by the abnormal behaviors of the people is prevented, the risk of battery theft of the battery exchange cabinet is effectively reduced, and the use experience of a user on the battery exchange cabinet is improved.
(2) According to the invention, through monitoring the current signal, the local area network signal and the vibration signal of the battery-changing cabinet, the abnormal working state of the battery-changing cabinet can be found in time, necessary maintenance or replacement measures are further carried out, the further aggravation of the failure of the battery-changing cabinet is avoided, and meanwhile, the damage to the battery-changing cabinet can be effectively reduced through multi-dimensional abnormal working state monitoring, and the further expansion of the loss is avoided.
(3) According to the invention, through monitoring and identifying the battery information in the battery changing cabinet, the efficiency of battery management in the battery changing cabinet and the safety of battery use are improved, illegal battery access to a system is avoided through identifying and registering the battery, the risk of theft of the battery changing cabinet is reduced, meanwhile, the battery information is monitored, the health state and quality problems of the battery can be checked, the safety risk caused by battery faults is reduced, and the use experience of a user on the battery is further improved.
(4) According to the invention, by monitoring and identifying the abnormal behaviors of the personnel around the power exchange cabinet and timely warning and feeding back the abnormal behaviors of the personnel, the phenomenon that the battery in the power exchange cabinet is stolen is greatly reduced, and meanwhile, the abnormal behaviors of the personnel around the power exchange cabinet are monitored, so that the damage of the abnormal behaviors of the personnel to the power exchange cabinet can be effectively avoided, the maintenance cost of the power exchange cabinet is reduced, and the risk of the power exchange cabinet being stolen is reduced.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a schematic flow chart of the method of the present invention.
Detailed Description
The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by those skilled in the art without making creative efforts based on the embodiments of the present invention are included in the protection scope of the present invention.
Referring to fig. 1, a first aspect of the present invention provides a battery anti-theft identification method for a battery exchange cabinet, including: step one, monitoring and analyzing the working state of the target battery-changing cabinet, and calculating the abnormal index of the working state of the target battery-changing cabinet in each monitoring period.
Specifically, the monitoring analysis is performed on the working state of the target battery-changing cabinet, and the specific analysis process is as follows: the working current intensity of the target battery-changing cabinet is monitored by taking the set time interval as a monitoring period and dividing the monitoring time point with the set frequency to obtain the working current I of each monitoring time point of the target battery-changing cabinet in each monitoring period ij Obtaining rated working current I of the target battery-changing cabinet from a battery-changing cabinet database 0 And simultaneously monitoring the current signal of the target battery-changing cabinet in each monitoring period to obtain the current signal waveform of the target battery-changing cabinet in each monitoring period.
Standard current signal waveform generated by rated current of target battery-changing cabinet is obtained from battery-changing cabinet database, and standard current signal waveform length is extractedThe current signal waveform of the target power conversion cabinet in each monitoring period is subjected to overlapping comparison with the standard current signal waveform, so that the overlapping length +.>
It should be explained that the above-mentioned monitoring of current signal that utilizes current monitoring sensor helps finding the inside trouble and the problem of trading the electric cabinet through monitoring the current signal, helps monitoring the performance and the service behavior of trading the electric cabinet, and unusual current signal probably causes because trouble, short circuit or illegal operation simultaneously, in time monitors and handles unusual current signal and can reduce the security risk that trades the electric cabinet and use, reduces the emergence of incident.
Comprehensively calculating abnormal index χ of current signal of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein ΔI is expressed as a set allowable deviation operating current, ζ 1 And zeta 2 The current intensity and the duty ratio weight to which the current signal belongs are respectively expressed as a set current intensity and a set duty ratio weight, i is expressed as a number of each monitoring period, i=1, 2, 3.
Monitoring local area network signals accessed by the target battery-changing cabinet to obtain local area network signal intensity B of each monitoring time point of the target battery-changing cabinet in each monitoring period ij Signal connection speed V with lan ij Simultaneously monitoring and obtaining the local area network signal interruption times and interruption duration time T of the target battery-changing cabinet in each monitoring period t 。
Obtaining signal intensity B of reference standard local area network from battery-changing cabinet database 0 And reference standard LAN connection speed V 0 And a single signal interruption maximum critical time T 0 Comprehensively calculating local area network signal abnormality index delta of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein DeltaB and DeltaV are respectively expressed as a set allowable deviation LAN signal strength and an allowable deviation LAN signal connection speed, ψ 1 、ψ 2 Sum phi 3 The signal strength, the connection speed and the interruption time of the local area network are respectively expressed as set local area network signal strength, the local area network signal connection speed and the local area network signal interruption time, t is expressed as the number of each signal interruption, t=1, 2, 3.
It should be explained that, the monitoring of the local area network signal by using the network analyzer can help the manager monitor the state and performance of the power exchange cabinet in real time from a remote location, thereby being beneficial to timely finding and solving the potential problem of the power exchange cabinet, improving the availability and stability of the power exchange cabinet, and simultaneously being beneficial to preventing unauthorized access and potential network attack by monitoring the local area network signal.
Monitoring vibration signals of the battery replacement cabinet to obtain each vibration intensity F of the target battery replacement cabinet in each monitoring period ip The vibration signal waveform of the target battery-changing cabinet in each monitoring period is obtained, and then the vibration frequency E of the target battery-changing cabinet in each monitoring period is obtained i Meanwhile, the critical vibration intensity F of the battery changing cabinet is obtained from the battery changing cabinet database 0 And reference standard vibration frequency E 0 。
It should be explained that, above-mentioned utilize vibration sensor to monitor vibration signal, can help detecting potential trouble and the abnormal conditions that the cabinet is inside to be present through monitoring vibration signal, abnormal vibration probably is related with the ageing wearing and tearing of cabinet internal part, in time to the maintenance replacement of cabinet internal part, can help improving reliability and the life-span of cabinet that trades, reduce the security risk of using, monitor the destructive action of outside cabinet that trades simultaneously to vibration signal, reduce the stolen risk of cabinet that trades.
Obtaining standard vibration signal waveforms of the target battery-changing cabinet from a battery-changing cabinet database, and extracting the length of the standard vibration signal waveformsThe vibration signal waveform of the target battery-changing cabinet in each monitoring period is subjected to superposition comparison with the standard vibration signal waveform, so that the superposition length of the vibration signal waveform of the target battery-changing cabinet in each monitoring period is obtained>
Comprehensively calculating abnormal index epsilon of vibration signal of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein Δf and Δe are respectively expressed as the set allowable deviation vibration intensity and allowable deviation vibration frequency, ζ 1 、ξ 2 And xi 3 Respectively expressed as correction factors corresponding to the set vibration intensity, vibration frequency and vibration signal waveform superposition length,p represents the number of each vibration, p=1, 2,3,...
Further, the working state abnormality index phi of the target battery-changing cabinet in each monitoring period is calculated i The calculation formula is as follows:wherein omega 1 、ω 2 And omega 3 The duty ratio weights of the set current signal, the local area network signal and the vibration signal are respectively expressed, and e is expressed as a natural constant.
In a specific embodiment, through monitoring the current signal, the local area network signal and the vibration signal of the power conversion cabinet, the abnormal working state of the power conversion cabinet can be found in time, necessary maintenance or replacement measures are further carried out, the further aggravation of the fault of the power conversion cabinet is avoided, and meanwhile, the damage to the power conversion cabinet can be effectively reduced through multi-dimensional abnormal working state monitoring, and the further expansion of the loss is avoided.
And secondly, monitoring and analyzing the battery information of the target battery changing cabinet, and calculating the abnormal index of the battery information of the target battery changing cabinet in each monitoring period.
Specifically, the monitoring analysis is performed on the battery information of the target battery replacement cabinet, and the specific analysis process is as follows: counting the batteries in the target battery changing cabinet, and acquiring the input use time T of each battery in the target battery changing cabinet from a battery changing cabinet database r Battery cell And the charge and discharge times N r Battery cell Comprehensively calculating loss characterization values of all batteries in target battery-changing cabinetThe calculation formula is as follows:wherein v is 1 And v 2 The long loss factor and the single charge/discharge loss factor are respectively expressed as a set unit time of use, r is expressed as the number of each battery, r=1, 2, 3.
Slave exchangeAcquiring a relation curve between the loss characterization value and the preset working voltage in the electric cabinet database, and matching according to the loss characterization value of each battery in the target electric cabinet to obtain the preset working voltage of each battery in the target electric cabinetMeanwhile, the voltage of each battery in the target battery changing cabinet is monitored to obtain the voltage of each battery at each monitoring time point of the target battery changing cabinet in each monitoring period>Comprehensively calculating battery voltage abnormality index gamma of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:where Δu is indicated as a set allowable deviation battery voltage, and τ is indicated as a correction factor corresponding to the set battery voltage.
It should be explained that, above-mentioned utilize voltage sensor to monitor battery voltage, through the voltage of monitoring battery, can know the charge and discharge state of battery, and then evaluate the capacity of battery, judge charge and discharge condition and the surplus usable electric quantity of battery, and through battery voltage analysis, can reduce the illegal use to the battery, reduce the stolen risk of battery, be favorable to rationally arranging battery live time, avoid overdischarge of battery, monitor battery voltage simultaneously and can help evaluating the ageing condition of battery, the security risk of battery use has been reduced.
The battery of the battery replacement cabinet is communicated with the battery replacement cabinet in real time through an RFID technology, radio frequency signals sent by the batteries and received by the battery replacement cabinet are monitored, and radio frequency signal power of each battery at each monitoring time point of the target battery replacement cabinet in each monitoring period is obtainedAnd acquiring preset transmitted radio frequency signal power of each battery in the target battery-changing cabinet from the battery-changing cabinet database>Further calculating the power abnormality index eta of the battery radio frequency signal of the target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein ΔP is expressed as the set allowable deviation battery RF signal power, ">And the correction factor is indicated as the correction factor corresponding to the set battery radio frequency signal power.
It is to be explained that the above-mentioned identification communication to the battery through RFID technique realization has improved the efficiency of battery management in the battery replacement and the security of battery use, has avoided illegal battery to get into the system to the discernment registration of battery, has reduced the stolen risk of battery replacement cabinet, and then has improved the user and has experienced the battery.
Further, the battery information abnormality index lambda of the target battery-changing cabinet in each monitoring period is calculated i The calculation formula is as follows: lambda (lambda) i ＝ln(γ i *σ 1 +η i *σ 2 +1), wherein σ 1 Sum sigma 2 Respectively expressed as the set battery voltage and the duty ratio weight of the battery radio frequency signal power.
In a specific embodiment, through the monitoring and identification of the battery information in the battery changing cabinet, the efficiency of battery management in the battery changing cabinet and the safety of battery use are improved, illegal batteries are prevented from entering the system through the identification and registration of the batteries, the risk of theft of the battery changing cabinet is reduced, meanwhile, the battery information is monitored, the health state and quality problems of the batteries can be checked, the safety risk caused by battery faults is reduced, and the use experience of a user on the batteries is further improved.
And thirdly, comprehensively calculating an abnormality degree evaluation index of the target battery-changing cabinet in each monitoring period, and carrying out warning feedback on an abnormality result.
Specifically, the target battery-changing cabinet in each monitoring period is comprehensively calculatedThe abnormal degree evaluation index of (2) and alarm feedback is carried out on an abnormal result, and the specific process is as follows: comprehensively calculating an abnormality degree evaluation index alpha of a target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein phi is i The abnormal index lambda of the working state of the target battery-changing cabinet in the ith monitoring period i The battery information abnormality index of the target battery-changing cabinet in the ith monitoring period is expressed as +.>And->The duty ratio weights of the set operating state abnormality index and the battery information abnormality index are respectively expressed.
Acquiring a power change cabinet abnormality degree evaluation index threshold value from a power change cabinet database, comparing the abnormality degree evaluation index of the target power change cabinet in each monitoring period with the power change cabinet abnormality degree evaluation index threshold value, and if the abnormality degree evaluation index of the target power change cabinet in a certain monitoring period is higher than the power change cabinet abnormality degree evaluation index threshold value, carrying out feedback warning on the abnormality of the target power change cabinet in the monitoring period.
And fourthly, monitoring and analyzing the behaviors of the target personnel.
Specifically, the monitoring analysis is performed on the behaviors of the target personnel, and the specific analysis process is as follows: identifying the position of a person in the setting range of the target battery-changing cabinet through an infrared sensor, marking the person in the setting range of the target battery-changing cabinet as a target person, positioning the person to the position point of each joint of the target person, constructing a joint connecting line of the target person, further carrying out overlapping comparison on the joint connecting line corresponding to various behavior categories stored in a battery-changing cabinet database, and extracting the length of the overlapped joint connecting lineSimultaneously extracting various behavior classesThe length of the corresponding reference joint connecting line>Calculating the matching degree mu of the target person and each behavior category d The calculation formula is as follows: />
Extracting the behavior class with the highest matching degree as the behavior class of the target person, and obtaining the duration T corresponding to the target person according to the behavior starting time point corresponding to the target person Behavior And meanwhile, extracting a risk abnormality factor theta corresponding to the unit duration time of the behavior category to which the target person belongs from the power conversion cabinet database.
The infrared sensor is used for analyzing the abnormal behaviors of the personnel, so that the potential risk that the abnormal behaviors of the personnel can damage the power exchange cabinet is judged, and the personnel around the power exchange cabinet can be effectively prevented from carrying out destructive behaviors on the power exchange cabinet through the monitoring analysis of the abnormal behaviors of the personnel, so that the risk that the power exchange cabinet is stolen is reduced.
In a specific embodiment, through monitoring and identifying the abnormal behaviors of personnel around the battery replacement cabinet, alarming and feeding back the abnormal behaviors of the personnel in time, the phenomenon that the battery in the battery replacement cabinet is stolen is greatly reduced, meanwhile, the abnormal behaviors of the personnel around are monitored, the damage of the abnormal behaviors of the personnel to the battery replacement cabinet can be effectively avoided, the maintenance cost of the battery replacement cabinet is reduced, and the risk of the battery replacement cabinet being stolen is reduced.
And fifthly, comprehensively calculating an abnormal index of the behavior of the target personnel, and performing early warning feedback on the behavior of the abnormal personnel.
In an embodiment, the early warning feedback of the abnormal personnel behavior includes on-site starting of the power conversion cabinet to perform voice warning, and simultaneously transmitting an infrared monitoring image of the abnormal personnel to a receiving end of a manager of the power conversion cabinet.
Specifically, the calculation formula of the target person behavior abnormality index beta is as follows:wherein the method comprises the steps ofThe correction factor is indicated as a correction factor corresponding to the set behavioral abnormality index.
Further, the early warning feedback is performed on the abnormal personnel behaviors, and the specific analysis process is as follows: and acquiring a personnel behavior abnormality index threshold from the power conversion cabinet database, comparing the target personnel behavior abnormality index with the personnel behavior abnormality index threshold, and if the target personnel behavior abnormality index is higher than the personnel behavior abnormality index threshold, marking the target personnel as abnormal personnel and carrying out feedback warning on the abnormal personnel behavior.
The second aspect of the invention provides a battery anti-theft identification device of a battery exchange cabinet, comprising: a processor, a memory and a network interface connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieving a computer program from the non-volatile memory via the network interface and running the computer program via the memory to perform the method of any one of the above
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (10)
1. The battery anti-theft identification method of the battery exchange cabinet is characterized by comprising the following steps of:
step one, monitoring and analyzing the working state of a target battery-changing cabinet, and calculating the abnormal index of the working state of the target battery-changing cabinet in each monitoring period;
step two, monitoring and analyzing battery information of the target battery changing cabinet, and calculating abnormal indexes of the battery information of the target battery changing cabinet in each monitoring period;
step three, comprehensively calculating an abnormality degree evaluation index of the target battery-changing cabinet in each monitoring period, and carrying out warning feedback on an abnormality result;
step four, monitoring and analyzing the behaviors of the target personnel;
and fifthly, comprehensively calculating an abnormal index of the behavior of the target personnel, and performing early warning feedback on the behavior of the abnormal personnel.
2. The battery anti-theft identification method of the battery exchange cabinet according to claim 1, wherein the method comprises the following steps: the working state of the target battery-changing cabinet is monitored and analyzed, and the specific analysis process is as follows:
the working current intensity of the target battery-changing cabinet is monitored by taking the set time interval as a monitoring period and dividing the monitoring time point with the set frequency to obtain the working current I of each monitoring time point of the target battery-changing cabinet in each monitoring period ij Obtaining rated working current I of the target battery-changing cabinet from a battery-changing cabinet database 0 Simultaneously monitoring current signals of the target power conversion cabinet in each monitoring period to obtain current signal waveforms of the target power conversion cabinet in each monitoring period;
standard current signal waveform generated by rated current of target battery-changing cabinet is obtained from battery-changing cabinet database, and standard current signal waveform length is extractedThe current signal waveform of the target power conversion cabinet in each monitoring period is subjected to overlapping comparison with the standard current signal waveform, so that the overlapping length +.>
Comprehensively calculating abnormal index χ of current signal of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein the method comprises the steps ofΔI is expressed as a set allowable deviation operating current ζ 1 And zeta 2 Respectively representing the set current intensity and the duty ratio weight of the current signal, wherein i represents the number of each monitoring period, i=1, 2,3, & gt, n, n represents the total number of the monitoring periods, j represents the number of each monitoring time point, j=1, 2,3, & gt, and m, m represents the total number of the monitoring time points;
monitoring local area network signals accessed by the target battery-changing cabinet to obtain local area network signal intensity B of each monitoring time point of the target battery-changing cabinet in each monitoring period ij Signal connection speed V with lan ij Simultaneously monitoring and obtaining the local area network signal interruption times and interruption duration time T of the target battery-changing cabinet in each monitoring period t ；
Obtaining signal intensity B of reference standard local area network from battery-changing cabinet database 0 And reference standard LAN connection speed V 0 And a single signal interruption maximum critical time T 0 Comprehensively calculating local area network signal abnormality index delta of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein DeltaB and DeltaV are respectively expressed as a set allowable deviation LAN signal strength and an allowable deviation LAN signal connection speed, ψ 1 、ψ 2 Sum phi 3 The local area network signal strength, the local area network signal connection speed and the local area network signal interruption time are respectively set, t is the number of each signal interruption, t=1, 2,3, & gt, g, g is the total number of signal interruption;
monitoring vibration signals of the battery replacement cabinet to obtain each vibration intensity F of the target battery replacement cabinet in each monitoring period ip The vibration signal waveform of the target battery-changing cabinet in each monitoring period is obtained, and then the vibration frequency E of the target battery-changing cabinet in each monitoring period is obtained i Meanwhile, the critical vibration intensity F of the battery changing cabinet is obtained from the battery changing cabinet database 0 And reference standard vibration frequency E 0 ；
Acquisition of order from battery-changing cabinet databaseStandard vibration signal waveform of standard change cabinet and extracting standard vibration signal waveform lengthThe vibration signal waveform of the target battery-changing cabinet in each monitoring period is subjected to superposition comparison with the standard vibration signal waveform, so that the superposition length of the vibration signal waveform of the target battery-changing cabinet in each monitoring period is obtained>
Comprehensively calculating abnormal index epsilon of vibration signal of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein Δf and Δe are respectively expressed as the set allowable deviation vibration intensity and allowable deviation vibration frequency, ζ 1 、ξ 2 And xi 3 The correction factors corresponding to the set vibration intensity, vibration frequency, and vibration signal waveform overlap length are expressed, p is the number of each vibration, p=1, 2,3,...
3. The battery anti-theft identification method of the battery exchange cabinet according to claim 2, wherein the method comprises the following steps: the working state abnormality index phi of the target battery-changing cabinet in each monitoring period is calculated i The calculation formula is as follows:wherein omega 1 、ω 2 And omega 3 The duty ratio weights of the set current signal, the local area network signal and the vibration signal are respectively expressed, and e is expressed as a natural constant.
4. The battery anti-theft identification method of the battery exchange cabinet according to claim 1, wherein the method comprises the following steps: the battery information of the target battery replacement cabinet is monitored and analyzed, and the specific analysis process is as follows:
counting the batteries in the target battery changing cabinet, and acquiring the time length of each battery in the target battery changing cabinet when the battery is put into use from a battery changing cabinet databaseAnd charge and discharge times->Comprehensively calculating loss characterization values +.>The calculation formula is as follows: />Wherein v is 1 And v 2 The long loss factor and the single charge and discharge loss factor are respectively expressed as set unit time of use, r is expressed as the number of each battery, r=1, 2,3,..;
obtaining a relation curve of the loss characterization value and the preset working voltage from a battery change cabinet database, and obtaining the preset working voltage of each battery in the target battery change cabinet according to the matching of the loss characterization value of each battery in the target battery change cabinetMeanwhile, the voltage of each battery in the target battery changing cabinet is monitored to obtain the voltage of each battery at each monitoring time point of the target battery changing cabinet in each monitoring period>Comprehensively calculating battery voltage abnormality index gamma of target battery-changing cabinet in each monitoring period i The calculation formula is as follows:where ΔU is expressed as the set allowable deviation battery voltage and τ is expressed asA correction factor corresponding to the set battery voltage;
the battery of the battery replacement cabinet is communicated with the battery replacement cabinet in real time through an RFID technology, radio frequency signals sent by the batteries and received by the battery replacement cabinet are monitored, and radio frequency signal power of each battery at each monitoring time point of the target battery replacement cabinet in each monitoring period is obtainedAnd acquiring preset transmitted radio frequency signal power of each battery in the target battery-changing cabinet from the battery-changing cabinet database>Further calculating the power abnormality index eta of the battery radio frequency signal of the target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein ΔP is expressed as the set allowable deviation battery RF signal power, ">And the correction factor is indicated as the correction factor corresponding to the set battery radio frequency signal power.
5. The battery anti-theft identification method of the battery exchange cabinet according to claim 4, wherein the method comprises the following steps: calculating the abnormal index lambda of the battery information of the target battery-changing cabinet in each monitoring period i The calculation formula is as follows: lambda (lambda) i ＝ln(γ i *σ 1 +η i *σ 2 +1), wherein σ 1 Sum sigma 2 Respectively expressed as the set battery voltage and the duty ratio weight of the battery radio frequency signal power.
6. The battery anti-theft identification method of the battery exchange cabinet according to claim 1, wherein the method comprises the following steps: the method comprises the steps of comprehensively calculating an abnormality degree evaluation index of a target battery-changing cabinet in each monitoring period, and carrying out warning feedback on an abnormality result, wherein the specific process is as follows:
comprehensively calculating an abnormality degree evaluation index alpha of a target battery-changing cabinet in each monitoring period i The calculation formula is as follows:wherein phi is i The abnormal index lambda of the working state of the target battery-changing cabinet in the ith monitoring period i The battery information abnormality index of the target battery-changing cabinet in the ith monitoring period is expressed as +.>And->Respectively representing the duty ratio weights of the set operating state abnormality index and the battery information abnormality index;
acquiring a power change cabinet abnormality degree evaluation index threshold value from a power change cabinet database, comparing the abnormality degree evaluation index of the target power change cabinet in each monitoring period with the power change cabinet abnormality degree evaluation index threshold value, and if the abnormality degree evaluation index of the target power change cabinet in a certain monitoring period is higher than the power change cabinet abnormality degree evaluation index threshold value, carrying out feedback warning on the abnormality of the target power change cabinet in the monitoring period.
7. The battery anti-theft identification method of the battery exchange cabinet according to claim 1, wherein the method comprises the following steps: the target personnel behaviors are monitored and analyzed, and the specific analysis process is as follows:
identifying the position of a person in the setting range of the target battery-changing cabinet through an infrared sensor, marking the person in the setting range of the target battery-changing cabinet as a target person, positioning the person to the position point of each joint of the target person, constructing a joint connecting line of the target person, further carrying out overlapping comparison on the joint connecting line corresponding to various behavior categories stored in a battery-changing cabinet database, and extracting the length of the overlapped joint connecting lineSimultaneously extracting the length of the joint line of the reference joint corresponding to various behavior categories>Calculating the matching degree mu of the target person and each behavior category d The calculation formula is as follows: />
Extracting the behavior class with the highest matching degree as the behavior class of the target person, and obtaining the duration T corresponding to the target person according to the behavior starting time point corresponding to the target person Behavior And meanwhile, extracting a risk abnormality factor theta corresponding to the unit duration time of the behavior category to which the target person belongs from the power conversion cabinet database.
8. The battery theft-proof identification method for a battery exchange cabinet according to claim 7, wherein: the calculation formula of the target personnel behavior abnormality index beta is as follows:wherein->The correction factor is indicated as a correction factor corresponding to the set behavioral abnormality index.
9. The battery anti-theft identification method of the battery exchange cabinet according to claim 1, wherein the method comprises the following steps: the early warning feedback is carried out on the abnormal personnel behaviors, and the specific analysis process is as follows:
and acquiring a personnel behavior abnormality index threshold from the power conversion cabinet database, comparing the target personnel behavior abnormality index with the personnel behavior abnormality index threshold, and if the target personnel behavior abnormality index is higher than the personnel behavior abnormality index threshold, marking the target personnel as abnormal personnel and carrying out feedback warning on the abnormal personnel behavior.
10. A battery anti-theft identification device of a battery replacement cabinet is characterized in that: comprising the following steps:
a processor, a memory and a network interface connected with the processor; the network interface is connected with a nonvolatile memory in the server; the processor, when running, retrieving a computer program from the non-volatile memory via the network interface and running the computer program via the memory to perform the method of any of the preceding claims 1-9.
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