CN116757482B - Fault supervision and maintenance system for new energy power battery production - Google Patents
Fault supervision and maintenance system for new energy power battery production Download PDFInfo
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- QHGJSLXSVXVKHZ-UHFFFAOYSA-N dilithium;dioxido(dioxo)manganese Chemical compound [Li+].[Li+].[O-][Mn]([O-])(=O)=O QHGJSLXSVXVKHZ-UHFFFAOYSA-N 0.000 description 1
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- 229910052744 lithium Inorganic materials 0.000 description 1
- 229910000625 lithium cobalt oxide Inorganic materials 0.000 description 1
- 229910001416 lithium ion Inorganic materials 0.000 description 1
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 description 1
- BFZPBUKRYWOWDV-UHFFFAOYSA-N lithium;oxido(oxo)cobalt Chemical compound [Li+].[O-][Co]=O BFZPBUKRYWOWDV-UHFFFAOYSA-N 0.000 description 1
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Abstract
The invention belongs to the technical field of battery production supervision, in particular to a fault supervision maintenance system for new energy power battery production, which comprises a server, a battery verification and statistics module, a real-time production supervision analysis module, an equipment processing detection management module and a fault supervision early warning module; according to the invention, the battery verification statistics module is used for analyzing to judge whether the target battery is a low-quality battery, the verification early warning signal or the verification normal signal is generated through analysis, the real-time production supervision analysis module is used for analyzing the corresponding battery production equipment to judge whether the risk early warning signal of the corresponding battery production equipment is generated, and when the risk early warning signal is not generated, the supervision early warning signal of the corresponding battery production equipment is judged whether to be generated through continuous analysis, and the processing condition of the corresponding battery production equipment in the management period is analyzed, so that the fault prediction is realized through a multi-step analysis and combination mode, and the fault supervision maintenance of battery production is convenient.
Description
Technical Field
The invention relates to the technical field of battery production supervision, in particular to a fault supervision maintenance system for new energy power battery production.
Background
The new energy power battery is a battery which adopts a new technology and a new process to accelerate the promotion of new energy automobiles, is an important part of the new energy automobiles, and mainly comprises a ternary lithium battery, a lithium iron phosphate battery, a lithium cobalt oxide battery, a lithium manganate battery, a multi-element composite lithium ion battery and the like; in the field of new energy automobiles, the performance and the service life of a power battery directly influence the endurance mileage and the service life of an electric automobile, so that research and development of the power battery with high performance and long service life are always important subjects in the field of new energy automobiles;
at present, in the production process of the new energy power battery, operation observation of battery production equipment is generally carried out manually and data summarization is carried out to judge the abnormal fault condition of the equipment, the judging result is not accurate enough, the real-time monitoring analysis and the processing condition analysis of the battery production equipment cannot be combined, the fault supervision of battery production cannot be realized based on the verification analysis of the produced new energy power battery, the fault prediction is difficult to realize, and the comprehensive inspection and maintenance of the battery production equipment are not facilitated for corresponding management personnel in time;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a fault supervision and maintenance system for new energy power battery production, which solves the problems that the prior art cannot combine real-time monitoring analysis and processing condition analysis of battery production equipment, cannot realize fault supervision of battery production based on verification analysis of the produced new energy power battery, cannot realize fault prediction, is not beneficial to corresponding management personnel to timely perform comprehensive inspection and maintenance of the battery production equipment, and cannot ensure efficient, stable and safe operation of the battery production equipment.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the fault supervision and maintenance system for the production of the new energy power battery comprises a server, a battery verification and statistics module, a real-time production supervision and analysis module, an equipment processing detection management module and a fault supervision and early warning module; the battery verification statistics module is used for setting a battery verification period, marking a new energy power battery produced by battery production equipment corresponding to the battery verification period as a target battery i, wherein i is a natural number larger than 1, analyzing and judging whether the target battery i is a low-quality battery or not, generating a verification early-warning signal or a verification normal signal through analysis, sending the verification early-warning signal or the verification normal signal to the server, sending the verification early-warning signal to the fault supervision early-warning module by the server, and sending a corresponding early warning after the fault supervision early-warning module receives the verification early-warning signal;
the real-time production supervision and analysis module is used for analyzing the corresponding battery production equipment, judging whether a risk early warning signal of the corresponding battery production equipment is generated through analysis, judging whether a supervision early warning signal of the corresponding battery production equipment is generated through analysis when judging that the risk early warning signal is not generated, sending the risk early warning signal or the supervision early warning signal to the fault supervision early warning module through the server, and sending a corresponding early warning when the fault supervision early warning module receives the risk early warning signal or the supervision early warning signal; the equipment processing detection management module is used for setting a management period, analyzing the processing conditions of the corresponding battery production equipment in the management period, judging whether to generate a management abnormal signal of the corresponding battery production equipment through analysis, sending the management abnormal signal to the fault supervision and early warning module through the server, and sending a corresponding early warning after the fault supervision and early warning module receives the management abnormal signal.
Further, the specific operation process of the battery verification and statistics module comprises the following steps:
performing quality detection on the target battery i through a battery detection instrument to acquire real-time data of all battery performance detection items, performing numerical comparison on the real-time data of the corresponding battery performance detection items and a corresponding preset real-time data range, and marking the corresponding battery performance detection items as unimpeded items if the real-time data of the corresponding battery performance detection items are located in the corresponding preset real-time data range; if the real-time data of the corresponding battery performance detection item is not in the corresponding preset real-time data range, marking the real-time data of the corresponding battery performance detection item as a performance deviation value compared with the deviation value of the corresponding preset real-time data range, if the performance deviation value exceeds a preset performance deviation threshold, marking the corresponding battery performance detection item as a high event item, otherwise marking the corresponding battery performance detection item as a low event item;
carrying out normalization calculation on the number of unimpeded items, the number of high items and the number of low items of the target battery i to obtain a battery performance value, carrying out numerical comparison on the battery performance value and a preset battery performance threshold value, and if the battery performance value exceeds the preset battery performance threshold value, marking the target battery i as a low-quality battery; collecting the quantity of low-quality batteries produced by battery production equipment corresponding to a battery verification period, calculating the ratio of the quantity of the low-quality batteries to the total quantity of new energy power batteries produced by the battery production equipment corresponding to the battery verification period to obtain a poor ratio, calculating the quantity of the low-quality batteries to the poor ratio to obtain a poor value, comparing the poor value with a preset poor threshold value in a numerical mode, generating a verification early warning signal if the poor value exceeds the preset poor threshold value, and otherwise generating a verification normal signal.
Further, the specific operation process of the real-time production supervision and analysis module comprises the following steps:
acquiring a last maintenance date of corresponding battery production equipment, calculating a time difference between the last maintenance date and a current date to obtain a maintenance interval duration, acquiring a starting time of current operation of the corresponding battery production equipment, calculating a time difference between the current time and the starting time of the current operation to obtain an operation duration, analyzing and acquiring a fault time difference value, calculating a value of the fault time difference value, the maintenance interval duration and the operation duration to obtain a risk value, comparing the risk value with a preset risk threshold value, and generating a risk early warning signal if the risk value exceeds the preset risk threshold value;
otherwise, setting a supervision period, setting a plurality of time points in the supervision period, marking the time points as u, wherein u is a natural number larger than 1, collecting a noise intensity excess value, a dust concentration excess value, a vibration amplitude excess value and a vibration frequency excess value which are generated by battery production equipment corresponding to the time point u, carrying out numerical calculation on the noise intensity excess value, the dust concentration excess value, the vibration amplitude excess value and the vibration frequency excess value to obtain an abnormal excess value, marking the abnormal excess value exceeding a preset abnormal excess threshold as a bad value, carrying out ratio calculation on the number of bad values and the number of abnormal excess values in the supervision period to obtain a bad coefficient, and carrying out numerical calculation on the bad coefficient and the number of bad values to obtain a bad reaction value; and if the adverse reaction value exceeds a preset adverse reaction threshold value, generating a supervision early warning signal.
Further, the specific analysis and acquisition method of the fault time difference value is as follows:
and taking the current time as a time end point to trace forward and define a tracing period, collecting faults generated by corresponding battery production equipment in the tracing period and time corresponding to each fault, performing time difference calculation on time corresponding to two adjacent groups of faults to obtain fault occurrence interval time, establishing a time length set of all fault occurrence interval time in the tracing period, eliminating the maximum value and the minimum value in the time length set, performing summation calculation on the rest subsets and taking an average value to obtain a fault time average value, performing time difference calculation on the current time and the occurrence time of the last fault to obtain a near-fault value, and performing difference calculation on the near-fault value and the fault time average value to obtain a fault time difference value.
Further, the specific operation process of the equipment processing detection management module comprises the following steps:
setting a management period, collecting yield data corresponding to battery production equipment in the management period, generating a yield shortage signal if the yield data does not exceed a preset yield data threshold, otherwise, collecting waste liquid capacity and waste gas discharge capacity corresponding to the battery production equipment in the management period, performing numerical calculation on the waste liquid capacity, the waste gas discharge capacity and the yield data corresponding to the battery production equipment in the management period to obtain a management coefficient, performing numerical comparison on the management coefficient and a preset management coefficient, and generating a management abnormality signal if the management coefficient exceeds the preset management coefficient threshold.
Further, the server is in communication connection with the equipment area supervision and analysis module, the server generates an area supervision and analysis signal and sends the area supervision and analysis signal to the equipment area supervision and analysis module, the equipment area supervision and analysis module receives the area supervision and analysis signal and then analyzes the equipment area, whether an area early warning signal is generated or not is judged through the equipment area analysis, the area early warning signal is sent to the fault supervision and early warning module through the server, and the fault supervision and early warning module sends corresponding early warning.
Further, the specific analysis process of the device area analysis is as follows:
marking a circle with a radius of R1 by taking corresponding battery production equipment as a circle center, marking a corresponding circular area as a target area, collecting a monitoring image in the target area corresponding to a supervision period, presetting a group of preset type risk values corresponding to each behavior type, acquiring all the dangerous behaviors based on the monitoring image in the target area, classifying all the dangerous behaviors to obtain a plurality of groups of behavior types, performing product calculation on the occurrence times of the dangerous behaviors of the corresponding behavior types and the corresponding preset type risk values, marking the product calculation result as a line risk value, and performing summation calculation on all the line risk values to obtain a zone risk value; and comparing the zone risk value with a preset zone risk threshold value, and generating a zone early warning signal if the zone risk value exceeds the preset zone risk threshold value.
Further, the server is in communication connection with the fault supervision terminal, and the server sends a verification early warning signal, a risk early warning signal, a supervision early warning signal or a management abnormal signal to the fault supervision terminal, and when a manager of the fault supervision terminal receives the corresponding signal, comprehensive inspection and maintenance of corresponding battery production equipment are timely carried out so as to ensure safe and efficient operation of the battery production equipment; and the server sends the regional early warning signal to the fault supervision terminal, and when the manager of the fault supervision terminal receives the regional early warning signal, the manager of the fault supervision terminal can timely strengthen personnel supervision of the corresponding region so as to ensure the safety of the battery production process.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, the battery verification statistical module is used for analyzing to judge whether the target battery i is a low-quality battery, the verification early warning signal or the verification normal signal is generated through analysis, the real-time production supervision and analysis module is used for analyzing the corresponding battery production equipment to judge whether the risk early warning signal of the corresponding battery production equipment is generated, the supervision and early warning signal of the corresponding battery production equipment is judged to be generated through continuous analysis when the risk early warning signal is not generated, the equipment processing detection management module is used for analyzing the processing condition of the corresponding battery production equipment in the management period to judge whether the management abnormal signal of the corresponding battery production equipment is generated, the fault prediction is realized through a mode of multi-step analysis and combination, the prediction result is more accurate and the workload of personnel is obviously reduced, and the fault supervision and maintenance of battery production is facilitated;
2. according to the invention, the equipment area supervision and analysis module is used for setting the target area of the corresponding battery production equipment, carrying out equipment area analysis on the target area, judging whether to generate an area early warning signal through the equipment area analysis, sending the area early warning signal to the fault supervision and early warning module through the server, sending the corresponding early warning through the fault supervision and early warning module, and timely reinforcing personnel supervision of the corresponding area when a manager receives the area early warning signal so as to ensure the safety of the battery production process and further reduce the potential safety hazard in the operation process of the corresponding battery production equipment.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
fig. 1 is an overall system block diagram of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: as shown in fig. 1, the fault supervision and maintenance system for new energy power battery production provided by the invention comprises a server, a battery verification and statistics module, a real-time production supervision and analysis module, an equipment processing detection and management module and a fault supervision and early warning module, wherein the server is in communication connection with the battery verification and statistics module, the real-time production supervision and analysis module, the equipment processing detection and management module and the fault supervision and early warning module; the battery verification statistics module is used for setting a battery verification period, marking a new energy power battery produced by battery production equipment corresponding to the battery verification period as a target battery i, wherein i is a natural number larger than 1, analyzing and judging whether the target battery i is a low-quality battery or not, and generating a verification early warning signal or a verification normal signal through analysis, wherein the specific operation process of the battery verification statistics module is as follows:
performing quality detection on the target battery i through a battery detection instrument to obtain real-time data of all battery performance detection items (including appearance flaw conditions, discharge performance, charging performance, capacitance and the like), performing numerical comparison on the real-time data of the corresponding battery performance detection items and corresponding preset real-time data ranges which are input and stored in advance, and marking the corresponding battery performance detection items as unimpeded items if the real-time data of the corresponding battery performance detection items are located in the corresponding preset real-time data ranges; if the real-time data of the corresponding battery performance detection item is not in the corresponding preset real-time data range, marking the real-time data of the corresponding battery performance detection item as a performance deviation value compared with a deviation value of the corresponding preset real-time data range, performing numerical comparison between the performance deviation value and a corresponding preset performance deviation threshold value, marking the corresponding battery performance detection item as a high event item if the performance deviation value exceeds the corresponding preset performance deviation threshold value, and marking the corresponding battery performance detection item as a low event item if the performance deviation value does not exceed the corresponding preset performance deviation threshold value;
obtaining the number of unimpaired items, the number of high items and the number of low items of the target battery i, marking the number of unimpaired items, the number of high items and the number of low items as WAi, GGi and DGi respectively, and carrying out normalization calculation on the number of unimpaired items WAi, the number of high items GGi and the number of low items DGi of the target battery i by the formula HXi = (a2× GGi +a3×DGi)/(a1× WAi +0.734) to obtain a battery performance value HXi; wherein a1, a2 and a3 are preset proportionality coefficients, a2 > a3 > a1 > 0; and, the larger the value of the battery performance value HXi, the worse the battery performance of the target battery i; comparing the battery performance value with a preset battery performance threshold value, and if the battery performance value exceeds the preset battery performance threshold value, marking the target battery i as a low-quality battery;
collecting the quantity ZS of low-quality batteries produced by battery production equipment corresponding to a battery verification period, calculating the ratio of the quantity of the low-quality batteries to the total quantity of new energy power batteries produced by the battery production equipment corresponding to the battery verification period to obtain a poor ratio SB, and calculating the quantity ZS of the low-quality batteries and the poor ratio SB by a formula JL=b1×ZS+b2×SB to obtain a poor correction value JL, wherein b1 and b2 are preset weight coefficients, and b2 is larger than b1 and larger than 1; and the value of the correction value JL is in a direct proportion relation with the number of the low-quality batteries and the reject ratio, and the larger the value of the correction value JL is, the worse the battery verification period is corresponding to the whole quality of the battery produced by the battery production equipment, and the greater the possibility of fault abnormality of the corresponding battery production equipment is; and comparing the value of the deterioration with a preset deterioration threshold value, if the value of the deterioration exceeds the preset deterioration threshold value, generating a check early warning signal, otherwise, generating a check normal signal. And the server sends the verification early warning signal to the fault supervision early warning module, and the fault supervision early warning module sends corresponding early warning after receiving the verification early warning signal, so that equipment checking and maintenance are conveniently and timely carried out to ensure the safe and efficient operation of the equipment and improve the quality of the produced product.
The real-time production supervision and analysis module is used for analyzing the corresponding battery production equipment, judging whether a risk early warning signal of the corresponding battery production equipment is generated through analysis, judging whether a supervision early warning signal of the corresponding battery production equipment is generated through analysis when judging that the risk early warning signal is not generated, sending the risk early warning signal or the supervision early warning signal to the fault supervision early warning module through the server, and sending out the corresponding early warning when the fault supervision early warning module receives the risk early warning signal or the supervision early warning signal so as to perform comprehensive inspection and maintenance of the corresponding battery production equipment in time and ensure the follow-up safe and efficient operation of the battery production equipment; the specific operation process of the real-time production supervision and analysis module is as follows:
collecting the last maintenance date of corresponding battery production equipment, performing time difference calculation on the last maintenance date and the current date to obtain a maintenance interval duration TK, collecting the starting time of the current operation of the corresponding battery production equipment, performing time difference calculation on the current time and the starting time of the current operation to obtain an operation duration TP, taking the current time as a time end point to trace forward and define a tracing period, collecting faults generated by the corresponding battery production equipment in the tracing period and the time corresponding to each fault, performing time difference calculation on the time corresponding to two adjacent groups of faults to obtain a fault occurrence interval duration, establishing a duration set of all fault occurrence interval durations in the tracing period, removing the maximum value and the minimum value in the duration set, performing summation calculation and taking an average value of the rest subsets in the duration set to obtain a fault time average value, performing time difference calculation on the current time and the occurrence time of the adjacent last fault to obtain a near fault value, and performing difference calculation on the near fault value and the fault time average value to obtain a fault time difference value GS; preferably, if the value of the difference value GS at the time of failure is a non-positive number, the value is expressed as zero;
carrying out numerical calculation on the fault time difference value GS, the maintenance interval duration TK and the operation duration TP through a formula PX=fu1, GS+fu2 and TK+fu3, and obtaining a risk value PX, wherein fu1, fu2 and fu3 are preset weight coefficients, and fu1 is more than fu2 is more than fu3 is more than 0; the larger the value of the risk value is, the larger the risk that the corresponding battery production equipment continues to operate is, the more the current risk that the battery production equipment needs to be overhauled and maintained in time to ensure the subsequent operation safety is, the value of the risk value is compared with a preset risk threshold value, and if the risk value exceeds the preset risk threshold value, a risk early warning signal is generated;
if the running risk value does not exceed the preset running risk threshold value, a supervision period is set, a plurality of time points are set in the supervision period, the time points are marked as u, u is a natural number larger than 1, the noise intensity exceeding value ZCu, the dust concentration exceeding value FCu, the vibration amplitude exceeding value HCu and the vibration frequency exceeding value PCu, which are generated by corresponding battery production equipment, are acquired, wherein the noise intensity exceeding value is a data value representing the exceeding value of the noise intensity generated in the running process of the corresponding battery production equipment compared with the preset noise intensity threshold value, and the meanings of the dust concentration exceeding value FCu, the vibration amplitude exceeding value HCu and the vibration frequency exceeding value PCu can be known in the same way; numerical calculation is performed on the noise intensity excess value ZCu, the dust concentration excess value FCu, the vibration amplitude excess value HCu and the vibration frequency excess value PCu through a formula YCu =eu1+eu2+ FCu +eu3+ HCu +eu4 to obtain an abnormal excess value YCu;
wherein, eu1, eu2, eu3, and eu4 are preset weight coefficients, and eu1 > eu3 > eu4 > eu2 > 0; and, the larger the value of the different excess value YCu is, the worse the operation condition of the battery production equipment corresponding to the time point u is indicated; the abnormal supervalue is compared with a preset abnormal superthreshold value in a numerical mode, the abnormal supervalue exceeding the preset abnormal superthreshold value is marked as an abnormal value, the number of the abnormal values and the number of the abnormal supervalues in a supervision period are subjected to ratio calculation to obtain an abnormal coefficient HG, and the abnormal coefficient HG and the number HS of the abnormal values are subjected to numerical calculation through a formula FX=et1+et2 HS to obtain an adverse reaction value FX; wherein, et1 and et2 are preset weight coefficients, and et1 is more than et2 is more than 0; and the larger the value of the adverse reaction value FX is, the greater the possibility that the fault abnormality exists in the operation condition of the corresponding battery production equipment in the supervision period is indicated; and comparing the adverse reaction value with a preset adverse reaction threshold value, and generating a supervision early warning signal if the adverse reaction value exceeds the preset adverse reaction threshold value.
The equipment processing detection management module is used for setting a management period, analyzing the processing condition of the corresponding battery production equipment in the management period, judging whether to generate a management abnormal signal of the corresponding battery production equipment through analysis, sending the management abnormal signal to the fault supervision and early warning module through the server, and sending out the corresponding early warning after the fault supervision and early warning module receives the management abnormal signal, so that the comprehensive inspection and maintenance of the corresponding battery production equipment can be performed in time, and the subsequent safe and efficient operation of the battery production equipment can be ensured; the specific operation process of the equipment processing detection management module is as follows:
setting a management period, collecting yield data CS of corresponding battery production equipment in the management period, generating a yield shortage signal if the yield data does not exceed a preset yield data threshold, checking production conditions and personnel operation conditions in time when the yield shortage signal is generated, collecting waste weight FZ generated by the corresponding battery production equipment in the management period if the yield data exceeds the preset yield data threshold, collecting waste liquid capacity RL and waste gas discharge quantity QL generated by the corresponding battery production equipment in the management period, and calculating the waste material weight FZ, the waste liquid capacity RL, the waste gas discharge quantity QL and the yield data CS by a formula GX= (tf 1. F1. Times. FZ+tf 2. Times. RL+tf 3. Times. QL)/(tf 4. Times. CS+1.216) to obtain a management coefficient GX;
wherein tf1, tf2, tf3, tf4 are preset proportionality coefficients, values of tf1, tf2, tf3, tf4 are all greater than zero, and in the process of producing the new energy power battery corresponding to the battery production equipment, if the generated waste weight FZ is greater, the generated waste liquid capacity RL is greater, the generated waste gas discharge amount QL is greater, the value of the relative management coefficient GX is greater, which indicates that the processing condition of the corresponding battery production equipment is worse in the management period; and comparing the management coefficient with a preset management coefficient which is recorded and stored in advance, if the management coefficient exceeds a preset management coefficient threshold value, indicating that the production condition of the battery production equipment corresponding to the management period is poor, generating a management abnormal signal, and if the management coefficient does not exceed the preset management coefficient threshold value, indicating that the production condition of the battery production equipment corresponding to the management period is good.
Further, the server is in communication connection with the fault supervision terminal, and the server sends a verification early warning signal, a risk early warning signal, a supervision early warning signal or a management abnormal signal to the fault supervision terminal, and when a manager of the fault supervision terminal receives the corresponding signal, comprehensive inspection and maintenance of corresponding battery production equipment are timely carried out so as to ensure safe and efficient operation of the battery production equipment.
Embodiment two: as shown in fig. 1, the difference between the present embodiment and embodiment 1 is that the server is communicatively connected to the device region supervision and analysis module, the server generates a region supervision and analysis signal and sends the region supervision and analysis signal to the device region supervision and analysis module, the device region supervision and analysis module performs device region analysis after receiving the region supervision and analysis signal, determines whether to generate a region early warning signal through device region analysis, sends the region early warning signal to the fault supervision and early warning module through the server, and the fault supervision and early warning module sends a corresponding early warning. The server sends the regional early warning signal to the fault supervision terminal, and when a manager of the fault supervision terminal receives the regional early warning signal, personnel supervision of a corresponding region is enhanced in time, so that the safety of a battery production process is ensured, and potential safety hazards in the operation process of corresponding battery production equipment are further reduced; the specific analysis process of the device area analysis is as follows:
marking a circle with a radius of R1 by taking corresponding battery production equipment as a circle center, preferably, marking a corresponding circular area as a target area, collecting monitoring images in the target area corresponding to a supervision period, presetting that each behavior type corresponds to a group of preset type risk values, acquiring all hazard behaviors (hazard behaviors refer to improper behaviors of personnel in the corresponding area and comprise smoking, alarm and the like) based on the monitoring images in the target area, classifying all hazard behaviors to obtain a plurality of groups of behavior types, performing product calculation on the hazard behavior occurrence times of the corresponding behavior types and the corresponding preset type risk values, marking the product calculation result as a row risk value, and summing all row risk values to obtain a zone risk value; and comparing the zone risk value with a preset zone risk threshold value, if the zone risk value exceeds the preset zone risk threshold value, indicating that the corresponding battery production equipment is in the zone where the monitoring is to be enhanced, generating a zone early warning signal, and if the zone risk value exceeds the preset zone risk threshold value, not generating a zone early warning signal.
The working principle of the invention is as follows: when the system is used, the new energy power battery produced by the battery production equipment corresponding to the battery verification period is marked as a target battery i through the battery verification statistics module, whether the target battery i is a low-quality battery or not is judged through analysis, a verification early warning signal or a verification normal signal is generated through analysis, and the server sends the verification early warning signal to the fault supervision early warning module so as to enable the fault supervision early warning module to send corresponding early warning, so that equipment checking and maintenance are convenient and timely to ensure safe and efficient operation of the equipment, and the quality of produced products is improved; the real-time production supervision and analysis module analyzes the corresponding battery production equipment to judge whether a risk early warning signal of the corresponding battery production equipment is generated or not, and judges whether a supervision early warning signal of the corresponding battery production equipment is generated or not through continuous analysis when the risk early warning signal is not generated, so that comprehensive inspection and maintenance of the corresponding battery production equipment can be performed in time, and subsequent safe and efficient operation of the battery production equipment is ensured; the equipment processing detection management module analyzes the processing condition of the corresponding battery production equipment in the management period, judges whether to generate a management abnormal signal of the corresponding battery production equipment through analysis, sends the management abnormal signal to the fault supervision and early warning module through the server so as to enable the fault supervision and early warning module to send corresponding early warning, so that comprehensive inspection and maintenance of the corresponding battery production equipment can be conducted in time, follow-up safe and efficient operation of the battery production equipment is guaranteed, fault prediction is achieved through a mode of multi-step analysis and combination, a prediction result is more accurate, workload of personnel is obviously reduced, and fault supervision and maintenance of battery production is facilitated.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (2)
1. The fault supervision and maintenance system for the production of the new energy power battery is characterized by comprising a server, a battery verification and statistics module, a real-time production supervision and analysis module, an equipment processing detection management module and a fault supervision and early warning module; the battery verification statistics module is used for setting a battery verification period, marking a new energy power battery produced by battery production equipment corresponding to the battery verification period as a target battery i, wherein i is a natural number larger than 1, analyzing and judging whether the target battery i is a low-quality battery or not, generating a verification early-warning signal or a verification normal signal through analysis, sending the verification early-warning signal or the verification normal signal to the server, sending the verification early-warning signal to the fault supervision early-warning module by the server, and sending a corresponding early warning after the fault supervision early-warning module receives the verification early-warning signal;
the real-time production supervision and analysis module is used for analyzing the corresponding battery production equipment, judging whether a risk early warning signal of the corresponding battery production equipment is generated through analysis, judging whether a supervision early warning signal of the corresponding battery production equipment is generated through analysis when judging that the risk early warning signal is not generated, sending the risk early warning signal or the supervision early warning signal to the fault supervision early warning module through the server, and sending a corresponding early warning when the fault supervision early warning module receives the risk early warning signal or the supervision early warning signal; the equipment processing detection management module is used for setting a management period, analyzing the processing conditions of the corresponding battery production equipment in the management period, judging whether to generate a management abnormal signal of the corresponding battery production equipment through analysis, sending the management abnormal signal to the fault supervision and early warning module through the server, and sending a corresponding early warning after the fault supervision and early warning module receives the management abnormal signal;
the specific operation process of the battery verification and statistics module comprises the following steps:
performing quality detection on the target battery i through a battery detection instrument to acquire real-time data of all battery performance detection items, performing numerical comparison on the real-time data of the corresponding battery performance detection items and a corresponding preset real-time data range, and marking the corresponding battery performance detection items as unimpeded items if the real-time data of the corresponding battery performance detection items are located in the corresponding preset real-time data range; if the real-time data of the corresponding battery performance detection item is not in the corresponding preset real-time data range, marking the real-time data of the corresponding battery performance detection item as a performance deviation value compared with the deviation value of the corresponding preset real-time data range, if the performance deviation value exceeds a preset performance deviation threshold, marking the corresponding battery performance detection item as a high event item, otherwise marking the corresponding battery performance detection item as a low event item;
normalizing the number WAi of unimpeded terms, the number GGi of high terms and the number DGi of low terms of the target battery i by a formula HXi = (a2× GGi +a3×dgi)/(a1× WAi +0.734) to obtain a battery performance value HXi; wherein a1, a2 and a3 are preset proportionality coefficients, a2 > a3 > a1 > 0; comparing the battery performance value with a preset battery performance threshold value, and if the battery performance value exceeds the preset battery performance threshold value, marking the target battery i as a low-quality battery;
collecting the number of low-quality batteries produced by battery production equipment corresponding to a battery verification period, calculating the ratio of the number of the low-quality batteries to the total number of new energy power batteries produced by the battery production equipment corresponding to the battery verification period to obtain a poor ratio, and calculating the number ZS of the low-quality batteries and the poor ratio SB by a formula JL=b1+b2 to obtain a poor value JL, wherein b1 and b2 are preset weight coefficients, and b2 is larger than b1 and larger than 1; comparing the value of the deterioration with a preset deterioration threshold value, if the value of the deterioration exceeds the preset deterioration threshold value, generating a checking early warning signal, otherwise, generating a checking normal signal;
the specific operation process of the real-time production supervision and analysis module comprises the following steps:
acquiring a last maintenance date of corresponding battery production equipment, performing time difference calculation on the last maintenance date and the current date to obtain maintenance interval duration, acquiring starting time of current operation of the corresponding battery production equipment, performing time difference calculation on the current time and the starting time of the current operation to obtain operation duration, analyzing and obtaining a fault time difference value, and performing numerical calculation on the fault time difference value GS, the maintenance interval duration TK and the operation duration TP through a formula PX=fu1+fu2+TK+fu3×TP to obtain a risk transport value PX, wherein fu1, fu2 and fu3 are preset weight coefficients, and fu1 > fu2 > fu3 > 0; comparing the risk value with a preset risk threshold value, and generating a risk early warning signal if the risk value exceeds the preset risk threshold value;
otherwise, setting a supervision period, setting a plurality of time points in the supervision period, marking the time points as u, wherein u is a natural number larger than 1, collecting a noise intensity exceeding value, a dust concentration exceeding value, a vibration amplitude exceeding value and a vibration frequency exceeding value which are generated by battery production equipment corresponding to the time point u, and carrying out numerical calculation on the noise intensity exceeding value ZCu, the dust concentration exceeding value FCu, the vibration amplitude exceeding value HCu and the vibration frequency exceeding value PCu through a formula YCu =eu1× ZCu +eu2× FCu +eu3× HCu +eu4×pcu to obtain an abnormal exceeding value YCu; wherein, eu1, eu2, eu3, and eu4 are preset weight coefficients, and eu1 > eu3 > eu4 > eu2 > 0;
marking the abnormal value exceeding a preset abnormal super-threshold value as a bad value, calculating the ratio of the number of the bad values to the number of the abnormal values in the supervision period to obtain a bad coefficient, and calculating the number HS of the bad coefficient HG and the bad value to obtain a bad response value FX through a formula FX=et1+et2+HS; wherein, et1 and et2 are preset weight coefficients, and et1 is more than et2 is more than 0; if the adverse reaction value exceeds a preset adverse reaction threshold value, generating a supervision early warning signal;
the specific analysis and acquisition method of the fault time difference value is as follows:
the current time is taken as a time terminal point to trace forward and define a tracing period, faults generated by corresponding battery production equipment in the tracing period and the time corresponding to each fault are acquired, time difference calculation is carried out on the time corresponding to two adjacent groups of faults to obtain fault occurrence interval time, a time length set is established on all fault occurrence interval time lengths in the tracing period, the maximum value and the minimum value in the time length set are removed, the rest subsets are summed and calculated, an average value is obtained, the current time and the occurrence time of the last fault are calculated to obtain a near-event value, and difference calculation is carried out on the near-event value and the average value to obtain a fault time difference value;
the specific operation process of the equipment processing detection management module comprises the following steps:
setting a management period, collecting yield data of corresponding battery production equipment in the management period, generating a yield shortage signal if the yield data does not exceed a preset yield data threshold value, otherwise, collecting waste material weight generated by the battery production equipment corresponding to the management period, and collecting waste liquid capacity and waste gas discharge amount generated by the battery production equipment corresponding to the management period, wherein the waste material weight FZ, the waste liquid capacity RL, the waste gas discharge amount QL and the yield data CS are subjected to numerical calculation through a formula GX= (tf 1 x FZ+tf2 x RL+tf3 x QL)/(tf 4 x CS+1.216) to obtain a management coefficient GX; wherein tf1, tf2, tf3, tf4 are preset proportionality coefficients, and values of tf1, tf2, tf3, tf4 are all greater than zero; comparing the management coefficient with a preset management coefficient in a numerical value, and generating a management abnormal signal if the management coefficient exceeds a preset management coefficient threshold;
the server is in communication connection with the equipment area supervision and analysis module, the server generates an area supervision and analysis signal and sends the area supervision and analysis signal to the equipment area supervision and analysis module, the equipment area supervision and analysis module receives the area supervision and analysis signal and then performs equipment area analysis, whether an area early warning signal is generated or not is judged through equipment area analysis, the area early warning signal is sent to the fault supervision and early warning module through the server, and the fault supervision and early warning module sends corresponding early warning;
the specific analysis process of the device area analysis is as follows:
marking a circle with a radius of R1 by taking corresponding battery production equipment as a circle center, marking a corresponding circular area as a target area, collecting a monitoring image in the target area corresponding to a supervision period, presetting a group of preset type risk values corresponding to each behavior type, acquiring all the dangerous behaviors based on the monitoring image in the target area, classifying all the dangerous behaviors to obtain a plurality of groups of behavior types, performing product calculation on the occurrence times of the dangerous behaviors of the corresponding behavior types and the corresponding preset type risk values, marking the product calculation result as a line risk value, and performing summation calculation on all the line risk values to obtain a zone risk value; and comparing the zone risk value with a preset zone risk threshold value, and generating a zone early warning signal if the zone risk value exceeds the preset zone risk threshold value.
2. The fault supervision and maintenance system for new energy power battery production according to claim 1, wherein the server is in communication connection with the fault supervision terminal, and the server sends a verification early warning signal, a risk early warning signal, a supervision early warning signal or a management abnormality signal to the fault supervision terminal, and a manager of the fault supervision terminal timely performs comprehensive inspection and maintenance of corresponding battery production equipment when receiving the corresponding signal so as to ensure safe and efficient operation of the battery production equipment; and the server sends the regional early warning signal to the fault supervision terminal, and when the manager of the fault supervision terminal receives the regional early warning signal, the manager of the fault supervision terminal can timely strengthen personnel supervision of the corresponding region so as to ensure the safety of the battery production process.
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Denomination of invention: Fault supervision and maintenance system for the production of new energy power batteries Granted publication date: 20240209 Pledgee: Bank of Shanghai Limited by Share Ltd. Shenzhen branch Pledgor: SHENZHEN TAIKE POWER SYSTEM Co.,Ltd. Registration number: Y2024980015416 |