CN116026534B - Filling equipment gas tightness detecting system based on thing networking - Google Patents
Filling equipment gas tightness detecting system based on thing networking Download PDFInfo
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Abstract
The invention belongs to the technical field of filling equipment detection, in particular to a filling equipment air tightness detection system based on the Internet of things, which comprises an Internet of things detection and analysis platform, wherein the Internet of things detection and analysis platform comprises a server, and the server is in communication connection with a filling live monitoring module, a data storage module, a detection urgency analysis module, an equipment air tightness detection and analysis module and an equipment early warning module; according to the invention, the accuracy of the air tightness detection result is improved through the air tightness detection analysis based on the multi-data by the equipment air tightness detection analysis module, the real-time monitoring analysis and judgment are carried out through the filling live monitoring module during filling, the detection urgency analysis module carries out urgency analysis on the corresponding filling equipment, the operation monitoring backtracking module carries out retrospective analysis of detection operation, and the effective combination of the filling process monitoring analysis, the air tightness detection analysis based on the multi-data and the detection urgency analysis and the detection operation backtracking analysis is realized, so that the intelligent degree is high.
Description
Technical Field
The invention relates to the technical field of filling equipment detection, in particular to a filling equipment air tightness detection system based on the Internet of things.
Background
Filling equipment belongs to a class of products in a packaging machine, and can be classified into a liquid filling machine, a paste filling machine, a powder filling machine or a particle filling machine from the aspect of material packaging, and classified into a semi-automatic filling machine or a full-automatic filling machine from the aspect of production automation; the air tightness detection of the filling equipment is mainly used for detecting whether a leakage point exists on the filling equipment, when the leakage point exists on the filling equipment, the filling equipment should be maintained in time, and at present, air is mainly filled into the closed filling equipment through the air tightness detection equipment and the internal air pressure change is observed to realize the air tightness detection; however, potential influencing factors in the air tightness detection process are not considered in the prior art, the potential influencing factors mainly comprise the temperature change in equipment and the vibration degree of the equipment, so that a large deviation exists in an air tightness detection result, the air tightness detection result is inaccurate, the monitoring analysis of the filling process, the air tightness detection analysis based on multivariate data, the detection urgency analysis and the detection operation retrospective analysis cannot be combined, the intelligent degree is low, and the function is single;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide a filling equipment air tightness detection system based on the Internet of things, which solves the problems that potential influence factors in the air tightness detection process are not considered in the prior art, so that a large deviation exists in an air tightness detection result, and the monitoring analysis of the filling process, the air tightness detection analysis based on multivariate data, the detection urgency analysis and the detection operation retrospective analysis cannot be combined, so that the intelligent degree is low.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the filling equipment air tightness detection system based on the Internet of things comprises an Internet of things detection analysis platform, wherein the Internet of things detection analysis platform comprises a server, a data storage module, a filling live monitoring module, a detection urgency analysis module, an equipment air tightness detection analysis module and an equipment early warning module, and the server is in communication connection with the filling live monitoring module, the data storage module, the detection urgency analysis module, the equipment air tightness detection analysis module and the equipment early warning module; the filling live monitoring module is used for carrying out real-time monitoring analysis on corresponding filling equipment when filling is carried out, judging whether to generate a filling early warning signal or a filling adjusting signal through the real-time monitoring analysis, and sending the filling early warning signal or the filling adjusting signal to the equipment early warning module through the server when the filling early warning signal or the filling adjusting signal is generated;
The detection urgency analysis module is used for carrying out urgency analysis on the corresponding filling equipment, judging whether an urgency early warning signal is generated or not based on an urgency analysis result, and sending the urgency early warning signal to the equipment early warning module through the server when the urgency early warning signal is generated; the equipment air tightness detection analysis module is used for carrying out air tightness detection analysis on the corresponding filling equipment, stopping the current air tightness detection operation when the detection process of the corresponding filling equipment is unstable, continuing to carry out detection analysis when the detection process of the corresponding filling equipment is stable, generating an air tightness disqualification signal or an air tightness qualification signal of the filling equipment, and sending the air tightness disqualification signal or the air tightness qualification signal of the filling equipment to the equipment early warning module through the server;
the equipment early warning module displays corresponding early warning information and sends out corresponding prompt tone and corresponding warning light when receiving the filling early warning signal or the filling adjusting signal and the urgency early warning signal; and displaying text information corresponding to the filling equipment air tightness disqualification signal or the filling equipment air tightness qualification signal when the filling equipment air tightness disqualification signal or the filling equipment air tightness qualification signal is received, and sending corresponding prompt sound and corresponding warning light when the filling equipment air tightness disqualification signal is received.
Further, the specific operation process of the filling live monitoring module comprises the following steps:
acquiring a device weight reduction value of corresponding filling equipment and a material output weight value at an outlet of the corresponding filling equipment when filling is carried out, and carrying out difference calculation on the device weight reduction value and the material output weight value to acquire a filling output difference value; the method comprises the steps of calling a preset filling output difference threshold value through a data storage module, carrying out numerical comparison on a filling output difference value and the filling output difference threshold value, and if the filling output difference value is smaller than or equal to the preset filling output difference threshold value, not generating any signal; and if the filling output difference value is larger than the preset filling output difference threshold value, carrying out filling error analysis.
Further, the specific analysis process of the filling error analysis is as follows:
acquiring a material output speed value and filling equipment vibration data at an outlet of filling equipment, acquiring a preset material output proper speed value through a data storage module, performing difference calculation on a filling output difference value and a preset filling output difference threshold value to acquire filling difference threshold data, performing difference calculation on the material output speed value and the preset material output proper speed value to acquire a speed real deviation value, and performing numerical calculation on the filling difference threshold data, the speed real deviation value and the filling equipment vibration data to acquire an error influence coefficient;
And a preset error influence coefficient threshold value is called through the data storage module, the error influence coefficient is compared with the preset error influence coefficient threshold value in a numerical value mode, a filling early warning signal is generated if the error influence coefficient is larger than or equal to the preset error influence coefficient threshold value, and a filling adjusting signal is generated if the error influence coefficient is smaller than the preset error influence coefficient threshold value.
Further, the specific operation process of the detecting urgency analysis module comprises:
obtaining dates of a plurality of times of air tightness detection of corresponding filling equipment in unit time, performing difference calculation on the dates of two adjacent times of air tightness detection to obtain detection time difference coefficients, and summing and averaging a plurality of groups of detection time difference coefficients in unit time to obtain detection time average difference coefficients; the date of the last air tightness detection is obtained, and the difference value between the current date and the date of the last air tightness detection is calculated to obtain a current detection time value;
calculating the ratio of the current detection interval value to the detection time average difference coefficient to obtain a detection urgency coefficient; the method comprises the steps of calling a preset detection urgency coefficient threshold value through a data storage module, comparing the detection urgency coefficient with the preset urgency coefficient threshold value in a numerical mode, generating an urgency early warning signal if the detection urgency coefficient is larger than or equal to the preset urgency coefficient threshold value, and not generating the urgency early warning signal if the detection urgency coefficient is smaller than the preset urgency coefficient threshold value.
Further, the specific operation process of the equipment air tightness detection and analysis module comprises the following steps:
generating a stability qualified signal or a stability unqualified signal through detection stability analysis, stopping current detection when the stability unqualified signal is generated, acquiring an air pressure initial condition coefficient in corresponding filling equipment after generating the stability qualified signal at an interval of t0, acquiring an air pressure variable condition coefficient in corresponding filling equipment after an interval of t1, wherein t0 and t1 are preset interval periods, and t1 is more than t0 and more than 0;
and calculating the difference value between the air pressure initial condition coefficient and the air pressure variable condition coefficient to obtain an air pressure difference variable coefficient, calling a preset air pressure difference variable coefficient threshold value through a data storage module, performing numerical comparison on the air pressure difference variable coefficient and the preset air pressure difference variable coefficient threshold value, generating an air tightness disqualification signal of the filling equipment if the air pressure difference variable coefficient is larger than or equal to the preset air pressure difference variable coefficient threshold value, and generating an air tightness qualification signal of the filling equipment if the air pressure difference variable coefficient is smaller than the preset air pressure difference variable coefficient threshold value.
Further, the specific analysis procedure for the assay stability analysis is as follows:
acquiring a temperature stability coefficient and a vibration stability coefficient through analysis, calling a preset temperature stability coefficient threshold value and a preset vibration stability coefficient threshold value through a data storage module, respectively comparing the temperature stability coefficient and the vibration stability coefficient with the preset temperature stability coefficient threshold value and the preset vibration stability coefficient threshold value in a numerical mode, and generating a detection stability disqualification signal if at least one of the temperature stability coefficient and the vibration stability coefficient is larger than the corresponding preset threshold value;
And if the temperature stability coefficient and the vibration stability coefficient are smaller than or equal to the corresponding preset thresholds, carrying out numerical calculation on the temperature stability coefficient and the vibration stability coefficient to obtain a stability total analysis value, calling the preset stability total analysis threshold through a data storage module, carrying out numerical comparison on the stability total analysis value and the preset stability total analysis threshold, generating a detection stability disqualification signal if the stability total analysis value is larger than or equal to the preset stability total analysis threshold, and generating a detection stability qualification signal if the stability total analysis value is smaller than the preset stability total analysis threshold.
Further, the analysis and acquisition method of the temperature stability coefficient is specifically as follows:
acquiring real-time temperatures of a plurality of positions in corresponding filling equipment at corresponding detection time points, summing the real-time temperatures of all detection time points in the corresponding positions in the corresponding filling equipment, taking an average value to acquire a live value of the temperature, carrying out difference calculation on the live value of the temperature and a preset standard value of the temperature, and taking an absolute value to acquire a standard deviation value of the temperature; carrying out variance calculation on the real-time temperatures of all detection time points at corresponding positions in corresponding filling equipment to obtain a temperature disturbance value, and carrying out numerical calculation on a temperature mark separation value and the temperature disturbance value to obtain a temperature evaluation value at the corresponding position; acquiring all the temperature evaluation values in the corresponding filling equipment, establishing a temperature evaluation set from all the temperature evaluation values, and carrying out mean value calculation on the temperature evaluation set to acquire a temperature total evaluation value;
The method comprises the steps of calling a preset temperature evaluation threshold value through a data storage module, comparing a temperature evaluation value with the preset temperature evaluation threshold value in a numerical mode, marking the corresponding position of the corresponding filling equipment as a temperature jump zone bit if the temperature evaluation value is larger than or equal to the preset temperature evaluation threshold value, and marking the corresponding position of the corresponding filling equipment as a temperature stable zone bit if the temperature evaluation value is smaller than the preset temperature evaluation threshold value; and carrying out numerical calculation on the total evaluation value of the bit temperature, the number of temperature jump zone bits and the number of temperature stable zone bits to obtain a temperature stability coefficient.
Further, the method for analyzing and acquiring the vibration stability coefficient is specifically as follows:
acquiring vibration frequencies and vibration amplitudes at a plurality of positions on corresponding filling equipment, performing numerical calculation on the vibration frequencies and the vibration amplitudes to acquire vibration frequency amplitude data at the corresponding positions, establishing a vibration frequency amplitude set for the vibration frequency amplitude data at the plurality of positions, and performing mean value calculation on the vibration frequency amplitude set to acquire a vibration frequency amplitude uniform condition value; the method comprises the steps that a preset vibration frequency amplitude judging value is called through a data storage module, vibration frequency amplitude data at a corresponding position is compared with the preset vibration frequency amplitude judging value in a numerical mode, if the vibration frequency amplitude data are larger than or equal to the preset vibration frequency amplitude judging value, the corresponding position is marked as a high vibration position, and if the vibration frequency amplitude data are smaller than the preset vibration frequency amplitude judging value, the corresponding position is marked as a low vibration position; and carrying out numerical calculation on the vibration frequency amplitude average condition value, the number of high vibration sites and the number of low vibration sites to obtain a vibration stability coefficient.
Further, the detection analysis platform of the internet of things further comprises an operation monitoring backtracking module, the server is in communication connection with the operation monitoring backtracking module, after the current air tightness detection operation is finished, the server generates an operation backtracking analysis signal and sends the operation backtracking analysis signal to the operation monitoring backtracking module, the operation monitoring backtracking module is used for carrying out operation backtracking analysis on the current air tightness detection operation after receiving the operation backtracking analysis signal, and an operation efficiency disqualification signal, an operation normalization disqualification signal or an operation backtracking qualification signal are generated based on an operation backtracking analysis result and are sent to the equipment early warning module through the server.
Further, the specific operation process of the operation monitoring backtracking module is as follows:
acquiring the starting time and the ending time of the current air tightness detection operation, and calculating the difference between the ending time and the starting time to acquire an air tightness detection duration value; the method comprises the steps of calling a preset air tightness detection time threshold value through a data storage module, carrying out numerical comparison on the air tightness detection time value and the preset air tightness detection time threshold value, and generating an operation efficiency disqualification signal if the air tightness detection time value is greater than or equal to the preset air tightness detection time threshold value; if the air tightness detection duration value is smaller than the preset air tightness detection duration threshold value, acquiring preset standard operation flow information of air tightness detection operation, dividing the air tightness detection operation into a plurality of operation links based on the preset standard operation flow information, and acquiring the operation duration value of an operator corresponding to the current operation in the corresponding operation link and the frequency of errors;
The method comprises the steps that a preset operation duration threshold value and an error frequency threshold value of a corresponding operation link are called through a data storage module, the operation duration value and the error frequency of a corresponding operator in the corresponding operation link are respectively compared with the corresponding preset operation duration threshold value and the error frequency threshold value in a numerical mode, if the operation duration value and the error frequency of the corresponding operator in the corresponding operation link are smaller than the corresponding threshold value, the corresponding operation link is marked as a qualified link, and the other conditions are marked as unqualified links; and carrying out numerical calculation on the number of qualified links and the number of unqualified links to obtain an operation backtracking coefficient, calling a preset operation backtracking coefficient threshold value through a data storage module, carrying out numerical comparison on the operation backtracking coefficient and the preset operation backtracking coefficient threshold value, and generating an operation normalization unqualified signal if the operation backtracking coefficient is greater than or equal to the preset operation backtracking coefficient threshold value, otherwise, generating an operation backtracking qualified signal.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the equipment air tightness detection analysis module is used for stopping the current air tightness detection operation when the detection process of the corresponding filling equipment is unstable, continuing the detection analysis when the detection process of the corresponding filling equipment is stable, generating an air tightness unqualified signal of the filling equipment or an air tightness qualified signal of the filling equipment, obviously improving the accuracy of an air tightness detection result, and timely checking and maintaining the filling equipment when the corresponding staff receives the air tightness unqualified signal of the filling equipment;
2. In the invention, when filling is carried out, whether a filling early warning signal or a filling adjusting signal is generated is judged by carrying out real-time monitoring analysis through the filling live monitoring module, so that the leak detection of the filling process of the filling equipment is realized, the corresponding staff should carry out the inspection and maintenance of the filling equipment in time when receiving the filling early warning signal, and the equipment adjustment should be carried out in time according to the requirement when receiving the filling adjusting signal so as to ensure the stability of the working process of the equipment and reduce the error influence on the monitoring result of the filling process;
3. according to the invention, the urgency analysis module is used for carrying out urgency analysis on the corresponding filling equipment, and when an urgency early warning signal is generated, the corresponding staff should carry out the air tightness detection of the filling equipment in time so as to ensure the subsequent smooth work of the filling equipment; operation tracing analysis is carried out on the current air tightness detection operation through the operation monitoring tracing module, and air tightness detection operation training for related staff is enhanced later when an operation efficiency disqualified signal or an operation normalization disqualified signal is generated so as to ensure that the subsequent detection operation is carried out efficiently and smoothly.
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;
fig. 2 is a system block diagram of a second embodiment 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 filling equipment air tightness detection system based on the internet of things provided by the invention comprises an internet of things detection and analysis platform, wherein the internet of things detection and analysis platform comprises a server, and the server is in communication connection with a filling live monitoring module, a data storage module, a detection urgency analysis module, an equipment air tightness detection and analysis module and an equipment early warning module; the filling live monitoring module is used for carrying out real-time monitoring analysis on corresponding filling equipment when filling is carried out, and the concrete analysis process of the filling live monitoring module is as follows:
acquiring a device weight reduction value of corresponding filling equipment and a material output weight value at an outlet of the corresponding filling equipment when filling is carried out, and carrying out difference calculation on the device weight reduction value and the material output weight value to acquire a filling output difference value GY; the larger the value of the filling output difference value GY is, the leakage point possibly appears in the filling equipment in the filling process, namely the air tightness of the filling equipment is poor, and the filling equipment needs to be checked and maintained in time, otherwise, the smaller the value of the filling output difference value GY is close to zero, the smaller the possibility that the leakage point exists in the filling equipment is, and the air tightness is better;
The preset filling output difference threshold value is called through the data storage module, is input in advance by corresponding staff and is stored in the data storage module, and is used for judging and analyzing the filling output difference value GY, and preferably, the value of the preset filling output difference threshold value is 2.63; comparing the filling output difference value GY with a filling output difference threshold value in a numerical mode, and if the filling output difference value GY is smaller than or equal to a preset filling output difference threshold value, generating no signal; if the filling output difference value GY is larger than a preset filling output difference threshold value, acquiring a material output speed value at an outlet of filling equipment and filling equipment vibration data which are respectively marked as LC and LZ, wherein the filling equipment vibration data LZ is a data value representing the vibration frequency and the vibration amplitude of the filling equipment, and the material output speed value LC is a data value representing the material output speed;
the filling difference threshold data YY is obtained by carrying out difference calculation on a filling output difference value and a preset filling output difference threshold value, a preset material output proper speed value is called through a data storage module, a material output speed value LC and a preset material output proper speed value are carried out difference calculation, an absolute value is taken, a speed actual deviation value SP is obtained, and a formula is adopted 
Substituting the filling difference threshold data YY, the speed actual deviation value SP and the filling equipment vibration data LZ for numerical calculation, and obtaining an error influence coefficient WYX after the numerical calculation; wherein a1, a2 and a3 are preset proportionality coefficients, and the values of a1, a2 and a3 are all larger than zero;
when the value of the error influence coefficient WYX is too large, the error influence on the monitoring result of the filling process caused by the equipment during filling is smaller, and the greater the possibility that the filling equipment has leakage points; the preset error influence coefficient threshold value is called through the data storage module, is recorded in advance by corresponding staff and is stored in the data storage module, and is used for judging and analyzing the error influence coefficient WYX, and preferably, the value of the preset error influence coefficient threshold value is 3.271; and comparing the error influence coefficient WYX with a preset error influence coefficient threshold value in a numerical mode, generating a filling early warning signal if the error influence coefficient WYX is larger than or equal to the preset error influence coefficient threshold value, and generating a filling adjusting signal if the error influence coefficient WYX is smaller than the preset error influence coefficient threshold value.
When filling is carried out, whether a filling early warning signal or a filling adjusting signal is generated or not is judged by carrying out real-time monitoring analysis through the filling live monitoring module, the filling early warning signal or the filling adjusting signal is sent to the equipment early warning module through the server when the filling early warning signal or the filling adjusting signal is generated, the equipment early warning module displays corresponding filling early warning information or filling adjusting information when the filling early warning signal or the filling adjusting signal is received, and sends corresponding prompt tones and corresponding warning lights, and corresponding staff should timely carry out inspection and maintenance of filling equipment when the filling early warning signal is received, and should timely carry out equipment adjustment according to requirements when the filling adjusting signal is received so as to ensure the stability of the working process of the equipment, thereby reducing error influence brought to monitoring results of the filling process.
The method comprises the steps that a detection urgency analysis module carries out urgency analysis on corresponding filling equipment, whether an urgency early warning signal is generated or not is judged based on an urgency analysis result, the urgency early warning signal is sent to the equipment early warning module through a server when the urgency early warning signal is generated, the equipment early warning module displays corresponding signal text information when the urgency early warning signal is received, corresponding prompt tones and corresponding warning lights are sent, and corresponding staff should carry out air tightness detection on the filling equipment in time when the urgency early warning signal is received; the analysis process of the detection urgency analysis module is as follows:
obtaining dates of a plurality of times of air tightness detection of corresponding filling equipment in unit time, performing difference calculation on the dates of two adjacent times of air tightness detection to obtain detection time difference coefficients, namely, the interval duration of two adjacent times of air tightness detection, summing up a plurality of groups of detection time difference coefficients in unit time, and taking an average value to obtain detection time average difference coefficients, wherein the detection time average difference coefficients are average values representing a plurality of groups of detection interval durations in unit time, namely, average detection interval duration; the date of the last air tightness detection is obtained, compared with the current date, the current date and the date of the last air tightness detection are subjected to difference value calculation to obtain a current detection time value, namely the current detection time value represents the interval duration between the adjacent last air tightness detection time and the current time;
Calculating the ratio of the current detection interval value to the detection time average difference coefficient to obtain a detection urgency coefficient JPX; the preset detection urgency coefficient threshold value is called through the data storage module, is recorded in advance by corresponding staff and is stored in the data storage module, and is used for judging and analyzing the detection urgency coefficient JPX, and preferably, the value of the preset detection urgency coefficient threshold value is 1.213; the detected urgency coefficient JPX is compared with a preset urgency coefficient threshold value in value, if the detected urgency coefficient JPX is greater than or equal to the preset urgency coefficient threshold value, an urgency pre-warning signal is generated, and if the detected urgency coefficient JPX is less than the preset urgency coefficient threshold value, an urgency pre-warning signal is not generated.
When the air tightness of the filling equipment is detected, the corresponding filling equipment is in a cavity state, namely, no material to be filled exists in the filling equipment, then the inlet and the outlet of the corresponding filling equipment are sealed, the interior of the filling equipment is in a sealed state, and finally, air is filled into the corresponding filling equipment through the air inflation pressurizing equipment in the air tightness detecting equipment so as to detect the air tightness; the equipment air tightness detection and analysis module carries out air tightness detection and analysis on the corresponding filling equipment, and the specific analysis process of the air tightness detection and analysis is as follows:
Acquiring real-time temperatures of a plurality of positions in corresponding filling equipment at corresponding detection time points, summing the real-time temperatures of all detection time points in the corresponding positions in the corresponding filling equipment, averaging to acquire a live value of the position temperature in the corresponding positions, and acquiring a preset position temperature standard value through a data storage module, wherein the preset position temperature standard value is recorded in advance by corresponding staff and stored in the data storage module and is suitable for internal air tightness detection, and the value of the preset position temperature standard value is preferably 26.5 ℃; performing difference calculation on the live temperature value and a preset standard temperature value, and taking an absolute value to obtain a standard temperature value BL; carrying out variance calculation on the real-time temperatures of all detection time points at the corresponding positions in the corresponding filling equipment to obtain a temperature disturbance value WL at the corresponding positions;
by the formula
Substituting the temperature mark value BL and the temperature disturbance value WL at the corresponding position to perform numerical calculation, and obtaining a temperature evaluation value WPZ at the corresponding position after the numerical calculation; wherein b1 and b2 are preset weight coefficients, the values of b1 and b2 are both greater than zero, and b1 is smaller than b2; the smaller the value of the temperature evaluation value WPZ is, the more stable the temperature of the corresponding position is, and the smaller the deviation degree from the proper temperature (namely the preset temperature standard value) is, namely the more proper air tightness detection is performed, the larger the value of the temperature evaluation value WPZ is, and the more unfavorable the air tightness detection is performed; acquiring all the temperature evaluation values in the corresponding filling equipment, establishing a temperature evaluation set from all the temperature evaluation values, and carrying out mean value calculation on the temperature evaluation set to acquire a temperature total evaluation value WQ;
The preset temperature evaluation threshold value is called through the data storage module, is recorded in advance by corresponding staff and is stored in the data storage module, and is used for judging and analyzing the temperature evaluation value WPZ, and preferably, the value of the preset temperature evaluation threshold value is 2.833; the method comprises the steps of carrying out numerical comparison on a potential temperature evaluation value WPZ and a preset potential temperature evaluation threshold, marking the corresponding position of corresponding filling equipment as a temperature jump zone bit if the potential temperature evaluation value WPZ is larger than or equal to the preset potential temperature evaluation threshold, and marking the corresponding position of the corresponding filling equipment as a temperature stable zone bit if the potential temperature evaluation value WPZ is smaller than the preset potential temperature evaluation threshold;
the number of temperature jump zone bits and the number of temperature stable zone bits in the corresponding filling equipment are obtained and marked as TB and WB respectively, and the temperature jump zone bits and the temperature stable zone bits are calculated according to the formula
Substituting the total evaluation value WQ of the bit temperature, the number TB of the temperature jump zone bits and the number WB of the temperature stabilization zone bits to carry out numerical calculation to obtain a temperature stability coefficient WDX; wherein b3, b4,b5 is a preset proportionality coefficient, the values of b3, b4 and b5 are all larger than zero, and b4 is larger than b3 and larger than b5; the larger the value of the temperature stability coefficient WDX is, the more unfavorable the air tightness detection is caused by the temperature condition inside the corresponding filling equipment;
Obtaining vibration frequencies PL and vibration amplitudes FD at a plurality of positions on corresponding filling equipment, and obtaining vibration frequency amplitude data PF at the corresponding positions after carrying out numerical calculation on the vibration frequencies PL and the vibration amplitudes FD through a formula PF=k1+k2; wherein k1 and k2 are preset weight coefficients, and the values of k1 and k2 are both larger than zero; the method comprises the steps that a preset vibration frequency amplitude judging value is called through a data storage module, vibration frequency amplitude data PF at a corresponding position is compared with the preset vibration frequency amplitude judging value in a numerical mode, if the vibration frequency amplitude data PF is larger than or equal to the preset vibration frequency amplitude judging value, the corresponding position is marked as a high vibration position, and if the vibration frequency amplitude data PF is smaller than the preset vibration frequency amplitude judging value, the corresponding position is marked as a low vibration position;
establishing a vibration frequency amplitude set from vibration frequency amplitude data PF at a plurality of positions, and carrying out mean value calculation on the vibration frequency amplitude set to obtain a vibration frequency amplitude mean condition value ZJ; the number of high vibration sites and the number of low vibration sites in the corresponding filling equipment are obtained and marked as GZ and DZ respectively, and the formulas are used for preparing the high vibration sites and the low vibration sites
Substituting the vibration frequency amplitude average condition value ZJ, the high vibration site number GZ and the low vibration site number DZ for numerical calculation, and obtaining a vibration stability coefficient ZWX after the numerical calculation; wherein k3, k4 and k5 are preset proportionality coefficients, the values of k3, k4 and k5 are all larger than zero, and k4 is larger than k3 and larger than k5; the larger the value of the vibration stability coefficient ZWX is, the more unfavorable the vibration condition of the corresponding filling equipment is in detection, so that the accuracy of the air tightness detection result is improved;
A preset temperature stability coefficient threshold value and a preset vibration stability coefficient threshold value are called through a data storage module, the preset temperature stability coefficient threshold value and the preset vibration stability coefficient threshold value are recorded in advance by corresponding staff and stored in the data storage module, the data storage module is used for judging and analyzing the temperature stability coefficient WDX and the vibration stability coefficient ZWX, the temperature stability coefficient WDX and the vibration stability coefficient ZWX are respectively compared with the preset temperature stability coefficient threshold value and the preset vibration stability coefficient threshold value in numerical value, and if at least one of the temperature stability coefficient WDX and the vibration stability coefficient ZWX is larger than the corresponding preset threshold value, a detection stability disqualification signal is generated;
if both the temperature stability coefficient WDX and the vibration stability coefficient ZWX are smaller than or equal to the corresponding preset thresholds, performing numerical calculation on the temperature stability coefficient WDX and the vibration stability coefficient ZWX through a formula wzx=g1 wdx+g2 ZWX to obtain a stability total analysis value WZX; wherein, gh1 and gh2 are preset weight coefficients, the values of the gh1 and the gh2 are both larger than zero, and the gh1 is larger than the gh2; the method comprises the steps of calling a preset stability total analysis threshold value through a data storage module, carrying out numerical comparison on a stability total analysis value WZX and the preset stability total analysis threshold value, generating a detection stability disqualification signal if the stability total analysis value WZX is larger than or equal to the preset stability total analysis threshold value, and generating a detection stability qualification signal if the stability total analysis value WZX is smaller than the preset stability total analysis threshold value;
The current detection is stopped when the stability disqualification signal is generated, the air pressure initial condition coefficient YK in the corresponding filling equipment is obtained after the stability disqualification signal is generated and the time interval t0, the air pressure variable condition coefficient YB in the corresponding filling equipment is obtained after the time interval t1, and t0 and t1 are preset time intervals, wherein t1 is more than t0 is more than 0; calculating the difference value between the air pressure initial condition coefficient YK and the air pressure variable condition coefficient YB to obtain an air pressure difference variable coefficient YCX, wherein the larger the value of the air pressure difference variable coefficient YCX is, the larger the air pressure change is, and the worse the air tightness of the corresponding filling equipment is; the method comprises the steps of calling a preset air pressure difference variable coefficient threshold value through a data storage module, wherein the preset air pressure difference variable coefficient threshold value is recorded in advance by corresponding staff and stored in the data storage module for judging and analyzing an air pressure difference variable coefficient YCX, and the preset air pressure difference variable coefficient threshold value is 1.964 preferably; and comparing the air pressure difference variable coefficient YCX with a preset air pressure difference variable coefficient threshold value in a numerical mode, if the air pressure difference variable coefficient YCX is larger than or equal to the preset air pressure difference variable coefficient threshold value, generating an air tightness disqualification signal of the filling equipment, and if the air pressure difference variable coefficient YCX is smaller than the preset air pressure difference variable coefficient threshold value, generating an air tightness qualification signal of the filling equipment.
And the equipment early warning module displays text information of the air tightness disqualification signal of the corresponding filling equipment or the air tightness qualification signal of the filling equipment when receiving the air tightness disqualification signal of the filling equipment and sends corresponding prompt tones and corresponding warning lights when receiving the air tightness disqualification signal of the filling equipment, and the corresponding staff should check and maintain the filling equipment in time when receiving the air tightness disqualification signal of the filling equipment.
Embodiment two:
as shown in fig. 2, the difference between the present embodiment and embodiment 1 is that the detection and analysis platform of the internet of things further includes an operation monitoring backtracking module, the server is in communication connection with the operation monitoring backtracking module, after the current air tightness detection operation is finished, the server generates an operation backtracking analysis signal and sends the operation backtracking analysis signal to the operation monitoring backtracking module, the operation monitoring backtracking module performs the operation backtracking analysis on the current air tightness detection operation after receiving the operation backtracking analysis signal, and a specific analysis process of the operation monitoring backtracking module is as follows:
Acquiring the starting time and the ending time of the current air tightness detection operation, and calculating the difference between the ending time and the starting time to acquire an air tightness detection duration value; the preset air tightness detection time threshold value is called through the data storage module, is recorded in advance by corresponding staff and is stored in the data storage module, and is used for judging and analyzing the air tightness detection time value, and preferably, the value of the preset air tightness detection time threshold value is 25min; comparing the air tightness detection duration value with a preset air tightness detection duration threshold value in a numerical mode, and if the air tightness detection duration value is larger than or equal to the preset air tightness detection duration threshold value, indicating that the operation time of operators corresponding to the current air tightness detection operation is too long, generating an operation efficiency disqualification signal;
if the air tightness detection duration value is smaller than the preset air tightness detection duration threshold value, acquiring preset standard operation flow information of air tightness detection operation, wherein the preset standard operation flow information mainly refers to standard operation of each link of air tightness detection operation of filling equipment, the preset operation duration threshold value of each link and the like, dividing the air tightness detection operation into a plurality of operation links based on the preset standard operation flow information, and acquiring the operation duration value of an operator corresponding to the current operation in the corresponding operation link and the frequency of errors;
The method comprises the steps that a preset operation time length threshold value and an error frequency threshold value of a corresponding operation link are called through a data storage module, the preset operation time length threshold value and the error frequency threshold value are recorded in advance by corresponding staff and stored in the data storage module, the judgment and analysis of the operation time length value and the error frequency are used for carrying out, the operation time length value and the error frequency of the corresponding operation link are respectively compared with the corresponding preset operation time length threshold value and the error frequency threshold value, if the operation time length value and the error frequency of the corresponding operation link of the corresponding operation staff are smaller than the corresponding threshold value, the corresponding operation link is marked as a qualified link, and the other conditions are marked as unqualified links;
acquiring the number of qualified links and the number of unqualified links, respectively marking the number of qualified links and the number of unqualified links as HH and BH, and passing through a formula
Carrying out numerical calculation by substituting the number HH of the qualified links and the number BH of the unqualified links, and obtaining an operation backtracking coefficient HSX after the numerical calculation; wherein, ft1 and ft2 are preset proportional coefficients, the values of ft1 and ft2 are both greater than zero, and ft1 is smaller than ft2;
the larger the value of the operation backtracking coefficient HSX is, the more irregular the operation process of the secondary air tightness detection operation is; and the data storage module is used for calling a preset operation backtracking coefficient threshold value, the preset operation backtracking coefficient threshold value is recorded in advance by a corresponding worker and is stored in the data storage module for judging and analyzing the operation backtracking coefficient HSX, the operation backtracking coefficient HSX is compared with the preset operation backtracking coefficient threshold value in a numerical value mode, if the operation backtracking coefficient HSX is greater than or equal to the preset operation backtracking coefficient threshold value, an operation normalization disqualification signal is generated, and if the operation backtracking coefficient HSX is smaller than the preset operation backtracking coefficient threshold value, an operation backtracking qualification signal is generated.
And the operation monitoring backtracking module performs operation backtracking analysis on the current air tightness detection operation, generates an operation efficiency unqualified signal, an operation normalization unqualified signal or an operation backtracking qualified signal based on an operation backtracking analysis result, sends the operation efficiency unqualified signal, the operation normalization unqualified signal or the operation backtracking qualified signal to the equipment early warning module through the server, and the equipment early warning module displays signal information corresponding to the operation efficiency unqualified signal, the operation normalization unqualified signal or the operation backtracking qualified signal, and sends corresponding prompt tones and corresponding warning lights when receiving the operation efficiency unqualified signal or the operation normalization unqualified signal, so that the training of the air tightness detection operation of the filling equipment by related staff should be enhanced in the follow-up operation to ensure the efficient and smooth operation of the follow-up detection operation.
The working principle of the invention is as follows: when the automatic filling machine is used, the filling live monitoring module is used for monitoring and analyzing in real time to judge whether a filling early warning signal or a filling adjusting signal is generated or not when filling is carried out, corresponding staff should carry out inspection and maintenance of filling equipment in time when receiving the filling early warning signal, and equipment adjustment should be carried out in time according to the need when receiving the filling adjusting signal so as to ensure the stability of the working process of the equipment, and error influence on the monitoring result of the filling process is reduced; the corresponding filling equipment is subjected to urgency analysis through the urgency detection analysis module so as to judge whether an urgency early warning signal is generated, and when the urgency early warning signal is generated, corresponding staff should timely detect the air tightness of the filling equipment so as to ensure the subsequent smooth work of the filling equipment; stopping the current air tightness detection operation when the detection process of the corresponding filling equipment is unstable, continuing the detection analysis when the detection process of the corresponding filling equipment is stable, generating an air tightness disqualification signal of the filling equipment or an air tightness qualification signal of the filling equipment, and checking and maintaining the filling equipment in time when the corresponding staff receives the air tightness disqualification signal of the filling equipment; and the operation monitoring backtracking module performs operation backtracking analysis on the current air tightness detection operation and generates an operation efficiency unqualified signal, an operation normalization unqualified signal or an operation backtracking qualified signal, and air tightness detection operation training of related staff is enhanced subsequently when the operation efficiency unqualified signal or the operation normalization unqualified signal is received so as to ensure that the subsequent detection operation is performed efficiently and smoothly.
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 filling equipment air tightness detection system based on the Internet of things is characterized by comprising an Internet of things detection and analysis platform, wherein the Internet of things detection and analysis platform comprises a server, a data storage module, a filling live monitoring module, a detection urgency analysis module, an equipment air tightness detection and analysis module and an equipment early warning module; the filling live monitoring module is used for carrying out real-time monitoring analysis on corresponding filling equipment when filling is carried out, judging whether to generate a filling early warning signal or a filling adjusting signal through the real-time monitoring analysis, and sending the filling early warning signal or the filling adjusting signal to the equipment early warning module through the server when the filling early warning signal or the filling adjusting signal is generated;
The detection urgency analysis module is used for carrying out urgency analysis on the corresponding filling equipment, judging whether an urgency early warning signal is generated or not based on an urgency analysis result, and sending the urgency early warning signal to the equipment early warning module through the server when the urgency early warning signal is generated; the equipment air tightness detection analysis module is used for carrying out air tightness detection analysis on the corresponding filling equipment, stopping the current air tightness detection operation when the detection process of the corresponding filling equipment is unstable, continuing to carry out detection analysis when the detection process of the corresponding filling equipment is stable, generating an air tightness disqualification signal or an air tightness qualification signal of the filling equipment, and sending the air tightness disqualification signal or the air tightness qualification signal of the filling equipment to the equipment early warning module through the server;
the equipment early warning module displays corresponding early warning information and sends out corresponding prompt tone and corresponding warning light when receiving the filling early warning signal or the filling adjusting signal and the urgency early warning signal; displaying text information corresponding to the filling equipment air tightness disqualification signal or the filling equipment air tightness qualification signal when the filling equipment air tightness disqualification signal or the filling equipment air tightness qualification signal is received, and sending corresponding prompt sound and corresponding warning light when the filling equipment air tightness disqualification signal is received;
The specific operation process of the filling live monitoring module comprises the following steps:
acquiring a device weight reduction value of corresponding filling equipment and a material output weight value at an outlet of the corresponding filling equipment when filling is carried out, and carrying out difference calculation on the device weight reduction value and the material output weight value to acquire a filling output difference value; the method comprises the steps of calling a preset filling output difference threshold value through a data storage module, carrying out numerical comparison on a filling output difference value and the filling output difference threshold value, and if the filling output difference value is smaller than or equal to the preset filling output difference threshold value, not generating any signal; if the filling output difference value is larger than a preset filling output difference threshold value, carrying out filling error analysis;
the specific analysis process of the filling error analysis is as follows:
acquiring a material output speed value and filling equipment vibration data at an outlet of filling equipment, acquiring a preset material output proper speed value through a data storage module, performing difference calculation on a filling output difference value and a preset filling output difference threshold value to acquire filling difference threshold data, performing difference calculation on the material output speed value and the preset material output proper speed value to acquire a speed real deviation value, and adopting a formula 
Carrying out numerical calculation on filling difference threshold data YY, a speed real deviation value SP and filling equipment vibration data LZ to obtain an error influence coefficient; wherein a1, a2 and a3 are preset proportionality coefficients, and the values of a1, a2 and a3 are all larger than zero;
the method comprises the steps of calling a preset error influence coefficient threshold value through a data storage module, comparing the error influence coefficient with the preset error influence coefficient threshold value in a numerical mode, generating a filling early warning signal if the error influence coefficient is larger than or equal to the preset error influence coefficient threshold value, and generating a filling adjusting signal if the error influence coefficient is smaller than the preset error influence coefficient threshold value;
the specific operation process of the detecting urgency analysis module comprises the following steps:
obtaining dates of a plurality of times of air tightness detection of corresponding filling equipment in unit time, performing difference calculation on the dates of two adjacent times of air tightness detection to obtain detection time difference coefficients, and summing and averaging a plurality of groups of detection time difference coefficients in unit time to obtain detection time average difference coefficients; the date of the last air tightness detection is obtained, and the difference value between the current date and the date of the last air tightness detection is calculated to obtain a current detection time value;
Calculating the ratio of the current detection interval value to the detection time average difference coefficient to obtain a detection urgency coefficient; the method comprises the steps of calling a preset detection urgency coefficient threshold value through a data storage module, comparing the detection urgency coefficient with the preset urgency coefficient threshold value in a numerical mode, generating an urgency early warning signal if the detection urgency coefficient is larger than or equal to the preset urgency coefficient threshold value, and not generating the urgency early warning signal if the detection urgency coefficient is smaller than the preset urgency coefficient threshold value;
the specific operation process of the equipment air tightness detection and analysis module comprises the following steps:
generating a stability qualified signal or a stability unqualified signal through detection stability analysis, stopping current detection when the stability unqualified signal is generated, acquiring an air pressure initial condition coefficient in corresponding filling equipment after generating the stability qualified signal at an interval of t0, acquiring an air pressure variable condition coefficient in corresponding filling equipment after an interval of t1, wherein t0 and t1 are preset interval periods, and t1 is more than t0 and more than 0;
performing difference calculation on the air pressure initial condition coefficient and the air pressure variable condition coefficient to obtain an air pressure difference variable coefficient, calling a preset air pressure difference variable coefficient threshold value through a data storage module, performing numerical comparison on the air pressure difference variable coefficient and the preset air pressure difference variable coefficient threshold value, generating an air tightness disqualification signal of the filling equipment if the air pressure difference variable coefficient is larger than or equal to the preset air pressure difference variable coefficient threshold value, and generating an air tightness qualification signal of the filling equipment if the air pressure difference variable coefficient is smaller than the preset air pressure difference variable coefficient threshold value;
The specific analytical process of the assay stability analysis is as follows:
acquiring a temperature stability coefficient and a vibration stability coefficient through analysis, calling a preset temperature stability coefficient threshold value and a preset vibration stability coefficient threshold value through a data storage module, respectively comparing the temperature stability coefficient and the vibration stability coefficient with the preset temperature stability coefficient threshold value and the preset vibration stability coefficient threshold value in a numerical mode, and generating a detection stability disqualification signal if at least one of the temperature stability coefficient and the vibration stability coefficient is larger than the corresponding preset threshold value;
if the temperature stability coefficient and the vibration stability coefficient are both smaller than or equal to the corresponding preset threshold values, performing numerical calculation on the temperature stability coefficient WDX and the vibration stability coefficient ZWX through a formula wzx=g1×wdx+g2× ZWX to obtain a stability total analysis value WZX; wherein, gh1 and gh2 are preset weight coefficients, the values of the gh1 and the gh2 are both larger than zero, and the gh1 is larger than the gh2; the method comprises the steps of calling a preset stability total analysis threshold value through a data storage module, comparing the stability total analysis value with the preset stability total analysis threshold value in a numerical mode, generating a detection stability disqualification signal if the stability total analysis value is greater than or equal to the preset stability total analysis threshold value, and generating a detection stability qualification signal if the stability total analysis value is smaller than the preset stability total analysis threshold value;
The analysis and acquisition method of the temperature stability coefficient comprises the following specific steps:
acquiring real-time temperatures of a plurality of positions in corresponding filling equipment at corresponding detection time points, summing the real-time temperatures of all detection time points in the corresponding positions in the corresponding filling equipment, taking an average value to acquire a live value of the temperature, carrying out difference calculation on the live value of the temperature and a preset standard value of the temperature, and taking an absolute value to acquire a standard deviation value of the temperature; carrying out variance calculation on the real-time temperatures of all detection time points at corresponding positions in corresponding filling equipment to obtain a temperature disturbance value, and obtaining a temperature disturbance value according to a formula
Carrying out numerical calculation on the temperature mark deviation value BL and the temperature disturbance value WL to obtain a temperature evaluation value WPZ at a corresponding position; wherein b1 and b2 are preset weight coefficients, the values of b1 and b2 are both greater than zero, and b1 is smaller than b2; acquiring all the temperature evaluation values in the corresponding filling equipment, establishing a temperature evaluation set from all the temperature evaluation values, and carrying out mean value calculation on the temperature evaluation set to acquire a temperature total evaluation value;
the method comprises the steps of calling a preset temperature evaluation threshold value through a data storage module, comparing a temperature evaluation value with the preset temperature evaluation threshold value in a numerical mode, marking the corresponding position of the corresponding filling equipment as a temperature jump zone bit if the temperature evaluation value is larger than or equal to the preset temperature evaluation threshold value, and marking the corresponding position of the corresponding filling equipment as a temperature stable zone bit if the temperature evaluation value is smaller than the preset temperature evaluation threshold value; by the formula 
The total evaluation value WQ of the bit temperature, the number TB of temperature jump zone bits and the number WB of temperature stable zone bits are calculated to obtain a temperature stability coefficient; wherein b3, b4 and b5 are preset proportionality coefficients, the values of b3, b4 and b5 are all larger than zero, and b4 is larger than b3 and larger than b5;
the analysis and acquisition method of the vibration stability coefficient is specifically as follows:
obtaining vibration frequencies and vibration amplitudes at a plurality of positions on corresponding filling equipment, and carrying out numerical calculation on the vibration frequencies PL and the vibration amplitudes FD through a formula PF=k1+k2, wherein k1 and k2 are preset weight coefficients, and the values of k1 and k2 are larger than zero; establishing a vibration frequency amplitude set from the vibration frequency amplitude data at a plurality of positions, and carrying out mean value calculation on the vibration frequency amplitude set to obtain a vibration frequency amplitude mean condition value; the method comprises the steps that a preset vibration frequency amplitude judging value is called through a data storage module, vibration frequency amplitude data at a corresponding position is compared with the preset vibration frequency amplitude judging value in a numerical mode, if the vibration frequency amplitude data are larger than or equal to the preset vibration frequency amplitude judging value, the corresponding position is marked as a high vibration position, and if the vibration frequency amplitude data are smaller than the preset vibration frequency amplitude judging value, the corresponding position is marked as a low vibration position; by the formula 
Carrying out numerical calculation on the vibration frequency amplitude average condition value ZJ, the high vibration site number GZ and the low vibration site number DZ to obtain a vibration stability coefficient ZWX; wherein k3, k4 and k5 are preset proportionality coefficients, the values of k3, k4 and k5 are all larger than zero, and k4 is larger than k3 and larger than k5.
2. The filling equipment air tightness detection system based on the internet of things according to claim 1, wherein the internet of things detection analysis platform further comprises an operation monitoring backtracking module, the server is in communication connection with the operation monitoring backtracking module, after the current air tightness detection operation is finished, the server generates an operation retrospective analysis signal and sends the operation retrospective analysis signal to the operation monitoring backtracking module, the operation monitoring backtracking module is used for carrying out operation retrospective analysis on the current air tightness detection operation after receiving the operation retrospective analysis signal, and generates an operation efficiency disqualification signal, an operation normalization disqualification signal or an operation backtracking qualification signal based on the operation retrospective analysis result, and sends the operation efficiency disqualification signal, the operation normalization disqualification signal or the operation backtracking qualification signal to the equipment early warning module through the server; the specific operation process of the operation monitoring backtracking module is as follows:
Acquiring the starting time and the ending time of the current air tightness detection operation, and calculating the difference between the ending time and the starting time to acquire an air tightness detection duration value; the method comprises the steps of calling a preset air tightness detection time threshold value through a data storage module, carrying out numerical comparison on the air tightness detection time value and the preset air tightness detection time threshold value, and generating an operation efficiency disqualification signal if the air tightness detection time value is greater than or equal to the preset air tightness detection time threshold value; if the air tightness detection duration value is smaller than the preset air tightness detection duration threshold value, acquiring preset standard operation flow information of air tightness detection operation, dividing the air tightness detection operation into a plurality of operation links based on the preset standard operation flow information, and acquiring the operation duration value of an operator corresponding to the current operation in the corresponding operation link and the frequency of errors;
the method comprises the steps that a preset operation duration threshold value and an error frequency threshold value of a corresponding operation link are called through a data storage module, the operation duration value and the error frequency of a corresponding operator in the corresponding operation link are respectively compared with the corresponding preset operation duration threshold value and the error frequency threshold value in a numerical mode, if the operation duration value and the error frequency of the corresponding operator in the corresponding operation link are smaller than the corresponding threshold value, the corresponding operation link is marked as a qualified link, and the other conditions are marked as unqualified links; by the formula 
Performing numerical calculation on the number of qualified links HH and the number of unqualified links BH to obtain an operation backtracking coefficient HSX; wherein, ft1 and ft2 are preset proportional coefficients, the values of ft1 and ft2 are both greater than zero, and ft1 is smaller than ft2; retrieving a preset operation loop through a data storage moduleAnd comparing the operation tracing coefficient with a preset operation tracing coefficient threshold value in a numerical value mode, if the operation tracing coefficient is larger than or equal to the preset operation tracing coefficient threshold value, generating an operation normalization disqualification signal, otherwise, generating an operation tracing qualification signal. />
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Denomination of invention: A Gas Tightness Detection System for Filling Equipment Based on the Internet of Things Effective date of registration: 20230807 Granted publication date: 20230623 Pledgee: Shandong Shanxian Rural Commercial Bank Co.,Ltd. Pledgor: Shandong Weifu Pharmaceutical Co.,Ltd. Registration number: Y2023980051227 |