CN117590822A - MEMS gas pressure sensor dispensing processing supervision system based on Internet of things - Google Patents
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Abstract
The invention relates to the technical field of sensor processing supervision, in particular to an MEMS gas pressure sensor dispensing processing supervision system based on the Internet of things, which comprises a supervision platform, a data acquisition unit, a gas supervision unit, a processing blocking unit, an interference risk unit, a dispensing evaluation unit and a processing management unit; according to the invention, the influence of interference factors on the dispensing processing of the MEMS gas pressure sensor is reduced by analyzing from two angles of the dispensing supply end and the dispensing front end, so that the dispensing processing quality and processing efficiency are improved, and the equipment is reasonably and pertinently managed in an information feedback mode, namely, the two points of gas compression and pipelines in the dispensing supply end are analyzed, and simultaneously, the analysis is performed by combining with environmental factors, so that the accuracy of an analysis result is improved, and the processing quality risk assessment operation is performed by combining with the operation data of the dispensing front end, and the analysis precision and the management rationality are further improved by combining with the analysis of the influence condition of the dispensing processing whole.
Description
Technical Field
The invention relates to the technical field of sensor processing supervision, in particular to an MEMS gas pressure sensor dispensing processing supervision system based on the Internet of things.
Background
The MEMS pressure sensor is an automatic machine which combines mechanical and electrical technologies, needs to carry out dispensing operation during production, needs to use a dispensing machine, is also called a glue spreader, a glue dropping machine, a glue beating machine, a glue filling machine and the like during dispensing operation, is used for specially controlling fluid and dropping and coating the fluid on the surface of a product or in the product, is mainly used for accurately dispensing glue, paint and other liquid in the product process, injecting, coating and dropping the fluid to the accurate position of each product, and can be used for realizing dotting, line drawing, circular or arc;
however, in the use process of the existing equipment, the problem of improper supervision exists, so that the operation safety and the dispensing processing quality of the equipment are reduced, compressed gas, pipelines and environments cannot be supervised, interference factors influence the operation of the equipment, and the processing quality of the equipment is reduced;
in view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an MEMS gas pressure sensor dispensing processing supervision system based on the Internet of things, so as to solve the technical defects, and the invention analyzes from two angles of a dispensing supply end and a dispensing front end to reduce the influence of interference factors on the dispensing processing of the MEMS gas pressure sensor, so as to improve the dispensing processing quality and processing efficiency of the MEMS gas pressure sensor, reasonably and pointedly manage equipment in an information feedback mode, namely analyze from two points of gas compression and pipelines in the dispensing supply end, and simultaneously analyze by combining with environmental factors, thereby being beneficial to improving the data support for the whole dispensing processing quality of the subsequent analysis, and improving the accuracy of analysis results.
The aim of the invention can be achieved by the following technical scheme: the MEMS gas pressure sensor dispensing processing supervision system based on the Internet of things comprises a supervision platform, a data acquisition unit, a gas supervision unit, a processing blocking unit, an interference risk unit, a dispensing evaluation unit and a processing management unit;
when the supervision platform generates a pipe transporting instruction, the pipe transporting instruction is sent to the data acquisition unit and the gas supervision unit, the data acquisition unit immediately acquires dispensing data and interference data of the dispensing equipment when receiving the pipe transporting instruction, the dispensing data comprise compressed gas values and pipeline risk values, the interference data comprise temperature-humidity deviation values and ventilation risk values, the dispensing data and the interference data are respectively sent to the processing blocking unit and the interference risk unit, the gas supervision unit immediately acquires gas data of the compressed gas when receiving the pipe transporting instruction, the gas data represent gas influence values, performs gas quality feedback evaluation analysis on the gas data, sends an obtained normal signal to the processing blocking unit, and sends an obtained abnormal signal to the processing management unit through the processing blocking unit;
the processing blocking unit immediately carries out safe processing supervision and evaluation analysis on the dispensing data after receiving the dispensing data and the normal signal, and sends the obtained risk signal to the processing management unit;
the interference risk unit immediately carries out dispensing interference risk assessment analysis on the interference data after receiving the interference data, sends the obtained sector occupation ratio to a dispensing assessment unit, and sends the obtained interference signal to a processing management unit through the dispensing assessment unit;
and after receiving the fan-shaped occupation ratio, the dispensing evaluation unit immediately acquires operation data of the equipment, wherein the operation data comprises a glue outlet risk value and an efficiency risk value, performs processing quality risk evaluation operation and formulation comparison operation on the operation data, and sends the obtained low-level control signals and high-level control signals to the processing management unit.
Preferably, the gas quality feedback evaluation analysis process of the gas supervision unit is as follows:
acquiring the time length from the starting operation time to the ending operation time of the equipment, marking the time length as a time threshold, dividing the time threshold into i sub-time periods, wherein i is a natural number larger than zero, acquiring gas influence values of the equipment in each sub-time period, wherein the gas influence values represent the number of the gas influence parameters exceeding a preset threshold, normalizing the gas influence parameters with the part of the gas influence parameters exceeding the preset threshold through data, wherein the gas influence parameters comprise a unit volume gas dust particle content value and a gas humidity average value, establishing a rectangular coordinate system by taking the number of the sub-time periods as an X axis and taking the gas influence value as a Y axis, drawing a gas influence value curve in a description way, further acquiring the area surrounded by the gas influence value curve and the X axis, marking the gas influence value curve as a gas evaluation value, comparing the gas evaluation value with a stored preset gas evaluation value threshold, and marking the part of the gas influence value larger than the preset gas evaluation value threshold as a gas purity risk value if the gas evaluation value is larger than the preset gas evaluation value threshold;
comparing the gas purity risk value with a preset gas purity risk value threshold value recorded and stored in the gas purity risk value, and analyzing the gas purity risk value:
if the gas purity risk value is smaller than a preset gas purity risk value threshold, generating a normal signal;
if the gas purity risk value is greater than or equal to a preset gas purity risk value threshold, generating an abnormal signal.
Preferably, the safety processing supervision, evaluation and analysis process of the processing blocking unit is as follows:
s1: obtaining a compressed gas value of equipment in each sub-time period, wherein the compressed gas value represents a part of the gas compression quantity in unit time, which deviates from a preset range, and then the sum value is obtained by carrying out data normalization processing on the part of the compressed gas value in the preset range and the part of the compressed gas pressure value, and comparing the compressed gas value with a stored preset compressed gas value threshold value for analysis, and if the compressed gas value is larger than the preset compressed gas value threshold value, marking the ratio of the number of sub-time periods corresponding to the compressed gas value larger than the preset compressed gas value threshold value to the total number of sub-time periods as a compression risk value;
s2: dividing a rubber conveying pipe into g sub-length sections, wherein g is a natural number larger than zero, acquiring a pipeline risk value of each sub-length section in a time threshold, wherein the pipeline risk value represents a product value obtained by carrying out data normalization processing on the total area of a pipeline bulge and a bending angle, comparing the pipeline risk value with a preset pipeline risk value threshold, and if the pipeline risk value is larger than the preset pipeline risk value threshold, marking the number of sub-pipelines corresponding to the pipeline risk value larger than the preset pipeline risk value threshold as a pipeline obstruction value;
s3: comparing the compression risk value and the pipeline obstruction value with a preset compression risk value threshold value and a preset pipeline obstruction value threshold value which are recorded and stored in the compression risk value and the pipeline obstruction value, and analyzing the compression risk value and the pipeline obstruction value:
if the compression risk value is smaller than a preset compression risk value threshold and the pipeline obstruction value is smaller than a preset pipeline obstruction value threshold, no signal is generated;
and if the compression risk value is greater than or equal to a preset compression risk value threshold or the pipeline obstruction value is greater than or equal to a preset pipeline obstruction value threshold, generating a risk signal.
Preferably, the dispensing interference risk assessment analysis process of the interference risk unit is as follows:
t1: taking equipment as a circle center, R1 as a radius, drawing a circle around the equipment to form an area, marking the area as a monitoring area, acquiring a temperature-humidity deviation value and a ventilation risk value of the monitoring area in each sub-time period, wherein the temperature-humidity deviation value represents a sum value obtained by carrying out data normalization processing on a part of the environment temperature value deviating from a preset range and a part of the environment humidity value deviating from the preset range, the ventilation risk value represents a part of the ventilation flow in unit time exceeding the ventilation flow in the preset unit time, and then carrying out data normalization processing on the sum value and the air humidity average value of the monitoring area to obtain product values, wherein the temperature-humidity deviation value and the ventilation risk value are respectively marked as WSi and TFi;
t2: according to the formulaObtaining dispensing interference evaluation coefficients of each sub-time period, wherein a1 and a2 are preset scale factor coefficients of a temperature-humidity deviation value and a ventilation risk value respectively, and a1 and a2 are positive factors larger than zeroThe number a3 is a preset correction factor coefficient, the value is 1.281, hi is a dispensing interference evaluation coefficient of each sub-time period, the dispensing interference evaluation coefficient Hi is compared with a stored preset dispensing interference evaluation coefficient threshold value, if the dispensing interference evaluation coefficient Hi is larger than the preset dispensing interference evaluation coefficient threshold value, the ratio of the number of sub-time periods corresponding to the dispensing interference evaluation coefficient threshold value to the total number of sub-time periods is marked as a sector occupation ratio, and the sector occupation ratio is compared with a preset sector occupation ratio threshold value recorded in the dispensing interference evaluation coefficient Hi and stored in the dispensing interference evaluation coefficient Hi:
if the ratio between the sector occupancy rate and the preset sector occupancy rate threshold is smaller than 1, no signal is generated;
and if the ratio of the sector occupation ratio to the preset sector occupation ratio threshold is more than or equal to 1, generating an interference signal.
Preferably, the processing quality risk assessment operation process of the dispensing assessment unit is as follows:
acquiring a sector occupation ratio in a time threshold, acquiring a compression risk value and a pipeline obstruction value in the time threshold, and respectively marking the sector occupation ratio, the compression risk value and the pipeline obstruction value as SZ, YF and LZ;
according to the formulaAnd obtaining a processing influence risk coefficient, wherein f1, f2 and f3 are preset weight factor coefficients of a sector occupation ratio, a compression risk value and a pipeline obstruction value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset fault tolerance factor coefficient, the value is 2.119, and P is the processing influence risk coefficient.
Preferably, the formulation comparison operation process of the dispensing evaluation unit is as follows:
SS1: obtaining a glue outlet risk value of equipment in a time threshold, wherein the glue outlet risk value represents a sum value obtained by carrying out data normalization processing on a part of a glue flow velocity mean value deviating from a preset range and a part of a glue temperature mean value deviating from the preset range;
SS2: obtaining an efficiency risk value of equipment in a time threshold, wherein the efficiency risk value represents a part of a change trend value of an unsuitable dispensing number characteristic curve exceeding a preset threshold, comparing the efficiency risk value with a stored preset efficiency risk value threshold for analysis, marking a part of the efficiency risk value larger than the preset efficiency risk value threshold as a damaged risk value, and marking a dispensing risk value and a damaged risk value as CF and SS respectively;
SS3: according to the formulaObtaining a quality risk assessment coefficient, wherein v1, v2 and v3 are respectively preset proportional coefficients of a glue outlet risk value, a damage risk value and a processing influence risk coefficient, v1, v2 and v3 are positive numbers larger than zero, v4 is a preset compensation factor coefficient, the value is 1.129, Z is a processing influence risk coefficient, and the processing influence risk coefficient Z is compared with a preset processing influence risk coefficient threshold value recorded and stored in the processing influence risk coefficient Z:
if the ratio between the processing influence risk coefficient Z and the preset processing influence risk coefficient threshold is smaller than or equal to 1, no signal is generated;
if the ratio between the processing influence risk coefficient Z and the preset processing influence risk coefficient threshold is greater than 1, generating a feedback instruction, acquiring a part of which the processing influence risk coefficient Z is greater than the preset processing influence risk coefficient threshold when generating the feedback instruction, marking the part as a quality optimization value, and comparing the quality optimization value with a preset quality optimization value threshold recorded and stored in the quality optimization value:
if the quality optimization value is smaller than a preset quality optimization value threshold value, generating a low-level control signal;
and if the quality optimized value is greater than or equal to a preset quality optimized value threshold value, generating an advanced control signal.
The beneficial effects of the invention are as follows:
(1) According to the invention, the two angles of the dispensing supply end and the dispensing front end are analyzed, so that the influence of interference factors on the dispensing processing of the MEMS gas pressure sensor is reduced, the dispensing processing quality and the processing efficiency of the MEMS gas pressure sensor are improved, and the equipment is reasonably and pertinently managed in an information feedback mode, namely, the two points of gas compression and a pipeline in the dispensing supply end are analyzed, and meanwhile, the environmental factors are combined for analysis, so that the data support is improved for the whole dispensing processing quality of the subsequent analysis, and the accuracy of an analysis result is improved;
(2) According to the invention, the processing quality risk assessment operation is carried out on the operation data of the dispensing front end, so that whether the dispensing processing quality risk of the MEMS gas pressure sensor is too high or not is facilitated, the analysis is carried out according to the integral influence condition of dispensing processing, the analysis precision is further improved, and the equipment is reasonably and pertinently managed in an information feedback mode, so that the integral dispensing processing quality is improved.
Drawings
The invention is further described below with reference to the accompanying drawings;
FIG. 1 is a flow chart of the system of the present invention;
fig. 2 is a partial analysis reference 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:
referring to fig. 1 to 2, the invention discloses an MEMS gas pressure sensor dispensing processing supervision system based on the internet of things, which comprises a supervision platform, a data acquisition unit, a gas supervision unit, a processing blocking unit, an interference risk unit, a dispensing evaluation unit and a processing management unit, wherein the supervision platform is in unidirectional communication connection with the data acquisition unit and the gas supervision unit, the data acquisition unit and the gas supervision unit are in unidirectional communication connection with the processing blocking unit, the data acquisition unit is in unidirectional communication connection with the interference risk unit, the processing blocking unit and the interference risk unit are in unidirectional communication connection with the dispensing evaluation unit, and the processing blocking unit and the dispensing evaluation unit are in unidirectional communication connection with the processing management unit;
when the supervision platform generates a pipe transporting instruction, and sends the pipe transporting instruction to the data acquisition unit and the gas supervision unit, the data acquisition unit immediately acquires dispensing data and interference data of dispensing equipment when receiving the pipe transporting instruction, the dispensing data comprise compressed gas values and pipeline risk values, the interference data comprise temperature-humidity deviation values and ventilation risk values, the dispensing data and the interference data are respectively sent to the processing blocking unit and the interference risk unit, the gas supervision unit immediately acquires gas data of compressed gas when receiving the pipe transporting instruction, the gas data represent gas influence values, and carries out gas quality feedback evaluation analysis on the gas data so as to judge whether the gas quality is normal or not, and further, the guarantee is provided for subsequent gas compression so as to improve the gas compression effect, and the specific gas quality feedback evaluation analysis process is as follows:
acquiring the duration from the starting operation time to the ending operation time of the equipment, marking the duration as a time threshold, dividing the time threshold into i sub-time periods, namely, a natural number larger than zero, acquiring the gas influence value of the equipment in each sub-time period, wherein the gas influence value represents the number of the gas influence parameter exceeding a preset threshold, and marking the part of the gas influence value exceeding the preset threshold as a gas pure risk value after data normalization processing with the part of the gas influence parameter exceeding the preset threshold, wherein the gas influence parameter comprises a gas dust particle content value and a gas humidity average value in unit volume, the number of the sub-time periods is taken as an X axis, a rectangular coordinate system is established with the gas influence value as a Y axis, a gas influence value curve is drawn in a description way, the area surrounded by the gas influence value curve and the X axis is acquired, the gas influence value is marked as a gas evaluation value, the gas evaluation value is compared with the stored preset gas evaluation value threshold, and if the gas evaluation value is larger than the preset gas evaluation value threshold, the part of the gas evaluation value is marked as a gas pure risk value, and the potential risk is higher when the gas pure risk value is larger than the preset gas risk value, and the potential risk is higher is compressed under the condition that the gas pure risk value is higher;
comparing the gas purity risk value with a preset gas purity risk value threshold value recorded and stored in the gas purity risk value, and analyzing the gas purity risk value:
if the gas purity risk value is smaller than a preset gas purity risk value threshold, generating a normal signal and sending the normal signal to a processing blocking unit;
if the gas purity risk value is greater than or equal to a preset gas purity risk value threshold, generating an abnormal signal, sending the abnormal signal to a processing management unit through a processing blocking unit, and immediately displaying preset early warning characters corresponding to the abnormal signal after the processing management unit receives the abnormal signal, so that feedback management is preset in time, the gas quality is improved, and the improvement and guarantee of subsequent gas compression are facilitated, so that the gas compression effect is improved;
after receiving the dispensing data and the normal signal, the processing blocking unit immediately carries out safety processing supervision, evaluation and analysis on the dispensing data so as to judge whether the dispensing risk of equipment is too high, so that the dispensing supply end is managed in time, the influence of compressed gas and a pipeline on dispensing processing is reduced, and the specific safety processing supervision, evaluation and analysis process is as follows:
obtaining a compressed gas value of equipment in each sub-time period, wherein the compressed gas value represents a part of the gas compression quantity in unit time, which deviates from a preset range, and then the sum value is obtained by carrying out data normalization processing on the part of the compressed gas value in the preset range and the part of the compressed gas pressure value, and comparing the compressed gas value with a stored preset compressed gas value threshold value for analysis, if the compressed gas value is larger than the preset compressed gas value threshold value, marking the ratio of the number of sub-time periods corresponding to the compressed gas value larger than the preset compressed gas value threshold value to the total number of sub-time periods as a compressed risk value, wherein the larger the value of the compressed risk value is, the larger the abnormal risk of dispensing processing is;
dividing a rubber conveying pipe into g sub-length sections, wherein g is a natural number larger than zero, obtaining a pipeline risk value of each sub-length section in a time threshold, wherein the pipeline risk value represents a product value obtained by carrying out data normalization processing on the total area of a pipeline bulge and a bending angle, comparing the pipeline risk value with a preset pipeline risk value threshold, and analyzing if the pipeline risk value is larger than the preset pipeline risk value threshold, marking the number of sub-pipelines corresponding to the pipeline risk value larger than the preset pipeline risk value threshold as a pipeline obstruction value, wherein the larger the pipeline obstruction value is, the larger the abnormal risk of glue dispensing processing is;
comparing the compression risk value and the pipeline obstruction value with a preset compression risk value threshold value and a preset pipeline obstruction value threshold value which are recorded and stored in the compression risk value and the pipeline obstruction value, and analyzing the compression risk value and the pipeline obstruction value:
if the compression risk value is smaller than a preset compression risk value threshold and the pipeline obstruction value is smaller than a preset pipeline obstruction value threshold, no signal is generated;
if the compression risk value is greater than or equal to a preset compression risk value threshold, or the pipeline obstruction value is greater than or equal to a preset pipeline obstruction value threshold, a risk signal is generated and sent to a processing management unit, and after the risk signal is received, the processing management unit immediately displays preset early warning characters corresponding to the risk signal, so that gas compression and pipelines are managed timely, the influence of the gas compression and the pipelines on dispensing processing is reduced, and further the whole MEMS gas pressure sensor dispensing processing quality and the processing efficiency are improved.
Embodiment two:
after receiving the interference data, the interference risk unit immediately performs dispensing interference risk assessment analysis on the interference data so as to know the influence condition of interference factors on dispensing processing of the MEMS gas pressure sensor, so that data support is improved for subsequent analysis of the whole dispensing processing quality, and the specific dispensing interference risk assessment analysis process is as follows:
taking equipment as a center of a circle, drawing a circle around the equipment to form an area, marking the area as a monitoring area, acquiring a temperature-humidity deviation value and a ventilation risk value of the monitoring area in each sub-time period, wherein the temperature-humidity deviation value represents a sum value obtained by carrying out data normalization processing on a part of the environment temperature value deviating from a preset range and a part of the environment humidity value deviating from the preset range, the ventilation risk value represents a part of the ventilation flow in unit time exceeding the preset unit time, and a product value obtained by carrying out data normalization processing on the ventilation flow in unit time and an air humidity average of the monitoring area, and the temperature-humidity deviation value and the ventilation risk value are two influence parameters reflecting the environment on the dispensing processing of the equipment and are respectively marked as WSi and TFi;
according to the formulaObtaining a dispensing interference evaluation coefficient of each sub-time period, wherein a1 and a2 are preset scale factor coefficients of a temperature-humidity deviation value and a ventilation risk value respectively, the scale factor coefficients are used for correcting deviation of each parameter in a formula calculation process, so that calculation results are more accurate, a1 and a2 are positive numbers larger than zero, a3 is a preset correction factor coefficient, a value is 1.281, hi is a dispensing interference evaluation coefficient of each sub-time period, the dispensing interference evaluation coefficient Hi is compared with a stored preset dispensing interference evaluation coefficient threshold value, if the dispensing interference evaluation coefficient Hi is larger than the preset dispensing interference evaluation coefficient threshold value, the ratio of the number of the dispensing interference evaluation coefficient Hi to the total number of the sub-time periods corresponding to the preset dispensing interference evaluation coefficient threshold value is marked as a fan-shaped ratio, the fan-shaped ratio is sent to a dispensing evaluation unit, and the fan-shaped ratio is compared with the preset fan-shaped ratio threshold value recorded in the dispensing evaluation unit:
if the ratio between the sector occupancy rate and the preset sector occupancy rate threshold is smaller than 1, no signal is generated;
if the ratio between the fan-shaped occupation ratio and the preset fan-shaped occupation ratio threshold is greater than or equal to 1, generating an interference signal, sending the interference signal to a processing management unit through a dispensing evaluation unit, and immediately displaying preset early warning characters corresponding to the interference signal after the processing management unit receives the interference signal, so that the environment where equipment is located is managed in time, the influence of environmental factors on dispensing processing of the MEMS gas pressure sensor is reduced, and meanwhile, data support is provided for the follow-up analysis of the whole dispensing processing quality;
the dispensing evaluation unit immediately acquires operation data of the equipment after receiving the fan-shaped occupation ratio, wherein the operation data comprises a dispensing risk value and an efficiency risk value, and carries out processing quality risk evaluation operation on the operation data so as to facilitate whether the dispensing processing quality risk of the MEMS gas pressure sensor is too high or not, and reasonable and targeted management is carried out in an information feedback mode so as to ensure the dispensing processing quality and the processing efficiency of the MEMS gas pressure sensor, and the specific processing quality risk evaluation operation process is as follows:
acquiring a sector occupation ratio in a time threshold, acquiring a compression risk value and a pipeline obstruction value in the time threshold, and respectively marking the sector occupation ratio, the compression risk value and the pipeline obstruction value as SZ, YF and LZ;
according to the formulaObtaining a processing influence risk coefficient, wherein f1, f2 and f3 are preset weight factor coefficients of a sector occupation ratio, a compression risk value and a pipeline obstruction value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset fault tolerance factor coefficient, the value is 2.119, P is the processing influence risk coefficient, the coefficient size is a specific numerical value obtained by quantizing each parameter, the subsequent comparison is convenient, and the corresponding coefficient is preliminarily set according to the number of sample data and each group of sample data by a person skilled in the art as long as the proportional relation between the parameter and the quantized numerical value is not influenced;
obtaining a glue outlet risk value of equipment in a time threshold, wherein the glue outlet risk value represents a part of a glue flow velocity mean value deviating from a preset range, and a sum value obtained by carrying out data normalization processing on the part of the glue flow velocity mean value deviating from the preset range and the part of the glue temperature mean value deviating from the preset range, and the larger the glue outlet risk value is, the larger the glue outlet processing quality abnormal risk is;
obtaining an efficiency risk value of equipment in a time threshold, wherein the efficiency risk value represents a part of a change trend value of an unsuitable dispensing number characteristic curve exceeding a preset threshold, comparing the efficiency risk value with a stored preset efficiency risk value threshold, marking a part of the efficiency risk value larger than the preset efficiency risk value threshold as a damaged risk value, and indicating that the larger the value of the damaged risk value is, the larger the abnormal risk of dispensing processing quality is, and marking a glue outlet risk value and a damaged risk value as CF and SS respectively;
according to the formulaObtaining a quality risk assessment coefficient, wherein v1, v2 and v3 are respectively preset proportional coefficients of a glue outlet risk value, a damage risk value and a processing influence risk coefficient, v1, v2 and v3 are positive numbers larger than zero, v4 is a preset compensation factor coefficient, the value is 1.129, Z is a processing influence risk coefficient, and the processing influence risk coefficient Z is compared with a preset processing influence risk coefficient threshold value recorded and stored in the processing influence risk coefficient Z:
if the ratio between the processing influence risk coefficient Z and the preset processing influence risk coefficient threshold is smaller than or equal to 1, no signal is generated;
if the ratio between the processing influence risk coefficient Z and the preset processing influence risk coefficient threshold is greater than 1, generating a feedback instruction, acquiring a part of which the processing influence risk coefficient Z is greater than the preset processing influence risk coefficient threshold when generating the feedback instruction, marking the part as a quality optimization value, and comparing the quality optimization value with a preset quality optimization value threshold recorded and stored in the quality optimization value:
if the quality optimization value is smaller than a preset quality optimization value threshold value, generating a low-level control signal;
if the quality optimization value is greater than or equal to a preset quality optimization value threshold, generating a high-level control signal, and sending the low-level control signal and the high-level control signal to a processing management unit, wherein the processing management unit immediately displays preset early warning characters corresponding to the low-level control signal and the high-level control signal after receiving the low-level control signal and the high-level control signal, and reasonably and pointedly manages the processing quality and the processing efficiency of dispensing of the MEMS gas pressure sensor in an information feedback mode;
in summary, the invention analyzes from two angles of the dispensing supply end and the dispensing front end to reduce the influence of interference factors on the dispensing processing of the MEMS gas pressure sensor, so as to improve the dispensing processing quality and processing efficiency of the MEMS gas pressure sensor, reasonably and pertinently manages the equipment in an information feedback manner, namely analyzes from two points of gas compression and pipelines in the dispensing supply end, simultaneously analyzes in combination with environmental factors, further contributes to providing data support for the subsequent analysis of the whole dispensing processing quality, so as to improve the accuracy of analysis results, and performs processing quality risk assessment operation on the operation data of the dispensing front end, so that the MEMS gas pressure sensor is used for analyzing whether the dispensing processing quality risk is too high or not and analyzing in combination with the influence of the whole dispensing processing, further improves the analysis precision, and reasonably and pertinently manages the equipment in an information feedback manner so as to improve the whole dispensing processing quality.
The size of the threshold is set for ease of comparison, and regarding the size of the threshold, the number of cardinalities is set for each set of sample data depending on how many sample data are and the person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected.
The above formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and coefficients in the formulas are set by a person skilled in the art according to practical situations, and the above is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art is within the technical scope of the present invention, and the technical scheme and the inventive concept according to the present invention are equivalent to or changed and are all covered in the protection scope of the present invention.
Claims (4)
1. The MEMS gas pressure sensor dispensing processing supervision system based on the Internet of things is characterized by comprising a supervision platform, a data acquisition unit, a gas supervision unit, a processing blocking unit, an interference risk unit, a dispensing evaluation unit and a processing management unit;
when the supervision platform generates a pipe transporting instruction, the pipe transporting instruction is sent to the data acquisition unit and the gas supervision unit, the data acquisition unit immediately acquires dispensing data and interference data of the dispensing equipment when receiving the pipe transporting instruction, the dispensing data comprise compressed gas values and pipeline risk values, the interference data comprise temperature-humidity deviation values and ventilation risk values, the dispensing data and the interference data are respectively sent to the processing blocking unit and the interference risk unit, the gas supervision unit immediately acquires gas data of the compressed gas when receiving the pipe transporting instruction, the gas data represent gas influence values, performs gas quality feedback evaluation analysis on the gas data, sends an obtained normal signal to the processing blocking unit, and sends an obtained abnormal signal to the processing management unit through the processing blocking unit;
the processing blocking unit immediately carries out safe processing supervision and evaluation analysis on the dispensing data after receiving the dispensing data and the normal signal, and sends the obtained risk signal to the processing management unit;
the interference risk unit immediately carries out dispensing interference risk assessment analysis on the interference data after receiving the interference data, sends the obtained sector occupation ratio to a dispensing assessment unit, and sends the obtained interference signal to a processing management unit through the dispensing assessment unit;
the glue dispensing evaluation unit immediately acquires operation data of the equipment after receiving the fan-shaped occupation ratio, wherein the operation data comprises a glue outlet risk value and an efficiency risk value, performs processing quality risk evaluation operation and formulation comparison operation on the operation data, and sends an obtained low-level control signal and an obtained high-level control signal to the processing management unit;
the processing quality risk assessment operation process of the dispensing assessment unit is as follows:
acquiring a sector occupation ratio in a time threshold, acquiring a compression risk value and a pipeline obstruction value in the time threshold, and respectively marking the sector occupation ratio, the compression risk value and the pipeline obstruction value as SZ, YF and LZ;
according to the formulaObtaining a processing influence risk coefficient, wherein f1, f2 and f3 are preset weight factor coefficients of a sector occupation ratio, a compression risk value and a pipeline obstruction value respectively, f1, f2 and f3 are positive numbers larger than zero, f4 is a preset fault tolerance factor coefficient, the value is 2.119, and P is the processing influenceRisk factors;
the formulation comparison operation process of the dispensing evaluation unit is as follows:
SS1: obtaining a glue outlet risk value of equipment in a time threshold, wherein the glue outlet risk value represents a sum value obtained by carrying out data normalization processing on a part of a glue flow velocity mean value deviating from a preset range and a part of a glue temperature mean value deviating from the preset range;
SS2: obtaining an efficiency risk value of equipment in a time threshold, wherein the efficiency risk value represents a part of a change trend value of an unsuitable dispensing number characteristic curve exceeding a preset threshold, comparing the efficiency risk value with a stored preset efficiency risk value threshold for analysis, marking a part of the efficiency risk value larger than the preset efficiency risk value threshold as a damaged risk value, and marking a dispensing risk value and a damaged risk value as CF and SS respectively;
SS3: according to the formulaObtaining a quality risk assessment coefficient, wherein v1, v2 and v3 are respectively preset proportional coefficients of a glue outlet risk value, a damage risk value and a processing influence risk coefficient, v1, v2 and v3 are positive numbers larger than zero, v4 is a preset compensation factor coefficient, the value is 1.129, Z is a processing influence risk coefficient, and the processing influence risk coefficient Z is compared with a preset processing influence risk coefficient threshold value recorded and stored in the processing influence risk coefficient Z:
if the ratio between the processing influence risk coefficient Z and the preset processing influence risk coefficient threshold is smaller than or equal to 1, no signal is generated;
if the ratio between the processing influence risk coefficient Z and the preset processing influence risk coefficient threshold is greater than 1, generating a feedback instruction, acquiring a part of which the processing influence risk coefficient Z is greater than the preset processing influence risk coefficient threshold when generating the feedback instruction, marking the part as a quality optimization value, and comparing the quality optimization value with a preset quality optimization value threshold recorded and stored in the quality optimization value:
if the quality optimization value is smaller than a preset quality optimization value threshold value, generating a low-level control signal;
and if the quality optimized value is greater than or equal to a preset quality optimized value threshold value, generating an advanced control signal.
2. The MEMS gas pressure sensor dispensing process monitoring system based on the internet of things of claim 1, wherein the gas quality feedback evaluation analysis process of the gas monitoring unit is as follows:
acquiring the time length from the starting operation time to the ending operation time of the equipment, marking the time length as a time threshold, dividing the time threshold into i sub-time periods, wherein i is a natural number larger than zero, acquiring gas influence values of the equipment in each sub-time period, wherein the gas influence values represent the number of the gas influence parameters exceeding a preset threshold, normalizing the gas influence parameters with the part of the gas influence parameters exceeding the preset threshold through data, wherein the gas influence parameters comprise a unit volume gas dust particle content value and a gas humidity average value, establishing a rectangular coordinate system by taking the number of the sub-time periods as an X axis and taking the gas influence value as a Y axis, drawing a gas influence value curve in a description way, further acquiring the area surrounded by the gas influence value curve and the X axis, marking the gas influence value curve as a gas evaluation value, comparing the gas evaluation value with a stored preset gas evaluation value threshold, and marking the part of the gas influence value larger than the preset gas evaluation value threshold as a gas purity risk value if the gas evaluation value is larger than the preset gas evaluation value threshold;
comparing the gas purity risk value with a preset gas purity risk value threshold value recorded and stored in the gas purity risk value, and analyzing the gas purity risk value:
if the gas purity risk value is smaller than a preset gas purity risk value threshold, generating a normal signal;
if the gas purity risk value is greater than or equal to a preset gas purity risk value threshold, generating an abnormal signal.
3. The MEMS gas pressure sensor dispensing process monitoring system based on the internet of things of claim 1, wherein the process of safety process monitoring, evaluating and analyzing of the process blocking unit is as follows:
s1: obtaining a compressed gas value of equipment in each sub-time period, wherein the compressed gas value represents a part of the gas compression quantity in unit time, which deviates from a preset range, and then the sum value is obtained by carrying out data normalization processing on the part of the compressed gas value in the preset range and the part of the compressed gas pressure value, and comparing the compressed gas value with a stored preset compressed gas value threshold value for analysis, and if the compressed gas value is larger than the preset compressed gas value threshold value, marking the ratio of the number of sub-time periods corresponding to the compressed gas value larger than the preset compressed gas value threshold value to the total number of sub-time periods as a compression risk value;
s2: dividing a rubber conveying pipe into g sub-length sections, wherein g is a natural number larger than zero, acquiring a pipeline risk value of each sub-length section in a time threshold, wherein the pipeline risk value represents a product value obtained by carrying out data normalization processing on the total area of a pipeline bulge and a bending angle, comparing the pipeline risk value with a preset pipeline risk value threshold, and if the pipeline risk value is larger than the preset pipeline risk value threshold, marking the number of sub-pipelines corresponding to the pipeline risk value larger than the preset pipeline risk value threshold as a pipeline obstruction value;
s3: comparing the compression risk value and the pipeline obstruction value with a preset compression risk value threshold value and a preset pipeline obstruction value threshold value which are recorded and stored in the compression risk value and the pipeline obstruction value, and analyzing the compression risk value and the pipeline obstruction value:
if the compression risk value is smaller than a preset compression risk value threshold and the pipeline obstruction value is smaller than a preset pipeline obstruction value threshold, no signal is generated;
and if the compression risk value is greater than or equal to a preset compression risk value threshold or the pipeline obstruction value is greater than or equal to a preset pipeline obstruction value threshold, generating a risk signal.
4. The MEMS gas pressure sensor dispensing process monitoring system based on the internet of things of claim 1, wherein the dispensing interference risk assessment analysis process of the interference risk unit is as follows:
t1: taking equipment as a circle center, R1 as a radius, drawing a circle around the equipment to form an area, marking the area as a monitoring area, acquiring a temperature-humidity deviation value and a ventilation risk value of the monitoring area in each sub-time period, wherein the temperature-humidity deviation value represents a sum value obtained by carrying out data normalization processing on a part of the environment temperature value deviating from a preset range and a part of the environment humidity value deviating from the preset range, the ventilation risk value represents a part of the ventilation flow in unit time exceeding the ventilation flow in the preset unit time, and then carrying out data normalization processing on the sum value and the air humidity average value of the monitoring area to obtain product values, wherein the temperature-humidity deviation value and the ventilation risk value are respectively marked as WSi and TFi;
t2: according to the formulaObtaining a dispensing interference evaluation coefficient of each sub-time period, wherein a1 and a2 are preset scale factor coefficients of a temperature-humidity deviation value and a ventilation risk value respectively, a1 and a2 are positive numbers larger than zero, a3 is a preset correction factor coefficient, the value is 1.281, hi is a dispensing interference evaluation coefficient of each sub-time period, the dispensing interference evaluation coefficient Hi is compared with a stored preset dispensing interference evaluation coefficient threshold value, if the dispensing interference evaluation coefficient Hi is larger than the preset dispensing interference evaluation coefficient threshold value, the ratio of the number of sub-time periods corresponding to the dispensing interference evaluation coefficient Hi larger than the preset dispensing interference evaluation coefficient threshold value to the total number of sub-time periods is marked as a sector occupation ratio, and the sector occupation ratio is compared with a preset sector occupation ratio threshold value stored in the internal recording of the sector occupation ratio:
if the ratio between the sector occupancy rate and the preset sector occupancy rate threshold is smaller than 1, no signal is generated;
and if the ratio of the sector occupation ratio to the preset sector occupation ratio threshold is more than or equal to 1, generating an interference signal.
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