CN117130258A - Intelligent control system for microwave drying equipment - Google Patents

Abstract

The invention belongs to the technical field of microwave drying equipment, and particularly relates to an intelligent control system for microwave drying equipment, which comprises a processor, a material input detection module, a microwave drying operation monitoring module, an equipment operation risk prediction module and an intelligent regulation module, wherein the processor is in communication connection with the material input detection module, the microwave drying operation monitoring module, the equipment operation risk prediction module and the intelligent regulation module; according to the invention, the material input detection module is used for accurately detecting the material input condition and automatically regulating and controlling the transmission efficiency, the microwave drying operation monitoring module is used for carrying out operation monitoring analysis on the microwave drying equipment, the operation control on the microwave drying equipment is enhanced when the operation failure signal is judged, the subsequent operation of the microwave drying equipment is more stable, and the drying effect on the material drying efficiency is effectively ensured by combining the material input detection feedback and the equipment operation monitoring feedback.

Description

Intelligent control system for microwave drying equipment

Technical Field

The invention relates to the technical field of microwave drying equipment, in particular to an intelligent control system for microwave drying equipment.

Background

The microwave drying equipment is commonly used for drying and dehydrating powdery and granular materials, the traditional drying method has long time, high power consumption, uneven heating and high labor intensity, and microwave energy penetrates through the inside of an object to realize simultaneous heating inside and outside, so that the drying efficiency and the drying and dehydrating effects are greatly improved, and the sterilization effect is also realized during drying;

most of microwave drying equipment in the prior art is used for carrying out material input and output through a material conveying mechanism, the input condition of the material is difficult to detect in the drying process of the material, the automatic adaptive regulation and control on the material conveying efficiency cannot be carried out based on the quality condition of the material, the monitoring feedback on the running condition is difficult to realize in the drying running process of the microwave drying equipment, and the material input detection feedback and the equipment running monitoring feedback cannot be combined to ensure the drying effect on the drying efficiency of the material;

in view of the above technical drawbacks, a solution is now proposed.

Disclosure of Invention

The invention aims to provide an intelligent control system for microwave drying equipment, which solves the problems that the existing microwave drying equipment cannot automatically adaptively regulate and control the material conveying efficiency based on the quality condition of materials, is difficult to realize monitoring feedback on the running condition, and cannot combine the material input detection feedback with the equipment running monitoring feedback to ensure the drying efficiency drying effect of the materials.

In order to achieve the above purpose, the present invention provides the following technical solutions:

the intelligent control system for the microwave drying equipment comprises a processor, a material input detection module, a microwave drying operation monitoring module, an equipment operation risk prediction module and an intelligent regulation and control module, wherein the processor is in communication connection with the material input detection module, the microwave drying operation monitoring module, the equipment operation risk prediction module and the intelligent regulation and control module, and the equipment operation risk prediction module is in communication connection with an equipment early warning module;

the processor generates a material input detection signal in a detection period and sends the material input detection signal to the material input detection module, the material input detection module receives the material input detection signal, obtains the drying difficulty information of the material in the detection period through analysis and distributes a corresponding transmission coefficient range, obtains the transmission coefficient of the material in the detection period through analysis and judges whether the material input meets the requirement, generates a material input qualified signal or a material input unqualified signal based on a material input judging result, and sends the material input qualified signal or the material input unqualified signal to the processor;

after receiving the material input unqualified signal, the processor generates an input regulation signal and sends the input regulation signal to the intelligent regulation module, the intelligent regulation module carries out adaptive regulation on the material input, and after receiving the material input unqualified signal, the processor generates a monitoring analysis signal and sends the monitoring analysis signal to the microwave drying operation monitoring module; the microwave drying operation monitoring module is used for performing operation monitoring analysis on the microwave drying equipment after receiving the monitoring analysis signal, acquiring a drying stable value through operation drying analysis, generating an operation disqualification signal or an operation qualification signal according to the drying stable value, and sending the operation qualification signal or the operation disqualification signal to the processor;

after receiving the unqualified running signal, the processor generates a reinforced drying control signal and sends the reinforced drying control signal to the intelligent control module, and the intelligent control module reinforces the running control of the microwave drying equipment; the method comprises the steps that a processor generates a risk prediction signal, the risk prediction signal and a dry stable value are sent to a device operation risk prediction module, the device operation risk prediction module receives the risk prediction signal, then carries out operation risk analysis on microwave drying devices, generates a high-risk signal or a low-risk signal, and sends the high-risk signal or the low-risk signal to the processor; after the processor receives the high risk signal, an early warning instruction is generated and sent to the intelligent regulation module, and the intelligent regulation module controls the equipment early warning module to send out early warning to remind corresponding operators.

Further, the specific operation process of the material input detection module comprises the following steps:

acquiring a material drying difficulty coefficient of a detection period by analyzing the drying difficulty of the input material, marking the input material as a high-difficulty drying material, a medium-difficulty drying material or a low-difficulty drying material, and distributing a corresponding transmission coefficient range based on the drying difficulty information of the input material;

acquiring transmission information of the materials in the detection period, wherein the transmission information comprises the transmission speed of the materials and the paving thickness of the materials on a conveyor belt, marking the transmission speed of the materials and the paving thickness of the materials on the conveyor belt as a material speed value and a material thickness value, and carrying out numerical calculation on the material speed value and the material thickness value to acquire a transmission coefficient of the materials in the detection period;

and comparing the transmission coefficient of the material with the corresponding transmission coefficient range, if the transmission coefficient is in the corresponding transmission coefficient range, judging that the material input meets the requirement, generating a material input qualified signal and sending the material input qualified signal to the processor, and otherwise, generating a material input unqualified signal and sending the material input unqualified signal to the processor.

Further, the specific process of allocating the corresponding transmission coefficient range is as follows:

if the input material is a high-difficulty dry material, the corresponding transmission coefficient range is a low-efficiency transmission range, if the input material is a medium-difficulty dry material, the corresponding transmission coefficient range is a medium-efficiency transmission range, and if the input material is a low-difficulty dry material, the corresponding transmission coefficient range is a high-efficiency transmission range, the low-efficiency transmission range is smaller than the medium-efficiency transmission range, and the medium-efficiency transmission range is smaller than the high-efficiency transmission range.

Further, the specific analysis process of the drying difficulty analysis is as follows:

acquiring quality information of the material in the detection period, wherein the material quality information comprises water content data, bacterial amount data and material temperature data of the material, and marking the water content data and the bacterial data of the material as water content value, bacterial amount value and material Wen Liangzhi; carrying out numerical calculation on the water content value, the bacterial content value and the material Wen Liangzhi to obtain a drying difficulty coefficient of the material in a detection period, calling a preset drying difficulty coefficient range, and comparing the drying difficulty coefficient in the detection period with the drying difficulty coefficient range;

if the drying difficulty coefficient is larger than or equal to the maximum value of the drying difficulty coefficient range, marking the material input in the detection period as a high-difficulty drying material, wherein a plurality of drying difficulty coefficients are positioned in the drying difficulty coefficient range, marking the material input in the detection period as a medium-difficulty drying material, and marking the material input in the detection period as a low-difficulty drying material.

Further, the operation monitoring and analyzing process of the microwave drying operation monitoring module is specifically as follows:

dividing the detection period into a plurality of sub-analysis time points according to the equal time interval, marking the sub-analysis time points as u, u= {1,2, …, j }, j representing the number of the sub-analysis time points and j being a positive integer greater than 5; acquiring operation monitoring information of the microwave drying equipment at a sub-analysis time point u, wherein the operation monitoring information comprises microwave output power, real-time drying temperature and real-time dehumidification speed of the sub-analysis time point u;

marking sub-analysis time u as qualified drying time, high deviation drying time or low deviation drying time through time anomaly analysis, obtaining the qualified drying time number, the high deviation drying time number and the low deviation drying time number in a detection period through statistical analysis, and carrying out numerical calculation on the qualified drying time number, the high deviation drying time number and the low deviation drying time number to obtain a drying stability value;

and comparing the drying stability values with a preset drying stability threshold value, wherein a plurality of drying stability values are larger than or equal to the preset drying stability threshold value, judging that the microwave drying equipment is normal in operation in the detection period, generating an operation qualified signal and sending the operation qualified signal to the processor, and a plurality of drying stability values are smaller than the preset drying stability threshold value, judging that the microwave drying equipment is abnormal in operation in the detection period, generating an operation disqualification signal and sending the operation disqualification signal to the processor.

Further, the specific analysis process of the time point abnormality analysis is as follows:

obtaining a preset microwave output power range, a preset drying temperature range and a preset dehumidification speed range, performing difference calculation on the microwave output power of the sub-analysis time point u and the median value of the preset microwave output power range, taking an absolute value to obtain a microwave power magnitude value, performing difference calculation on the real-time drying temperature and the median value of the preset drying temperature range, taking an absolute value to obtain a real Wen Liangzhi, performing difference calculation on the real-time dehumidification speed and the median value of the preset dehumidification speed range, and taking an absolute value to obtain a dehumidification value;

performing numerical calculation on the microwave power magnitude, the real temperature magnitude and the moisture removal magnitude of the sub-analysis time point u to obtain a drying monitoring coefficient, comparing the drying monitoring coefficient with a preset drying monitoring coefficient threshold value, judging that the drying operation of the microwave drying equipment at the corresponding sub-analysis time point u is qualified if a plurality of drying monitoring coefficients are smaller than the preset drying coefficient threshold value, and marking the corresponding sub-analysis time point u as a qualified drying time point;

if the dryness monitoring coefficients are larger than or equal to a preset dryness monitoring coefficient threshold, carrying out difference calculation on the dryness monitoring coefficients and the preset dryness monitoring coefficient threshold, obtaining dryness deviation coefficients corresponding to sub-analysis time points u after the difference calculation, and comparing the dryness deviation coefficients with the preset dryness deviation coefficient threshold;

if the drying deviation coefficient is larger than or equal to the preset drying deviation coefficient threshold value, judging that the drying operation deviation degree of the microwave drying equipment at the corresponding sub-analysis time point u is large, marking the corresponding sub-analysis time point u as a high deviation drying time point, and judging that the drying operation deviation degree of the microwave drying equipment at the corresponding sub-analysis time point u is small if a plurality of drying deviation coefficients are smaller than the preset drying deviation coefficient threshold value, and marking the corresponding sub-analysis time point u as a low deviation drying time point.

Further, the specific operation process of the equipment operation risk prediction module is as follows:

acquiring a time-carrying value of the microwave drying equipment, wherein the time-carrying value represents a data value of continuous operation time of the microwave drying equipment, comparing the time-carrying value with a preset time-carrying value threshold, and if the time-carrying value is greater than or equal to the preset time-carrying value, generating a high risk signal and sending the high risk signal to a processor;

otherwise, acquiring a drying stability value of the microwave drying equipment, carrying out numerical calculation on the drying stability value and the time-of-transportation value to acquire a risk prediction value, comparing the risk prediction value with a preset risk prediction threshold, generating a high risk signal and sending the high risk signal to the processor if the risk prediction value is greater than or equal to the preset risk prediction threshold, and generating a low risk signal and sending the low risk signal to the processor if the risk prediction value is less than the preset risk threshold.

Compared with the prior art, the invention has the beneficial effects that:

1. according to the invention, the material input detection module is used for analyzing and judging the drying difficulty of the material, the corresponding transmission coefficient range is distributed based on the drying difficulty of the material, whether the material transmission efficiency meets the requirement is judged based on the corresponding transmission coefficient range, the processor is used for adaptively regulating and controlling the material input through the intelligent regulation and control module after receiving the material input failure signal, so that the accurate detection of the material input condition is realized, the transmission efficiency is automatically regulated and controlled, and the drying and sterilization efficiency and the drying and sterilization effect of the material are ensured;

2. according to the invention, the microwave drying equipment is subjected to operation monitoring analysis through the microwave drying operation monitoring module, an operation disqualification signal or an operation qualification signal is generated according to the operation monitoring analysis and is sent to the processor, the processor receives the operation disqualification signal, then generates a reinforced drying control signal and sends the reinforced drying control signal to the intelligent control module, the intelligent control module is used for reinforcing the operation control of the microwave drying equipment, the subsequent operation of the microwave drying equipment is more stable, and the drying efficiency and the drying effect of the material are effectively ensured by combining the material input detection feedback and the equipment operation monitoring feedback;

3. according to the invention, the equipment operation risk prediction module is used for analyzing the operation risk and generating the high risk signal or the low risk signal and sending the high risk signal to the processor, the processor receives the high risk signal and then generates the early warning instruction and sends the early warning instruction to the intelligent regulation module, and the intelligent regulation module controls the equipment early warning module to send early warning to remind corresponding operators, so that the operators can know the risk condition of the microwave drying equipment and timely make countermeasures, the equipment operation risk is reduced, and the continuous safe operation of the microwave drying equipment is forcefully ensured.

Drawings

For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;

fig. 1 is an overall system block diagram of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Embodiment one:

as shown in fig. 1, the intelligent control system for the microwave drying equipment provided by the invention comprises a processor, a material input detection module, a microwave drying operation monitoring module and an intelligent regulation and control module, wherein the processor is in communication connection with the material input detection module, the microwave drying operation monitoring module and the intelligent regulation and control module;

the processor generates a material input detection signal in a detection period and sends the material input detection signal to the material input detection module, the material input detection module receives the material input detection signal, obtains the drying difficulty information of the material in the detection period through analysis and distributes a corresponding transmission coefficient range, obtains the transmission coefficient of the material in the detection period through analysis and judges whether the material input meets the requirement, generates a material input qualified signal or a material input unqualified signal based on a material input judging result, and sends the material input qualified signal or the material input unqualified signal to the processor; the specific operation process of the material input detection module is as follows:

s1, obtaining a material drying difficulty coefficient of a detection period by carrying out drying difficulty analysis on an input material, and marking the input material as a high-difficulty drying material, a medium-difficulty drying material or a low-difficulty drying material, wherein the specific analysis process of the drying difficulty analysis is as follows:

step S11, acquiring quality information of materials in a detection period, wherein the quality information of the materials comprises water content data, bacterial amount data and material temperature data of the materials, and marking the water content data and the bacterial data of the materials as a water content value HS, a bacterial amount value XJ and a material Wen Liangzhi LW;

step S12, analyzing the formula through the drying difficultyCarrying out numerical calculation on the water content value HS, the bacterial value XJ and the material Wen Liangzhi LW to obtain a drying difficulty coefficient GN of the material in the detection period; wherein tq1, tq2 and tq3 are preset proportionality coefficients, the values of tq1, tq2 and tq3 are all larger than zero, and tq1 is more than tq2 and more than tq3;

it should be noted that, the drying difficulty coefficient GN is used for indicating the data value of the drying difficulty of the material, the numerical value of the drying difficulty coefficient GN is in a direct proportion relation with the moisture content value HS and the bacterial value XJ, and in an inverse proportion relation with the material Wen Liangzhi LW, the larger the numerical value of the moisture content value HS, the larger the numerical value of the bacterial value XJ and the smaller the numerical value of the material Wen Liangzhi LW, the larger the numerical value of the drying difficulty coefficient GN is, the worse the quality of the corresponding material is, and the larger the microwave drying difficulty of the corresponding material is indicated;

s13, calling a preset drying difficulty coefficient range, and comparing the drying difficulty coefficient of the detection period with the drying difficulty coefficient range;

if the drying difficulty coefficient is greater than or equal to the maximum value of the drying difficulty coefficient range, marking the material input in the detection period as a high-difficulty drying material; if the drying difficulty coefficient is within the range of the drying difficulty coefficient, marking the material input in the detection period as a medium-difficulty drying material; if the drying difficulty coefficients are smaller than or equal to the minimum value of the drying difficulty coefficient range, marking the materials input in the detection period as low-difficulty drying materials;

step S2, distributing a corresponding transmission coefficient range based on the drying difficulty information of the input materials, wherein the specific process of distributing the corresponding transmission coefficient range is as follows:

if the input material is a high-difficulty dry material, the corresponding transmission coefficient range is a low-efficiency transmission range, if the input material is a medium-difficulty dry material, the corresponding transmission coefficient range is a medium-efficiency transmission range, and if the input material is a low-difficulty dry material, the corresponding transmission coefficient range is a high-efficiency transmission range, the low-efficiency transmission range is smaller than the medium-efficiency transmission range, and the medium-efficiency transmission range is smaller than the high-efficiency transmission range;

step S3, acquiring transmission information of the materials in the detection period, wherein the transmission information comprises the transmission speed of the materials and the paving thickness of the materials on a conveyor belt, and marking the transmission speed of the materials and the paving thickness of the materials on the conveyor belt as a material speed value LS and a material thickness value LH;

s4, transmitting an analysis formulaCarrying out numerical calculation on a material speed value LS and a material thickness value LH, and obtaining a conveying coefficient CS of the material in a detection period after the numerical calculation; wherein, tu1 and tu2 are preset proportionality coefficients, the values of tu1 and tu2 are both larger than zero, and tu1 is larger than tu2;

it should be noted that, the transmission coefficient CS is a data value indicating the material conveying efficiency, the value of the transmission coefficient CS is in a proportional relationship with the material speed value LS and the material thickness value LH, and the larger the value of the material speed value LS and the larger the value of the material thickness value LH, the larger the value of the transmission coefficient CS indicates that the material conveying efficiency is higher;

and S5, comparing the transmission coefficient of the material with the corresponding transmission coefficient range, if the transmission coefficient is in the corresponding transmission coefficient range, judging that the material input meets the requirement, generating a material input qualified signal and sending the material input qualified signal to the processor, and otherwise, generating a material input unqualified signal and sending the material input unqualified signal to the processor.

After the processor receives the unqualified signals of the material input, an input regulation signal is generated and sent to the intelligent regulation module, the intelligent regulation module carries out adaptive regulation and control on the material input, the function of detecting the material input condition in the material drying process is realized, the automatic adaptive regulation and control on the material conveying efficiency can be carried out based on the quality condition of the material, the drying sterilization efficiency and the drying sterilization effect of the material are guaranteed, the problem that the material quality is poor but the conveying efficiency is too high to cause the drying of the material cannot achieve the required effect is solved, and the problem that the material quality is good but the conveying efficiency is too low to cause the drying efficiency of the material cannot be improved is avoided.

After receiving the material input qualified signal, the processor generates a monitoring analysis signal and sends the monitoring analysis signal to the microwave drying operation monitoring module; the operation monitoring and analyzing process of the microwave drying operation monitoring module comprises the following steps of:

step T1, dividing the detection period into a plurality of sub-analysis time points according to the time interval, marking the sub-analysis time points as u, u= {1,2, …, j }, wherein j represents the number of the sub-analysis time points and j is a positive integer greater than 5;

step T2, acquiring operation monitoring information of the microwave drying equipment at a sub-analysis time point u, wherein the operation monitoring information comprises the microwave output power, the real-time drying temperature and the real-time dehumidification speed of the sub-analysis time point u, and marking the microwave output power, the real-time drying temperature and the real-time dehumidification speed of the sub-analysis time point u as GL, ZW and PS;

in the step T3, the sub-analysis time point u is marked as a qualified dry time point, a high deviation dry time point or a low deviation dry time point by a time point abnormality analysis, and the specific analysis process of the time point abnormality analysis is as follows:

step T31, obtaining a preset microwave output power range (GLmin, GLmax), a preset drying temperature range (ZWmin, ZWmax) and a preset dehumidification speed range (PSmin, PSmax), wherein the median value of the preset microwave output power range is (GLmin+GLmax)/2, the median value of the preset drying temperature range is (ZWmin+ZWmax)/2, and the median value of the preset dehumidification speed range is (PSmin+PSmax)/2;

performing difference calculation on the microwave output power GL of the sub-analysis time point u and the median value of the preset microwave output power range, taking an absolute value to obtain a microwave power magnitude GLz, performing difference calculation on the real-time drying temperature ZW and the median value of the preset drying temperature range, taking an absolute value to obtain a real Wen Liangzhi ZWz, performing difference calculation on the real-time dehumidification speed PS and the median value of the preset dehumidification speed range, and taking an absolute value to obtain a dehumidification capacity value PSz;

step T32, performing numerical calculation on the microwave power value GLz, the real Wen Liangzhi ZWz and the moisture removal value PSz of the sub-analysis time point u through a monitoring analysis formula zjx=a1× GLz +a2× ZWz +a3× PSz, and obtaining a drying monitoring coefficient ZJX after the numerical calculation; wherein a1, a2 and a3 are preset weight coefficients, and a1 is more than a2 and more than a3 is more than 0;

it should be noted that, the drying monitoring coefficient ZJX represents the deviation degree of the real-time running condition of the microwave drying device compared with the preset suitable running parameter, the drying monitoring coefficient ZJX is in a proportional relation with the microwave power value GLz, the real Wen Liangzhi ZWz and the moisture removal value PSz, the smaller the value of the microwave power value GLz, the smaller the value of the real Wen Liangzhi ZWz and the smaller the value of the moisture removal value PSz, the smaller the value of the drying monitoring coefficient ZJX is, which indicates that the smaller the running deviation degree of the microwave drying device at the corresponding sub-analysis time point u is, the better the microwave drying effect is and the running process is stable;

step T33, a preset drying monitoring coefficient threshold value is called, the drying monitoring coefficient ZJX is compared with the preset drying monitoring coefficient threshold value, if a plurality of drying monitoring coefficients ZJX are smaller than the preset drying coefficient threshold value, the drying operation of the microwave drying equipment at the corresponding sub-analysis time point u is judged to be qualified, and the corresponding sub-analysis time point u is marked as a qualified drying time point;

if the dryness monitoring coefficient ZJX is larger than or equal to a preset dryness monitoring coefficient threshold, performing difference calculation on the dryness monitoring coefficient ZJX and the preset dryness monitoring coefficient threshold, acquiring a dryness deviation coefficient ZPX corresponding to a sub-analysis time point u after the difference calculation, calling the preset dryness deviation coefficient threshold, and comparing the dryness deviation coefficient ZPX with the preset dryness deviation coefficient threshold;

if the dryness deviation coefficient ZPX is larger than or equal to a preset dryness deviation coefficient threshold value, judging that the dryness operation deviation degree of the microwave drying equipment at the corresponding sub-analysis time point u is large, marking the corresponding sub-analysis time point u as a high deviation dryness time point, and if the dryness deviation coefficient ZPX is smaller than the preset dryness deviation coefficient threshold value, judging that the dryness operation deviation degree of the microwave drying equipment at the corresponding sub-analysis time point u is small, marking the corresponding sub-analysis time point u as a low deviation dryness time point;

step T4, obtaining the number of qualified drying time points, the number of high deviation drying time points and the number of low deviation drying time points in the detection period through statistical analysis, and marking the number of qualified drying time points, the number of high deviation drying time points and the number of low deviation drying time points as HZS, GZS, DZS respectively;

stabilization of analytical formulas by dryingPerforming numerical calculation on the qualified drying time point number HZS, the high deviation drying time point number GZS and the low deviation drying time point number DZS, and obtaining a drying stable value GWZ after the numerical calculation; wherein b1, b2 and b3 are preset proportionality coefficients, the values of b1, b2 and b3 are all larger than zero, and b2 is larger than b3 and larger than b1;

it should be noted that, the magnitude of the drying stable value GWZ is in a direct proportion to the number of qualified drying time points HZS, and in an inverse proportion to the number of high deviation drying time points GZS and the number of low deviation drying time points DZS, the larger the magnitude of the qualified drying time point number HZS, the smaller the magnitude of the high deviation drying time point number GZS, and the smaller the magnitude of the low deviation drying time point number DZS, the larger the magnitude of the drying stable value GWZ indicates that the microwave drying equipment operates stably in the detection period;

and T5, calling a preset drying stability threshold, comparing the drying stability value GWZ with the preset drying stability threshold in a numerical value, judging that the microwave drying equipment in the detection period runs normally if the drying stability value GWZ is larger than or equal to the preset drying stability threshold, generating a running qualified signal and sending the running qualified signal to the processor, judging that the microwave drying equipment in the detection period runs abnormally if the drying stability value GWZ is smaller than the preset drying stability threshold, generating a running unqualified signal and sending the running unqualified signal to the processor.

The microwave drying operation monitoring module generates an operation disqualification signal or an operation qualification signal through operation monitoring analysis, the operation disqualification signal or the operation disqualification signal is sent to the processor, the processor receives the operation disqualification signal, generates a reinforced drying control signal and sends the reinforced drying control signal to the intelligent control module, and the intelligent control module reinforces the operation control of the microwave drying equipment, reinforces the control of the microwave output power, the drying temperature and the dehumidifying speed of the microwave drying equipment, so that various actual operation parameters of the microwave drying equipment in the subsequent operation process are kept in a preset proper range, the subsequent operation of the microwave drying equipment is more stable, and the microwave drying effect and the microwave drying efficiency are ensured.

Embodiment two:

as shown in fig. 1, the difference between the present embodiment and embodiment 1 is that the present embodiment further includes a device operation risk prediction module, the processor is communicatively connected to the device operation risk prediction module, and the device operation risk prediction module is communicatively connected to the device early warning module; the processor generates a risk prediction signal, sends the risk prediction signal and a dry stable value GWZ to the equipment operation risk prediction module, and performs microwave drying equipment after the equipment operation risk prediction module receives the risk prediction signal, wherein the specific operation process of the equipment operation risk prediction module is as follows:

acquiring a transportation time value of the microwave drying equipment and marking the transportation time value as YSL, wherein the transportation time value YSL represents a data value of continuous operation time of the microwave drying equipment, a preset transportation time value threshold value is called, the transportation time value YSL is compared with the preset transportation time value threshold value, and if the transportation time value YSL is greater than or equal to the preset transportation time value, a high risk signal is generated and sent to a processor;

otherwise, acquiring a drying stable value GWZ of the microwave drying equipment, and carrying out numerical calculation on the drying stable value GWZ and a transportation time value YSL through a risk prediction formula FCZ=kp1+kp2; wherein, kp1 and kp2 are preset weight coefficients, the values of kp1 and kp2 are both larger than zero, and kp1 is larger than kp2; the risk prediction value FCZ, the drying stability value GWZ and the transportation time value YSL are in a direct proportion relation, the larger the value of the drying stability value GWZ and the larger the value of the transportation time value YSL are, the larger the value of the risk prediction value FCZ is, which indicates that the operation risk of the microwave drying equipment is larger in a detection period;

and calling a preset risk prediction threshold value, comparing the risk prediction value FCZ with the preset risk prediction threshold value, generating a high risk signal and sending the high risk signal to the processor if the risk prediction value FCZ is larger than or equal to the preset risk prediction threshold value, and generating a low risk signal and sending the low risk signal to the processor if the risk prediction value FCZ is smaller than the preset risk threshold value.

The equipment operation risk prediction module generates a high risk signal or a low risk signal through operation risk analysis and sends the high risk signal or the low risk signal to the processor; after the processor receives the high-risk signal, an early warning instruction is generated and sent to the intelligent regulation module, and the intelligent regulation module controls the equipment early warning module to send early warning to remind corresponding operators, so that the operators can know the risk condition of the microwave drying equipment in time, and make corresponding countermeasures in time when the risk early warning is received, the risk existing in the operation of the equipment is reduced, and the continuous safe operation of the microwave drying equipment is ensured; preferably, the equipment early warning module comprises an alarm and a warning lamp, and when receiving an early warning instruction, the equipment early warning module gives out an alarm sound and continuously flashes light to improve the warning effect.

The working principle of the invention is as follows: when the intelligent material drying and sterilizing device is used, the material input detection module judges the drying difficulty of materials through analysis and distributes corresponding transmission coefficient ranges, judges whether the material transmission efficiency meets the requirements or not based on the corresponding transmission coefficient ranges, and carries out adaptive regulation and control on the material input through the intelligent regulation and control module after receiving a material input unqualified signal, so that the accurate detection on the material input condition is realized, the transmission efficiency is automatically regulated and controlled, and the drying and sterilizing efficiency and the drying and sterilizing effect of the materials are ensured; the microwave drying operation monitoring module performs operation monitoring analysis on the microwave drying equipment, generates an operation disqualification signal or an operation qualification signal according to the operation disqualification signal, and sends the operation disqualification signal to the processor, the processor receives the operation disqualification signal, generates a reinforced drying control signal and sends the reinforced drying control signal to the intelligent control module, the intelligent control module reinforces operation control on the microwave drying equipment, the subsequent operation of the microwave drying equipment is more stable, and the drying efficiency drying effect on the material is effectively ensured by combining material input detection feedback and equipment operation monitoring feedback.

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 (7)

1. The intelligent control system for the microwave drying equipment is characterized by comprising a processor, a material input detection module, a microwave drying operation monitoring module, an equipment operation risk prediction module and an intelligent regulation and control module, wherein the processor is in communication connection with the material input detection module, the microwave drying operation monitoring module, the equipment operation risk prediction module and the intelligent regulation and control module, and the equipment operation risk prediction module is in communication connection with an equipment early warning module;

the processor generates a material input detection signal in a detection period and sends the material input detection signal to the material input detection module, the material input detection module receives the material input detection signal, obtains the drying difficulty information of the material in the detection period through analysis and distributes a corresponding transmission coefficient range, obtains the transmission coefficient of the material in the detection period through analysis and judges whether the material input meets the requirement, generates a material input qualified signal or a material input unqualified signal based on a material input judging result, and sends the material input qualified signal or the material input unqualified signal to the processor;

after receiving the material input unqualified signal, the processor generates an input regulation signal and sends the input regulation signal to the intelligent regulation module, the intelligent regulation module carries out adaptive regulation on the material input, and after receiving the material input unqualified signal, the processor generates a monitoring analysis signal and sends the monitoring analysis signal to the microwave drying operation monitoring module; the microwave drying operation monitoring module is used for performing operation monitoring analysis on the microwave drying equipment after receiving the monitoring analysis signal, acquiring a drying stable value through operation drying analysis, generating an operation disqualification signal or an operation qualification signal according to the drying stable value, and sending the operation qualification signal or the operation disqualification signal to the processor;

after receiving the unqualified running signal, the processor generates a reinforced drying control signal and sends the reinforced drying control signal to the intelligent control module, and the intelligent control module reinforces the running control of the microwave drying equipment; the method comprises the steps that a processor generates a risk prediction signal, the risk prediction signal and a dry stable value are sent to a device operation risk prediction module, the device operation risk prediction module receives the risk prediction signal, then carries out operation risk analysis on microwave drying devices, generates a high-risk signal or a low-risk signal, and sends the high-risk signal or the low-risk signal to the processor; after the processor receives the high risk signal, an early warning instruction is generated and sent to the intelligent regulation module, and the intelligent regulation module controls the equipment early warning module to send out early warning to remind corresponding operators.

2. The intelligent control system for a microwave drying apparatus of claim 1, wherein the specific operation of the material input detection module comprises:

acquiring a material drying difficulty coefficient of a detection period by analyzing the drying difficulty of the input material, marking the input material as a high-difficulty drying material, a medium-difficulty drying material or a low-difficulty drying material, and distributing a corresponding transmission coefficient range based on the drying difficulty information of the input material;

acquiring transmission information of the materials in the detection period, wherein the transmission information comprises the transmission speed of the materials and the paving thickness of the materials on a conveyor belt, marking the transmission speed of the materials and the paving thickness of the materials on the conveyor belt as a material speed value and a material thickness value, and carrying out numerical calculation on the material speed value and the material thickness value to acquire a transmission coefficient of the materials in the detection period;

and comparing the transmission coefficient of the material with the corresponding transmission coefficient range, if the transmission coefficient is in the corresponding transmission coefficient range, judging that the material input meets the requirement, generating a material input qualified signal and sending the material input qualified signal to the processor, and otherwise, generating a material input unqualified signal and sending the material input unqualified signal to the processor.

3. An intelligent control system for a microwave drying appliance according to claim 2, wherein the specific process of assigning the corresponding transmission coefficient range is as follows:

if the input material is a high-difficulty dry material, the corresponding transmission coefficient range is a low-efficiency transmission range, if the input material is a medium-difficulty dry material, the corresponding transmission coefficient range is a medium-efficiency transmission range, and if the input material is a low-difficulty dry material, the corresponding transmission coefficient range is a high-efficiency transmission range, the low-efficiency transmission range is smaller than the medium-efficiency transmission range, and the medium-efficiency transmission range is smaller than the high-efficiency transmission range.

4. An intelligent control system for a microwave drying apparatus according to claim 3, wherein the specific analysis procedure for the drying difficulty analysis is as follows:

acquiring quality information of the material in the detection period, wherein the material quality information comprises water content data, bacterial amount data and material temperature data of the material, and marking the water content data and the bacterial data of the material as water content value, bacterial amount value and material Wen Liangzhi; carrying out numerical calculation on the water content value, the bacterial content value and the material Wen Liangzhi to obtain a drying difficulty coefficient of the material in a detection period, calling a preset drying difficulty coefficient range, and comparing the drying difficulty coefficient in the detection period with the drying difficulty coefficient range;

if the drying difficulty coefficient is larger than or equal to the maximum value of the drying difficulty coefficient range, marking the material input in the detection period as a high-difficulty drying material, wherein a plurality of drying difficulty coefficients are positioned in the drying difficulty coefficient range, marking the material input in the detection period as a medium-difficulty drying material, and marking the material input in the detection period as a low-difficulty drying material.

5. An intelligent control system for a microwave drying apparatus according to claim 1, wherein the operation monitoring analysis process of the microwave drying operation monitoring module is specifically as follows:

dividing the detection period into a plurality of sub-analysis time points according to the equal time interval, marking the sub-analysis time points as u, u= {1,2, …, j }, j representing the number of the sub-analysis time points and j being a positive integer greater than 5; acquiring operation monitoring information of the microwave drying equipment at a sub-analysis time point u, wherein the operation monitoring information comprises microwave output power, real-time drying temperature and real-time dehumidification speed of the sub-analysis time point u;

marking sub-analysis time u as qualified drying time, high deviation drying time or low deviation drying time through time anomaly analysis, obtaining the qualified drying time number, the high deviation drying time number and the low deviation drying time number in a detection period through statistical analysis, and carrying out numerical calculation on the qualified drying time number, the high deviation drying time number and the low deviation drying time number to obtain a drying stability value;

and comparing the drying stability values with a preset drying stability threshold value, wherein a plurality of drying stability values are larger than or equal to the preset drying stability threshold value, judging that the microwave drying equipment is normal in operation in the detection period, generating an operation qualified signal and sending the operation qualified signal to the processor, and a plurality of drying stability values are smaller than the preset drying stability threshold value, judging that the microwave drying equipment is abnormal in operation in the detection period, generating an operation disqualification signal and sending the operation disqualification signal to the processor.

6. The intelligent control system for a microwave drying apparatus according to claim 5, wherein the specific analysis process of the time point abnormality analysis is as follows:

obtaining a preset microwave output power range, a preset drying temperature range and a preset dehumidification speed range, performing difference calculation on the microwave output power of the sub-analysis time point u and the median value of the preset microwave output power range, taking an absolute value to obtain a microwave power magnitude value, performing difference calculation on the real-time drying temperature and the median value of the preset drying temperature range, taking an absolute value to obtain a real Wen Liangzhi, performing difference calculation on the real-time dehumidification speed and the median value of the preset dehumidification speed range, and taking an absolute value to obtain a dehumidification value;

performing numerical calculation on the microwave power magnitude, the real temperature magnitude and the moisture removal magnitude of the sub-analysis time point u to obtain a drying monitoring coefficient, comparing the drying monitoring coefficient with a preset drying monitoring coefficient threshold value, judging that the drying operation of the microwave drying equipment at the corresponding sub-analysis time point u is qualified if a plurality of drying monitoring coefficients are smaller than the preset drying coefficient threshold value, and marking the corresponding sub-analysis time point u as a qualified drying time point;

if the dryness monitoring coefficients are larger than or equal to a preset dryness monitoring coefficient threshold, carrying out difference calculation on the dryness monitoring coefficients and the preset dryness monitoring coefficient threshold, obtaining dryness deviation coefficients corresponding to sub-analysis time points u after the difference calculation, and comparing the dryness deviation coefficients with the preset dryness deviation coefficient threshold;

if the drying deviation coefficient is larger than or equal to the preset drying deviation coefficient threshold value, judging that the drying operation deviation degree of the microwave drying equipment at the corresponding sub-analysis time point u is large, marking the corresponding sub-analysis time point u as a high deviation drying time point, and judging that the drying operation deviation degree of the microwave drying equipment at the corresponding sub-analysis time point u is small if a plurality of drying deviation coefficients are smaller than the preset drying deviation coefficient threshold value, and marking the corresponding sub-analysis time point u as a low deviation drying time point.

7. The intelligent control system for a microwave drying appliance of claim 6, wherein the specific operational process of the appliance operational risk prediction module is as follows:

acquiring a time-carrying value of the microwave drying equipment, wherein the time-carrying value represents a data value of continuous operation time of the microwave drying equipment, comparing the time-carrying value with a preset time-carrying value threshold, and if the time-carrying value is greater than or equal to the preset time-carrying value, generating a high risk signal and sending the high risk signal to a processor;

otherwise, acquiring a drying stability value of the microwave drying equipment, carrying out numerical calculation on the drying stability value and the time-of-transportation value to acquire a risk prediction value, comparing the risk prediction value with a preset risk prediction threshold, generating a high risk signal and sending the high risk signal to the processor if the risk prediction value is greater than or equal to the preset risk prediction threshold, and generating a low risk signal and sending the low risk signal to the processor if the risk prediction value is less than the preset risk threshold.