CN118071130A - Sound early warning processing method and device, electronic equipment and storage medium - Google Patents

Abstract

The invention discloses a sound early warning processing method, a device, electronic equipment and a storage medium, which concretely comprises the following steps: in the tobacco shred preparation process, current tobacco shred processing parameters corresponding to different preparation nodes of the tobacco shreds are obtained, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds; determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule; when the tobacco shred processing parameters meet the target early warning rules, early warning information is generated based on the target early warning rules, and the early warning information is sent to a target early warning terminal for voice early warning. According to the invention, by acquiring various parameter data in the tobacco shred preparation process, real-time rapid sound early warning is carried out on different preparation nodes, and the comprehensiveness and accuracy of early warning information are ensured.

Description

Sound early warning processing method and device, electronic equipment and storage medium

Technical Field

The invention relates to the technical field of tobacco shred preparation, in particular to a sound early warning processing method, a device, electronic equipment and a storage medium.

Background

In the tobacco shred preparation process, a plurality of working procedures are included, and each working procedure includes corresponding control tasks. Therefore, each process needs to be monitored to ensure that the wire making process is performed smoothly.

At present, a mode of combining a timing alarm clock with a voice prompt is mainly adopted for monitoring and processing production procedures. However, the processing mode cannot realize judgment and real-time early warning reminding according to the production change of the tobacco shred preparation process. Based on the method, corresponding preparation nodes are arranged for each production procedure in the tobacco shred preparation process, so that accurate sound early warning processing is carried out on each production procedure based on tobacco shred processing parameters corresponding to the preparation nodes.

Disclosure of Invention

The invention provides a sound early warning processing method, a device, electronic equipment and a storage medium, which realize real-time and rapid sound early warning on different preparation nodes and ensure the comprehensiveness and accuracy of early warning information.

According to an aspect of the present invention, there is provided a sound warning processing method, including:

In the tobacco shred preparation process, current tobacco shred processing parameters corresponding to different preparation nodes of the tobacco shreds are obtained, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds;

determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule;

when the tobacco shred processing parameters meet the target early warning rules, early warning information is generated based on the target early warning rules, and the early warning information is sent to a target early warning terminal for voice early warning.

According to another aspect of the present invention, there is provided a sound warning processing apparatus including:

The parameter acquisition module is used for acquiring current tobacco shred processing parameters corresponding to different preparation nodes of the tobacco shreds in the tobacco shred preparation process, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds;

The target early warning rule determining module is used for determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule;

and the sound early warning module is used for generating early warning information based on the target early warning rule when the tobacco shred processing parameters meet the target early warning rule, and sending the early warning information to the target early warning terminal for sound early warning.

According to another aspect of the present invention, there is provided an electronic device including:

at least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the acoustic pre-warning processing method of any one of the embodiments of the present invention.

According to another aspect of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to execute the sound warning processing method of any one of the embodiments of the present invention.

According to the technical scheme, current tobacco shred processing parameters corresponding to tobacco shreds at different preparation nodes are obtained in the tobacco shred preparation process, the pre-warning rule to be called is determined according to the preparation nodes and tobacco shred brands of the tobacco shreds, the pre-warning rule to be called is used as a target pre-warning rule, further, when the tobacco shred processing parameters meet the target pre-warning rule, pre-warning information is generated based on the target pre-warning rule, and the pre-warning information is sent to a target pre-warning terminal to perform voice pre-warning. The method solves the problem that the prior art cannot realize real-time early warning and reminding according to production change in the tobacco shred preparation process, achieves the effect of real-time rapid early warning on each preparation node in the tobacco shred preparation process, ensures the comprehensiveness and accuracy of early warning information, and improves the early warning processing efficiency.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention or to delineate the scope of the invention. Other features of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flowchart of a method for processing voice early warning according to an embodiment of the present invention;

FIG. 2 is a flowchart of a method for processing voice early warning according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of a sound early warning processing device according to an embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device implementing a sound warning processing method according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a sound early warning processing method provided by the embodiment of the invention, where the embodiment is applicable to a situation that in a tobacco shred preparation process, tobacco shred processing parameters of each preparation node are judged and real-time sound early warning is performed, the method may be performed by a sound early warning processing device, the sound early warning processing device may be implemented in a form of hardware and/or software, and the sound early warning processing device may be configured in an electronic device such as a mobile phone, a computer or a server. As shown in fig. 1, the method includes:

S110, acquiring current tobacco shred processing parameters corresponding to different preparation nodes of tobacco shreds in the tobacco shred preparation process, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current tobacco shred feeding parameters.

In the production and preparation process of the cut tobacco, a plurality of production lines are included, and each production line includes a plurality of production procedures, then one or more preparation nodes can be arranged on each production procedure. Namely, the preparation node is a node which needs to monitor the tobacco shred production process. For example, the preparation node can be a monitoring node flexibly selected according to actual requirements in the stages of pretreatment stage, tobacco shred mixing stage, feeding stage, tobacco shred drying stage and the like. In the tobacco shred preparation process, tobacco shred processing parameters corresponding to each preparation node at different time points are slightly different, so that the tobacco shred processing parameters corresponding to each preparation node at the current time point, namely the current tobacco shred processing parameters, need to be acquired. The current tobacco shred processing parameters can comprise current equipment operation parameters and current feeding parameters during tobacco shred processing. Alternatively, the current equipment operating parameters may include equipment parameter data and equipment status data in the wire manufacturing line. The current feeding parameters can be understood as process parameter data determined by the production formula and actual requirements in the tobacco shred preparation process, for example, the current feeding parameters can be parameter data such as feeding, blending and flavoring process variation coefficients, standard deviation of moisture at the outlet of the tobacco shred, and the like, and the embodiment is not limited to this.

Specifically, in the tobacco shred preparation process, data acquisition can be performed on different preparation nodes based on corresponding data acquisition software so as to obtain current tobacco shred processing parameters corresponding to each preparation node, so that whether sound early warning processing is performed or not can be judged according to the current tobacco shred processing parameters.

Illustratively, KEPSERVER can be used as data acquisition software, and is connected with PLC (Programmable Logic Controller ) equipment of a tobacco shred preparation workshop, and current tobacco shred processing parameters in the tobacco shred preparation process are acquired in real time. For example, the current tobacco shred processing parameters may include current charging parameter data such as electronic scale flow, moisture, temperature and the like collected by the instrument, and current equipment operation parameter data such as equipment operation state signals, recipe work order information and the like. And then, the collected tobacco shred processing parameters can be subjected to standardized processing through an OPC server and converted into a format meeting the follow-up processing.

It should be noted that, for the current tobacco brand, there are corresponding current tobacco processing parameters in each preparation node. The current tobacco shred processing parameters may include current equipment operating parameters and current charging parameters. The current equipment operation parameters can comprise two main types, namely, abnormal material conveying, such as the operation states of various equipment for processing tobacco shreds, a motor, a photoelectric switch, a conveyer belt forward and reverse rotation, a turnover door and the like; and secondly, equipment operation fault types, such as corresponding equipment parameter data during equipment fault operation. In addition, the current feeding parameters can be divided into two parts, namely parameters which are required by a definite process standard range in the tobacco shred preparation process and parameters which are not mentioned by the process standard but are necessary for production in the tobacco shred preparation process, such as parameters of water feeding quantity, steam quantity, feed liquid flow and the like.

And S120, determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule.

The tobacco number can be understood as a way of distinguishing or identifying different types, qualities or styles of tobacco, for example, a-brand tobacco, B-brand tobacco, etc. And selecting the pre-warning rules to be called corresponding to each preparation node from the corresponding database according to the corresponding tobacco brands in the current tobacco shred preparation process. The pre-warning rule to be called can be understood to judge the current tobacco shred processing parameters of the current preparation node. The pre-warning rules to be called corresponding to different preparation nodes are different. The target early warning rule can be selected from a plurality of early warning rules to be called, and the rules of the current tobacco shred marks and the current preparation nodes are met.

Specifically, according to the tobacco shred marks of the current tobacco shreds and each preparation node, selecting a to-be-called early warning rule matched with the current tobacco shred marks and the current preparation node from a plurality of to-be-called early warning rules determined in advance, and taking the to-be-called early warning rule as a target early warning rule. For different preparation nodes, the target early warning rule corresponding to each preparation node needs to be determined, namely at least one target early warning rule can be determined. Based on the method, whether sound early warning is carried out on the corresponding preparation node or not can be conveniently judged based on the target early warning rule.

Before the pre-warning rule to be invoked is invoked, an equipment parameter pre-warning threshold and a charging parameter pre-warning threshold are also required to be determined, so that the pre-warning rule to be invoked is determined based on at least one of the thresholds.

Optionally, the method further comprises: acquiring historical tobacco shred processing parameters corresponding to different tobacco shred brands at each preparation node, wherein the historical tobacco shred processing parameters comprise historical equipment operation parameters and historical charging parameters corresponding to each preparation node; carrying out statistical analysis on historical equipment operation parameters corresponding to each preparation node of each tobacco shred mark for tobacco shreds of each tobacco shred mark to obtain a statistical result corresponding to each preparation node, wherein the statistical result comprises at least one of a mean value, an extreme value and a variance of the historical equipment operation parameters under at least one reference field; determining equipment parameter early warning thresholds corresponding to all preparation nodes based on statistical results; and taking the equipment parameter early warning threshold value as one item of data in the early warning rule to be called.

After the data acquisition device acquires the tobacco shred processing parameters, the tobacco shred processing parameters can be stored in a corresponding time sequence database so as to acquire historical tobacco shred processing parameters from the time sequence database, and the setting of the pre-warning rule to be called is performed. The historical tobacco shred processing parameters may include historical equipment operating parameters and historical charging parameters corresponding to each preparation node. The operation parameters of the historical equipment can be the operation parameters of tobacco shred processing equipment corresponding to each preparation node when the tobacco shreds with the tobacco shred brands are produced in the past. Optionally, the historical device operating parameters may include an operating state of the tobacco processing device. The historical charging parameters can be production process parameter data corresponding to the tobacco shreds in the traditional tobacco shred preparation process. It should be noted that, in the tobacco shred preparation process of the current tobacco shred brand, different preparation nodes all have corresponding historical tobacco shred processing parameters. Statistical results may be understood as the results of the calculation of the mean, extremum and/or variance of the historical equipment operating parameters. Further, a device parameter early warning threshold is obtained based on the statistical result. The device parameter early warning threshold may be a standard value corresponding to each preparation node set based on the statistical result. When the current equipment operation parameters reach the equipment parameter early warning threshold, one condition in the early warning rule to be called is considered to be satisfied. Optionally, the device parameter early-warning threshold may include a device early-warning state and a device operating parameter early-warning value. For example, the device parameter pre-warning threshold may be set to a corresponding upper limit, lower limit, and center value, which are only examples herein, and the present implementation does not limit the number of device parameter pre-warning thresholds.

Specifically, historical tobacco shred processing parameters corresponding to each tobacco shred mark in each preparation node are obtained from a corresponding time sequence database. The historical tobacco shred processing parameters can comprise historical equipment operation parameters and historical charging parameters corresponding to each preparation node. After determining the historical tobacco shred processing parameters of each brand, for the tobacco shreds of each tobacco shred brand, the historical equipment operation parameters of each preparation node of the current tobacco shred brand can be subjected to extremum, mean and/or variance processing under at least one reference field so as to obtain a statistical result corresponding to each preparation node. Further, setting a corresponding equipment parameter early warning threshold value for each preparation node according to the statistical result, and taking the equipment parameter early warning threshold value as one item of data in the early warning rule to be called.

Optionally, the method further comprises: for the tobacco shreds of each tobacco shred mark, carrying out statistical analysis on historical charging parameters corresponding to each preparation node of the current tobacco shred mark, and determining initial parameter early warning values corresponding to each preparation node; based on the historical charging parameters and the environmental parameters, adjusting the initial parameter early warning values to obtain charging parameter early warning thresholds corresponding to all the preparation nodes; the charging parameter early warning threshold value comprises an initial parameter early warning value and a parameter adjusting value; and taking the feeding parameter early warning threshold value as one item of data in the early warning rule to be called.

The statistical analysis can be to calculate parameter mean, standard deviation, variation coefficient and the like of the historical charging parameters. Alternatively, the historical feed parameters may be feed amount, feed time, feed ratio, etc. The initial parameter early warning value can be an early warning threshold value which is set according to the result of statistical analysis and industry standards and meets the actual requirements. For example, the initial parameter early-warning value may be set as a standard deviation of the parameter mean value plus or minus a certain multiple, which is only taken as an example and does not limit the specific setting manner of the initial parameter early-warning value. The environmental parameter is understood to be environmental data of the tobacco shred of the current tobacco shred brand in the tobacco shred preparation process, for example, the environmental parameter can be data such as temperature, humidity and the like. The charging parameter early warning threshold value can be data obtained after the initial parameter early warning value is adjusted according to the environmental parameter. Namely, the environmental parameters are different, and the obtained charging parameter early warning thresholds are also different.

Specifically, for the tobacco shreds of each tobacco shred grade, after the historical feeding parameters of the tobacco shreds of the current tobacco shred grade at each preparation node are obtained, the corresponding environmental parameters, such as temperature, humidity and the like, of the tobacco shreds of the current tobacco shred grade in the historical preparation process are also required to be obtained, and the environmental parameters also influence the tobacco shred preparation effect. Further, statistical analysis is carried out on the historical charging parameters of each preparation node of the current tobacco shred brand, and statistics such as parameter mean values, standard deviation and variation coefficients corresponding to each preparation node are calculated. Therefore, according to the statistical result and in combination with the standard in the industry, the initial parameter early warning value corresponding to each preparation node is determined. After the initial parameter early-warning value is obtained, the initial parameter early-warning value is adjusted by utilizing the environmental parameter so as to compensate the influence of environmental factors on the tobacco shred preparation process and obtain the feeding parameter early-warning threshold. Further, the charging parameter early warning threshold value is used as one item of data in the early warning rule to be called.

Optionally, the method further comprises: determining an early warning judging function based on at least one of the equipment parameter early warning threshold and the feeding parameter early warning threshold, wherein the early warning judging function comprises the equipment parameter early warning threshold and/or the feeding parameter early warning threshold and corresponding judging symbols; setting early warning buffer time for the early warning judging function, wherein the early warning buffer time is the duration time when the early warning judging function is met; and determining the pre-warning rules to be called corresponding to the tobacco shred marks at different preparation nodes based on the pre-warning judging function and the pre-warning buffer time, wherein the pre-warning rules to be called corresponding to the different tobacco shred marks are different.

The early warning judging function can be a function for judging whether the tobacco shred processing parameters reach early warning conditions. The early warning decision function may include a device parameter early warning threshold and/or a charging parameter early warning threshold and corresponding decision symbols. Alternatively, the decision symbol may be a logical operator. For example, the early warning decision function may be equal to (current equipment operating parameter > equipment parameter early warning threshold) and (current charging parameter > charging parameter early warning threshold), which is given here by way of example only, and may be set to different representations according to specific requirements, so as to meet the requirements of actual wire making. In addition, in order to meet the actual production needs, the early warning judging function may set additional conditions, and the additional conditions may be conditions set by production personnel according to the actual needs. The early warning buffer time can be set according to actual requirements, and the time lasts after the early warning judging function is met. For example, when the pre-warning determination function is a function of whether the temperature of the current preparation node exceeds 80 degrees celsius, the pre-warning buffer time is set to 30 seconds, when the temperature of the preparation node exceeds 80 degrees celsius and the pre-warning buffer time reaches 30 seconds, the pre-warning rule to be called is considered to be satisfied, and the pre-warning can be performed, but when the pre-warning buffer time is 29 seconds, the temperature of the preparation node falls back to below 80 degrees celsius, the pre-warning rule to be called is considered not to be satisfied, and the pre-warning is not performed.

Specifically, after the equipment parameter early warning threshold and the feeding parameter early warning threshold are determined, an early warning judging function of each preparation node can be generated based on at least one of the two thresholds so as to monitor whether various tobacco shred processing parameters in the tobacco shred preparation process need to be subjected to sound early warning. The early warning judging function generally comprises an equipment parameter early warning threshold value, a charging parameter early warning threshold value and corresponding judging symbols. The early warning decision function may be set according to actual requirements, i.e. for each preparation node, the early warning decision functions of different preparation nodes are different. In addition, as the production requirements of different tobacco shred marks are different, the early warning judging functions corresponding to the different tobacco shred marks are slightly different for the same preparation node. Furthermore, in order to avoid false sound early warning caused by instantaneous tobacco shred processing parameter fluctuation in the tobacco shred preparation process, an early warning buffer time can be set for the early warning judging function. Starting with the current tobacco shred processing parameters meeting the early warning judging function for the first time, and continuously meeting the shortest time of the conditions until the actual triggering sound early warning. Based on the method, the situation that the transient and non-persistent tobacco shred processing parameters meet the early warning judging function can be guaranteed to have certain tolerance, and the frequency and the sensitivity of sound early warning can be controlled. Furthermore, the early warning judging function and the early warning buffer time can be integrated, and corresponding early warning rules to be called are set for each preparation node of each tobacco shred mark, so that whether sound early warning is carried out or not can be judged based on the early warning rules to be called later, and production management staff can be helped to find potential problems in time and take corresponding measures.

Optionally, after determining the pre-warning rule to be invoked, the method further includes: verifying the early warning rule to be called, and determining a verification result; and if the verification result is that the verification is not passed, adjusting at least one of the early warning rule function and the early warning buffer time in the early warning rule to be called until the verification result is that the verification is passed.

In order to ensure the accuracy and applicability of the pre-warning rule to be called, verification processing is required to be performed on the pre-warning rule to be called. The verification result can be obtained by logically checking the early warning judging function and the early warning buffer time when the tobacco shred processing parameters meet the early warning rule to be called. That is, the verification result is used for evaluating whether the current pre-warning rule to be called meets the requirement of actual tobacco shred preparation.

Specifically, in the tobacco shred preparation process, the early warning rule to be invoked is verified, namely, under the current tobacco shred processing parameters, whether the early warning judging function and the early warning buffer time are matched with the actual production condition or not is checked, and a corresponding verification result is obtained. If the verification result is that the verification is not passed, at least one of an early warning rule function and an early warning buffer time in the early warning rule to be called is required to be adjusted, for example, logic in an early warning judging function is modified, a device parameter early warning threshold and/or a feeding parameter early warning threshold are adjusted, the early warning buffer time is adjusted, and the like. After the pre-warning rule to be called is adjusted and optimized, the adjusted pre-warning rule to be called can be verified again until the verification result is verification passing. Based on the method, the to-be-called early warning rule can be ensured to accurately and reliably trigger the sound early warning in the tobacco shred preparation process.

And S130, when the tobacco shred processing parameters meet the target early warning rules, early warning information is generated based on the target early warning rules, and the early warning information is sent to a target early warning terminal for voice early warning.

The early warning information can be automatically generated warning information for notifying related personnel when the tobacco shred processing parameters are detected to meet the target early warning rules. Optionally, the early warning information may include a preparation node involved in early warning, a problem existing in the preparation node, a time when early warning occurs, a measure recommended to be taken, and the like.

Specifically, when the tobacco shred processing parameters meet the target early warning rules, information needing early warning, namely early warning information, can be generated according to the target early warning rules. Furthermore, the early warning information is sent to the target early warning terminal, and the sound early warning is realized according to the corresponding application program of the target early warning terminal, so that after receiving the sound early warning prompt, relevant production personnel can timely process corresponding preparation nodes.

According to the technical scheme, current tobacco shred processing parameters corresponding to tobacco shreds at different preparation nodes are obtained in the tobacco shred preparation process, the to-be-called early warning rule is determined according to the preparation nodes and tobacco shred brands of the tobacco shreds, the to-be-called early warning rule is used as a target early warning rule, further, when the tobacco shred processing parameters meet the target early warning rule, early warning information is generated based on the target early warning rule, and the early warning information is sent to a target early warning terminal to perform voice early warning. The method solves the problem that the prior art cannot realize real-time early warning and reminding according to production change in the tobacco shred preparation process, achieves the effect of real-time rapid early warning on each preparation node in the tobacco shred preparation process, ensures the comprehensiveness and accuracy of early warning information, and improves the early warning processing efficiency.

Example two

Fig. 2 is a flowchart of a sound early warning processing method according to an embodiment of the present invention, and this embodiment is a preferred embodiment of the foregoing embodiments. The specific implementation manner can be seen in the technical scheme of the embodiment. Wherein, the technical terms identical to or corresponding to the above embodiments are not repeated herein. As shown in fig. 2, the method includes:

s210, acquiring current tobacco shred processing parameters corresponding to different preparation nodes of tobacco shreds in the tobacco shred preparation process, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current tobacco shred feeding parameters.

By taking the current preparation node as the A-brand tobacco shred pre-filling in the vacuum conditioning stage as an example, whether tobacco is pre-filled in time can be detected at the current preparation node, wherein tobacco shred processing parameters can comprise parameter data such as the cumulative amount of the vacuum conditioning electronic scale, the cumulative amount of the electronic scale before loosening conditioning, the flow of the electronic scale before loosening conditioning, whether the loosening conditioning scale operates normally or not, and the like.

S220, determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule.

For example, in combination with the above example, when it is determined that the current preparation node is a vacuum conditioning tobacco leaf pre-filling node and the tobacco shred license plate is a brand, a target pre-warning rule conforming to the preparation node and the tobacco shred license plate may be selected from a plurality of to-be-called pre-warning rules, where the target pre-warning rule may be "tobacco shred license plate=a brand and vacuum conditioning electronic scale accumulation amount <10kg and loosening conditioning electronic scale accumulation amount >5800kg and loosening conditioning electronic scale flow amount >0kg/h and pre-warning buffer time is 30s".

And S230, when the tobacco shred processing parameters meet the target early warning rules, determining a target early warning level corresponding to the output result based on the output result corresponding to the target early warning rules and a preset early warning level range.

The output result may be a result generated by inputting the tobacco shred processing parameter into the target early warning rule, for example, the output result may be one or more parameter data, device state information, or descriptions of abnormal situations. The early warning grade range can be a grade range determined according to practical experience or industry standards and used for distinguishing early warning of different degrees. For example, the alert level range may include multiple levels of alert levels, such as "low," medium, "or" high. Each pre-warning level corresponds to a different parameter data range or risk level.

Specifically, when it is determined that the tobacco shred processing parameters meet the target early warning rules, an output result corresponding to the target early warning rules can be matched with a preset early warning level range, so that a target early warning level corresponding to the output result can be determined according to the matching result. For example, if the output result falls within the "low" risk range, the target early warning level is "low", if the early warning level range is set to be the first early warning level, the second early warning level and the third early warning level, and if the output result falls within the data range corresponding to the third early warning level, the target early warning level is the third early warning level.

By way of example, in combination with the above example, when the tobacco shred brand is the cut tobacco of the brand a, and the loosening and conditioning scale is running, that is, the flow of the electronic scale before loosening and conditioning is greater than 0kg/h, the accumulated amount of the loosening and conditioning scale is greater than 5800kg, and the accumulated amount of the vacuum conditioning scale is less than 10kg, that is, the scale is not pre-filled with tobacco leaves at this time, and the early warning buffer time reaches 30s, at this time, the tobacco shred processing parameters are considered to reach the target early warning rule, then the target early warning grade corresponding to the current preparation node can be determined to be the second early warning grade according to the corresponding output result.

S240, based on the target early warning level, determining an early warning state corresponding to the output result, wherein the early warning state comprises real-time early warning and delay early warning.

The early warning state can be an early warning broadcasting state set according to the target early warning level. For example, if the target early warning level is the first early warning level, the early warning state is real-time early warning; if the target early warning level is the second early warning level, the early warning state can be delayed early warning, for example, the early warning is performed after five minutes of delay; if the target early warning level is the third early warning level, the early warning state can also be delayed early warning, for example, delayed for ten minutes and then early warning is performed.

Specifically, according to the target early warning level corresponding to the output result, the early warning state corresponding to the current output result is determined, so that voice early warning is performed based on the early warning state.

S250, generating early warning information based on the early warning state, the target early warning level and the output result.

Specifically, early warning information corresponding to the current preparation node is generated according to the early warning state, the target early warning level and the output result corresponding to the current preparation node, wherein the early warning information can comprise problems, early warning occurrence time, the target early warning level, suggested measures and the like of the current preparation node.

And S260, sending the early warning information to a target early warning terminal for voice early warning.

Specifically, after receiving the early warning information corresponding to the current preparation node, the early warning information can be sent to the target early warning terminal to carry out sound early warning, wherein the target early warning terminal can control the early warning broadcaster corresponding to the preparation node to carry out sound early warning, so that the pertinence of the sound early warning is improved, and related production personnel can conveniently and rapidly process based on sound early warning prompt.

In addition, when each time of sound early warning is carried out, corresponding early warning voice is generated according to the early warning information, so that sound early warning is carried out based on the early warning voice. After generating the plurality of early warning voices, the plurality of early warning voices may be divided for facilitating subsequent retrieval or analysis, for example, the early warning voices may be divided according to production areas corresponding to the preparation nodes, and different production areas correspond to different numbers of early warning voice strips, see table 1 below.

Production area category	Number of pre-alarm voices
		96 Line blade area	38
96 Line blade charging area	18
		96 Thread cut tobacco region	81
64 Line blade area	17
		64 Blade charging area	16
64 Thread cut tobacco region	66
		Cut stem region	3
Expansion line blade area	2
		Thread-expanding cut tobacco region	2

Or, the early warning voice strips can be divided according to specific early warning types, for example, 1) early warning of material shortage or material blockage in the wire making process, such as insufficient feeding of a feeding machine, material blockage of a quantitative tube and the like; 2) Early warning of operation types in the tobacco transferring process, such as early warning voice for prompting the tobacco storing cabinet to output, tobacco drying and feeding, stem expansion and tobacco returning, and the like; 3) Early warning of material circulation in the navigation starting and tailing stage, such as early warning voice that cut tobacco reaches a winnowing scale, a flavoring machine starts to spray materials, main cut tobacco scales are empty and the like; 4) And alarming for abnormal operation of the prompting equipment. If the flap door is not closed, the outlet conveyer belt is in a reverse rotation state, the feeder is not switched into a pre-filling state, and the like.

Optionally, the method further comprises: based on the tobacco shred processing parameters and the early warning information, an early warning report is generated and displayed at a target early warning terminal.

The early warning report may include early warning information such as a production area, an early warning level, an early warning occurrence time and the like corresponding to the current preparation node, and a tobacco shred processing parameter corresponding to triggering the early warning.

Specifically, after the voice early warning is performed, tobacco shred processing parameters corresponding to the current preparation node and early warning information can be integrated, a corresponding early warning report is generated, and the corresponding early warning report is displayed based on the target early warning terminal.

In addition, each time when the early warning is triggered, corresponding early warning information is transmitted to the target early warning terminal and an early warning report is generated. Then, in order to facilitate the statistics and analysis of the early warning information by the production personnel, the real-time early warning information can be counted and formed into a table to be displayed on the target early warning terminal; and counting the historical early warning information and forming a corresponding table for display. Or, the real-time early warning information is subjected to statistics arrangement and display only aiming at the early warning information of the current charging parameters.

It should be further noted that, when the target early warning rule is triggered each time, whether to query the sound early warning event consistent with the target early warning rule in the history early warning information can be selected according to the early warning level corresponding to the target early warning rule and the actual requirement, so as to solve the early warning problem corresponding to the preparation node more perfectly.

According to the technical scheme, current tobacco shred processing parameters corresponding to tobacco shreds at different preparation nodes are obtained in the tobacco shred preparation process, the pre-warning rules to be called are determined according to the preparation nodes and tobacco shred brands of the tobacco shreds, and the pre-warning rules to be called are used as target pre-warning rules. Further, when the tobacco shred processing parameters meet the target early warning rules, determining the target early warning level corresponding to the output result based on the output result corresponding to the target early warning rules and a preset early warning level range. The method comprises the steps of determining the early warning state corresponding to the output result according to the target early warning level, generating early warning information according to the early warning state, the target early warning level and the output result, sending the early warning information to a target early warning terminal for voice early warning, solving the problem that the prior art cannot realize real-time early warning reminding according to the production change in the tobacco shred preparation process, achieving the effect of real-time quick early warning on each preparation node in the tobacco shred preparation process, and determining the target early warning level and the early warning state corresponding to the output result of the target early warning rule, so that voice early warning is more targeted and accurate, and flexibility and efficiency of voice early warning are guaranteed.

Example III

Fig. 3 is a schematic structural diagram of a sound early warning processing device according to an embodiment of the present invention. As shown in fig. 3, the apparatus includes: a parameter acquisition module 310, a target early warning rule determination module 320, and a sound early warning module 330.

The parameter obtaining module 310 is configured to obtain current tobacco shred processing parameters corresponding to different preparation nodes of the tobacco shreds in a tobacco shred preparation process, where the tobacco shred processing parameters include current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds; the target early warning rule determining module 320 is configured to determine an early warning rule to be invoked according to the preparation node and the tobacco number of the tobacco, and take the early warning rule to be invoked as a target early warning rule; and the sound early-warning module 330 is used for generating early-warning information based on the target early-warning rule when the tobacco shred processing parameters meet the target early-warning rule, and sending the early-warning information to the target early-warning terminal for sound early-warning.

According to the technical scheme, current tobacco shred processing parameters corresponding to tobacco shreds at different preparation nodes are obtained in the tobacco shred preparation process, the to-be-called early warning rule is determined according to the preparation nodes and tobacco shred brands of the tobacco shreds, the to-be-called early warning rule is used as a target early warning rule, further, when the tobacco shred processing parameters meet the target early warning rule, early warning information is generated based on the target early warning rule, and the early warning information is sent to a target early warning terminal to perform voice early warning. The method solves the problem that the prior art cannot realize real-time early warning and reminding according to production change in the tobacco shred preparation process, achieves the effect of real-time rapid early warning on each preparation node in the tobacco shred preparation process, ensures the comprehensiveness and accuracy of early warning information, and improves the early warning processing efficiency.

On the basis of the above embodiment, optionally, the apparatus further includes a device parameter early warning threshold determining module, where the module includes: the historical tobacco shred processing system comprises a historical parameter acquisition unit, a processing unit and a processing unit, wherein the historical parameter acquisition unit is used for acquiring historical tobacco shred processing parameters corresponding to different tobacco shred brands at each preparation node, and the historical tobacco shred processing parameters comprise historical equipment operation parameters and historical charging parameters corresponding to each preparation node; the statistical result determining module is used for carrying out statistical analysis on the tobacco shred of each tobacco shred grade and the historical equipment operation parameters corresponding to each preparation node of the current tobacco shred grade to obtain a statistical result corresponding to each preparation node, wherein the statistical result comprises at least one of the mean value, the extreme value and the variance of the historical equipment operation parameters under at least one reference field; the equipment parameter early warning threshold determining unit is used for determining equipment parameter early warning thresholds corresponding to all preparation nodes based on statistical results; the data determining unit is used for taking the equipment parameter early warning threshold value as one item of data in the early warning rule to be called.

Optionally, the apparatus further includes a feeding parameter early warning threshold determining module, which includes: the initial early warning value determining unit is used for carrying out statistical analysis on historical charging parameters corresponding to all preparation nodes of the current tobacco shred marks for tobacco shreds of all tobacco shred marks to determine initial parameter early warning values corresponding to all preparation nodes; the early warning value adjusting unit is used for adjusting the initial parameter early warning value based on the historical charging parameters and the environmental parameters to obtain charging parameter early warning threshold values corresponding to all the preparation nodes; the charging parameter early warning threshold value comprises an initial parameter early warning value and a parameter adjusting value; the data setting unit is used for taking the feeding parameter early warning threshold value as one item of data in the early warning rule to be called.

Optionally, the device further includes a module for determining the pre-warning rule to be invoked, and the module includes: the judging function determining unit is used for determining an early warning judging function based on at least one of the equipment parameter early warning threshold value and the feeding parameter early warning threshold value, wherein the early warning judging function comprises the equipment parameter early warning threshold value and/or the feeding parameter early warning threshold value and corresponding judging symbols; the buffer time setting unit is used for setting early warning buffer time for the early warning judging function, wherein the early warning buffer time is the duration time when the early warning judging function is met; and the early warning rule determining unit is used for determining the early warning rules to be adjusted corresponding to the tobacco shred marks at different preparation nodes based on the early warning judging function and the early warning buffering time, wherein the early warning rules to be adjusted corresponding to the different tobacco shred marks are different.

Optionally, after the early warning rule determining module is to be invoked, a rule verifying module is further included, where the module includes: the verification result determining unit is used for performing verification processing on the early warning rule to be called and determining a verification result; and the rule adjusting unit is used for adjusting at least one of the early warning rule function and the early warning buffer time in the early warning rule to be called if the verification result is that the verification is not passed, until the verification result is that the verification is passed.

Optionally, the sound early warning module includes: the early warning grade determining unit is used for determining a target early warning grade corresponding to the output result based on the output result corresponding to the target early warning rule and a preset early warning grade range; the early warning state determining unit is used for determining an early warning state corresponding to the output result based on the target early warning level, wherein the early warning state comprises real-time early warning and delay early warning; and the early warning information determining unit is used for generating early warning information based on the early warning state, the target early warning level and the output result.

Optionally, the device further comprises an early warning report display module, wherein the early warning report display module is used for generating an early warning report based on tobacco shred processing parameters and early warning information and displaying the early warning report at the target early warning terminal.

The voice early warning processing device provided by the embodiment of the invention can execute the voice early warning processing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

Example IV

Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.

As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the voice pre-warning processing method.

In some embodiments, the acoustic warning processing method may be implemented as a computer program tangibly embodied on a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the acoustic warning processing method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the acoustic pre-warning processing method in any other suitable way (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

The computer program for implementing the acoustic pre-warning processing method of the present invention can be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

Example five

The embodiment of the invention also provides a computer readable storage medium, the computer readable storage medium stores computer instructions, the computer instructions are used for making a processor execute a sound early warning processing method, the method comprises:

In the tobacco shred preparation process, current tobacco shred processing parameters corresponding to different preparation nodes of the tobacco shreds are obtained, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds; determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule; when the tobacco shred processing parameters meet the target early warning rules, early warning information is generated based on the target early warning rules, and the early warning information is sent to a target early warning terminal for voice early warning.

In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present invention may be performed in parallel, sequentially, or in a different order, so long as the desired results of the technical solution of the present invention are achieved, and the present invention is not limited herein.

The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.

Claims (10)

1. The sound early warning processing method is characterized by comprising the following steps of:

in the tobacco shred preparation process, current tobacco shred processing parameters corresponding to different preparation nodes of tobacco shreds are obtained, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds;

Determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule;

When the tobacco shred processing parameters meet the target early warning rules, early warning information is generated based on the target early warning rules, and the early warning information is sent to a target early warning terminal for voice early warning.

2. The method as recited in claim 1, further comprising:

Acquiring historical tobacco shred processing parameters corresponding to different tobacco shred brands at each preparation node, wherein the historical tobacco shred processing parameters comprise historical equipment operation parameters and historical charging parameters corresponding to each preparation node;

carrying out statistical analysis on historical equipment operation parameters corresponding to each preparation node of the current tobacco shred mark for tobacco shreds of each tobacco shred mark to obtain a statistical result corresponding to each preparation node, wherein the statistical result comprises at least one of a mean value, an extreme value and a variance of the historical equipment operation parameters under at least one reference field;

Determining equipment parameter early warning thresholds corresponding to the preparation nodes based on the statistical results;

and taking the equipment parameter early warning threshold value as one item of data in the early warning rule to be called.

3. The method according to claim 1, wherein the method further comprises:

for tobacco shreds of each tobacco shred mark, carrying out statistical analysis on historical charging parameters corresponding to each preparation node of the current tobacco shred mark, and determining initial parameter early warning values corresponding to each preparation node;

Based on the historical charging parameters and the environmental parameters, adjusting the initial parameter early-warning values to obtain charging parameter early-warning thresholds corresponding to the preparation nodes; the charging parameter early warning threshold value comprises the initial parameter early warning value and a parameter adjusting value;

and taking the feeding parameter early warning threshold value as one item of data in the early warning rule to be called.

4. The method according to claim 1, wherein the method further comprises:

Determining an early warning judging function based on at least one of a device parameter early warning threshold and a charging parameter early warning threshold, wherein the early warning judging function comprises the device parameter early warning threshold and/or the charging parameter early warning threshold and corresponding judging symbols;

setting early warning buffer time for the early warning judging function, wherein the early warning buffer time is the duration time when the early warning judging function is met;

And determining the pre-warning rules to be adjusted corresponding to the tobacco shred marks at different preparation nodes based on the pre-warning judging function and the pre-warning buffer time, wherein the pre-warning rules to be adjusted corresponding to the different tobacco shred marks are different.

5. The method of claim 4, further comprising, after determining the pre-warning rule to be invoked:

performing verification processing on the pre-warning rule to be called, and determining a verification result;

And if the verification result is that the verification is not passed, adjusting at least one of the early warning rule function and the early warning buffer time in the early warning rule to be called until the verification result is that the verification is passed.

6. The method of claim 1, wherein the generating pre-warning information based on the target pre-warning rule comprises:

Determining a target early warning level corresponding to the output result based on the output result corresponding to the target early warning rule and a preset early warning level range;

based on the target early warning level, determining an early warning state corresponding to the output result, wherein the early warning state comprises real-time early warning and delay early warning;

And generating early warning information based on the early warning state, the target early warning level and the output result.

7. The method as recited in claim 1, further comprising:

And generating an early warning report based on the tobacco shred processing parameters and the early warning information, and displaying the early warning report at the target early warning terminal.

8. A sound warning processing apparatus, comprising:

The parameter acquisition module is used for acquiring current tobacco shred processing parameters corresponding to different preparation nodes of the tobacco shreds in the tobacco shred preparation process, wherein the tobacco shred processing parameters comprise current equipment operation parameters during tobacco shred processing and current feeding parameters of the tobacco shreds;

The target early warning rule determining module is used for determining an early warning rule to be called according to the preparation node and the tobacco shred marks of the tobacco shreds, and taking the early warning rule to be called as a target early warning rule;

And the sound early warning module is used for generating early warning information based on the target early warning rule when the tobacco shred processing parameters meet the target early warning rule, and sending the early warning information to a target early warning terminal for sound early warning.

9. An electronic device, the electronic device comprising:

at least one processor; and

A memory communicatively coupled to the at least one processor; wherein,

The memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the acoustic pre-warning processing method of any one of claims 1-7.

10. A computer readable storage medium storing computer instructions for causing a processor to perform the acoustic early warning processing method of any one of claims 1 to 7.