CN-121998508-A - Cement electric pole production quality control and detection system

CN121998508ACN 121998508 ACN121998508 ACN 121998508ACN-121998508-A

Abstract

The invention provides a cement electric pole production quality control and detection system, which realizes accurate data acquisition, scientific outlier processing and dynamic iterative optimization, and comprises a parameter acquisition module, a quality detection module, an intelligent decision regulation module, an execution feedback module and a parameter regulation module, wherein the parameter acquisition module acquires and preprocesses key technological parameters, the quality detection module judges and eliminates abnormal parameters in the preprocessed key technological parameters, and then calculates a production procedure qualification index in combination with preset parameter weights, the intelligent decision regulation module determines the adjustment quantity of each key technological parameter based on the production procedure qualification index and a preset quality standard threshold value, and outputs a targeted production equipment parameter adjustment instruction, the execution feedback module finishes the key technological parameter correction according to the parameter adjustment instruction, evaluates the parameter adjustment effect, stores the corresponding adjustment parameters as an optimization template if the adjustment effect is up to standard, and if the adjustment effect is not up to standard, feeds back the evaluation result to trigger secondary adjustment, and simultaneously synchronizes to the parameter acquisition module to realize closed loop iteration.

Inventors

WU JIANYI
CHEN JUNSHAO
CHEN LONGHUI
FANG BAOPING

Assignees

台山市俊强电力电信器材有限公司

Dates

Publication Date: 20260508
Application Date: 20260128

Claims (8)

1. A cement pole production quality control and detecting system is characterized by comprising: the parameter acquisition module acquires and preprocesses key process parameters; The quality detection module judges and eliminates abnormal parameters in the pretreated key process parameters, and calculates the qualification index of the production process by combining with preset parameter weights; the intelligent decision-making regulation and control module is used for comparing the qualification index of the production process with a preset quality standard threshold value, determining the adjustment quantity of each key process parameter according to a comparison result and outputting a targeted production equipment parameter adjustment instruction; The parameter adjustment module is used for carrying out key process parameter correction according to the parameter adjustment instruction, evaluating the parameter adjustment effect, storing the corresponding adjustment parameter as an optimization template if the adjustment effect meets the standard, and carrying out secondary adjustment triggered by the evaluation result feedback if the adjustment effect does not meet the standard, and synchronously synchronizing the evaluation result to the parameter acquisition module to realize closed loop iteration.
2. The system of claim 1, wherein the key process parameters include raw material proportioning parameters, stirring process parameters, forming pressure parameters, maintenance temperature and humidity parameters and finished product size parameters, and the pretreatment includes de-duplication treatment, complement of missing values, uniform format, physical boundary check and standardization treatment.
3. The system of claim 2, wherein the pre-processed key process parameters are grouped to obtain sub-data sets corresponding one-to-one to each type of parameters; According to the sample size of each sub-data set, combining sample size dividing standards, selecting an adaptive normal inspection method according to different sample types, wherein raw material proportioning parameters and finished product size parameters belong to small samples, adapting to shape-Wilk inspection, stirring process parameters, forming pressure parameters and maintenance temperature and humidity parameters belong to medium samples, adapting to Kolmogorov-Smirnov inspection, removing abnormal values for parameters conforming to normal distribution by using Laida criteria, and removing abnormal values for parameters of non-normal distribution by using a four-bit distance method.
4. The system of claim 3, wherein the rada criterion is formulated as: Wherein, the Representing parameters acquired by the kth type parameters at the time t; representing a normalized mean value of the kth class of parameters; A normalized standard deviation representing a kth class of parameters; If the parameter values are met, marking the parameter values as abnormal values, removing the abnormal values, and forming an effective sub-data set by the effective data reserved by each type of parameters after removing the abnormal values; The method comprises the steps of sorting and de-duplicating a target parameter sub-data set by using a quartile range method, calculating a first quartile, a third quartile and a quartile range by using a linear interpolation method, setting an abnormal value boundary according to parameter importance, comparing the sorted data with the boundary, identifying abnormal values out of range, verifying by combining production conditions, removing after confirmation, and forming an effective sub-data set by using effective data reserved by each type of parameters after removal; Calculating the ratio of the number of samples meeting the preset threshold of the process standard to the total number of effective samples for each type of effective sub-data set to obtain the qualification rate of the type of parameters; Calculating the qualification index of the production process, wherein the formula is as follows: Wherein, the Representing the parameter weight; representing the qualification index of the production process; and k represents the k-th class parameter.
5. The system of claim 4, wherein the multiplier for the outlier boundary is linearly mapped by the formula: Wherein, the Representing a base boundary multiplier; representing the maximum weight value in all key process parameters; m represents an outlier boundary multiplier; the qualification index of the production process and a preset quality standard threshold value For comparison, if Judging that the production process is in stable qualified state, if so Judging that the quality of the working procedure does not reach the standard, and triggering a parameter adjustment flow; calculating the adjustment quantity of the k-type parameter, wherein the formula is as follows: Wherein, the Representing the adjustment amount of the k-th type parameter; an adjustment sensitivity coefficient representing a kth class parameter; Representing the process standard value of the k-th type parameter; Mean value of k-th parameters; according to the adjustment amount of the k-th type parameter Generating a targeted production equipment parameter adjustment instruction, and synchronously generating a structured traceability carrier; The structured traceability carrier is a structured matrix of 5 rows and 4 columns, and each row corresponds to an adjustment record of a key process parameter, and comprises 4 core fields including parameter types, adjustment amounts, corresponding equipment and production batches.
6. The system of claim 5, wherein the adjusted key process parameters are collected and preprocessed, outliers are removed, and the adjusted process pass index is calculated in combination with the preset weights ; Calculating an effect evaluation value, wherein the formula is as follows: Wherein, the An effect evaluation value is represented; Evaluation value of effect And preset optimization threshold In contrast, two types of decisions are triggered: If it is The adjustment effect reaches the standard, and the parameter category is identified and the adjustment amount is adjusted And adjusting the sensitivity coefficient Storing the quality fluctuation as a reusable optimizing template, and directly calling the optimizing template when the quality fluctuation of the subsequent similar type occurs; If it is And synchronizing the effect evaluation value E and the adjusted key process parameters to an intelligent decision regulation module, triggering a secondary adjustment flow, simultaneously sending a parameter monitoring priority updating instruction to a parameter acquisition module, and improving the acquisition frequency of the parameters with the unqualified effect.
7. The system of claim 6, wherein the iterative mechanism of the optimization template is configured in a dual-drive manner by periodic triggering and event triggering; The trigger event scene of the event trigger is as follows: 1) After the template is continuously called for 3 times, the effect evaluation value is adjusted ; 2) Spot check or self-check finds that the quality index of the electric pole in a certain batch does not reach the standard, and the problem root is related to the stored optimization template; 3) The production conditions are changed.
8. The system of claim 7, wherein the optimization template iteration procedure is as follows: 1) Calculating the attenuation rate of the template effect, wherein the formula is as follows: d represents the attenuation rate of the template effect; an adjustment effect evaluation value indicating when the template is stored for the first time; Representing the average value of the effect evaluation values invoked in 1 month; If it is Judging that the template effect is obviously attenuated and the full iteration is needed to be carried out, if Only local parameter correction is needed; 2) Updating production characteristics, namely acquiring new production data after triggering iteration, and updating characteristic dimensions associated with a template; 3) Adjusting the sensitivity coefficient, and correcting according to the parameter weight ratio of the new data; 4) The new template after iteration is subjected to trial production link, the new template is called to generate an adjustment instruction, key technological parameters of trial production products are collected, and the adjusted qualification index is calculated If (1) And is also provided with If the verification is not passed, returning to a production feature updating link, supplementing missing features or adjusting model parameters until the verification is passed.

Description

Cement electric pole production quality control and detection system Technical Field The invention relates to the technical field of cement electric pole production processes, in particular to a cement electric pole production quality control and detection system. Background With the promotion of 5G base station construction, novel power system upgrading and rural power grid consolidation and promotion engineering, the performance requirements of the market on the cement electric pole are continuously upgraded, not only are the severe working condition requirements of high strength, corrosion resistance, wind load resistance and the like met, but also higher standards are provided for product consistency, production efficiency and green low-carbon properties; the method comprises the steps of firstly, coarsely controlling process parameters, insufficiently controlling automation and precision, controlling core processes by most small and medium-sized production enterprises in industry, wherein the core processes still depend on manual experience, the control of key parameters is lack of standardized means, so that performance fluctuation of the same batch or even the same electric pole is obvious, secondly, data processing and abnormal value identification capability is weak, quality detection is lagged and precision is low, in traditional production, acquisition of key process parameters depends on manual inspection or low-frequency sensor recording, data integrity is insufficient and an effective pretreatment mechanism is lacked, meanwhile, quality detection is mostly dependent on offline sampling inspection or manual visual inspection, efficiency is low, production complete flows are difficult to cover, unqualified products are found after flowing into markets, and accordingly, rework cost is increased and safety risks are exposed, meanwhile, the production processes are lack of complete closed loops from acquisition, detection, decision making and feedback to iteration, adjustment effects cannot be verified in real time, technological parameters and an optimization template are statically arranged for a long time, raw material batch, equipment ageing, production environment change and other dynamic factors are difficult to adapt, quality stability of products is poor, and in conclusion, the existing cement electric pole production technology is difficult to accurately control, and the quality control is difficult to be subjected to complete, and the dynamic control is required to be subjected to complete, and the quality control is high, and the quality is obviously and high in a closed loop. Disclosure of Invention In order to solve the technical problems mentioned in the background art at present, the invention aims to provide a cement electric pole production quality control and detection system. In order to achieve the above purpose, the present invention adopts the following technical scheme: a cement pole production quality control and detection system, comprising: the parameter acquisition module acquires and preprocesses key process parameters; The quality detection module judges and eliminates abnormal parameters in the pretreated key process parameters, and calculates the qualification index of the production process by combining with preset parameter weights; the intelligent decision-making regulation and control module is used for comparing the qualification index of the production process with a preset quality standard threshold value, determining the adjustment quantity of each key process parameter according to a comparison result and outputting a targeted production equipment parameter adjustment instruction; The parameter adjustment module is used for carrying out key process parameter correction according to the parameter adjustment instruction, evaluating the parameter adjustment effect, storing the corresponding adjustment parameter as an optimization template if the adjustment effect meets the standard, and carrying out secondary adjustment triggered by the evaluation result feedback if the adjustment effect does not meet the standard, and synchronously synchronizing the evaluation result to the parameter acquisition module to realize closed loop iteration. Further, the key technological parameters comprise raw material proportioning parameters, stirring technological parameters, forming pressure parameters, maintenance temperature and humidity parameters and finished product size parameters, and the pretreatment comprises duplication removal treatment, deletion value complementation, uniform format, physical boundary verification and standardization treatment. Further, the key process parameters after pretreatment are grouped to obtain sub-data sets corresponding to each type of parameters one by one; According to the sample size of each sub-data set, combining sample size dividing standards, selecting an adaptive normal inspection method according to different sample types, wherei