An industrial equipment monitoring management system and method based on a cloud management platform

Abstract

The application discloses an industrial equipment monitoring management system and method based on a cloud management platform, relates to the technical field of industrial equipment, and comprises a wastewater treatment equipment monitoring module, a wastewater treatment equipment prediction module, a wastewater treatment equipment mode confirmation module, a management terminal and a data warehouse. The application predicts the monitoring parameters and wastewater pollution indexes of a plurality of wastewater treatment equipment in an industrial park, accurately predicts the pollutant index set, and provides solid data support for the correction of the monitoring frequency or data acquisition time interval of the related sensors of the pollutant index set when real-time monitoring of the current production of the industrial park is carried out subsequently, reduces the data redundancy, and improves the efficiency of data monitoring processing. While ensuring the treatment effect of the wastewater treatment equipment and maintaining the service life of the wastewater treatment equipment, the application also saves the resource consumption of the wastewater treatment equipment, avoids over-treatment, and avoids resource waste.

Description

Technical Field

[0001] This invention relates to the field of industrial equipment technology, and specifically to an industrial equipment monitoring and management system and method based on a cloud management platform. Background Technology

[0002] Industrial equipment, as a core component of industrial production, often possesses complex structures and a high degree of automation. Its stable operation directly impacts the efficiency and effectiveness of the entire production line. Real-time monitoring of industrial equipment allows for the timely detection of potential malfunctions. With the deepening of environmental protection and sustainable development concepts, the efficiency of wastewater treatment equipment has received widespread attention. Direct discharge of untreated or substandard wastewater can cause serious pollution to aquatic environments. Harmful substances in wastewater can damage aquatic ecosystems and affect the quality and availability of water resources; therefore, monitoring and managing wastewater treatment equipment is extremely necessary.

[0003] Existing technology, such as the invention application patent with publication number CN109336199B, discloses a real-time monitoring method and system for wastewater treatment. This method includes: acquiring the geographical location information, wastewater pipeline information, wastewater treatment equipment parameters, and real-time data of each wastewater treatment station; classifying, storing, and displaying the real-time data of the wastewater treatment equipment at each station; determining the production and operation status based on the wastewater flow rate and / or production operation data of the wastewater treatment equipment; determining the equipment maintenance status based on the wastewater treatment equipment parameters and production operation plan data of the wastewater treatment station; determining the equipment maintenance method based on the production and operation status and / or equipment maintenance status; and displaying the production and operation status, equipment maintenance status, and determined equipment maintenance method of the wastewater treatment equipment at each station. This invention achieves effective monitoring of the production and treatment processes of wastewater treatment stations and timely maintenance of faulty equipment, thus improving the efficiency of wastewater treatment monitoring.

[0004] Existing technologies, such as the invention patent application CN118505435B, disclose an intelligent wastewater treatment method and system, relating to the field of wastewater treatment technology. This includes dividing wastewater treatment areas, collecting wastewater treatment data from each area, and analyzing and predicting water quality data; initially adjusting wastewater treatment parameters in each area based on the analysis results; and automatically adjusting the wastewater treatment parameters of the area to be optimized based on a comparison of the wastewater treatment performance of different areas after the initial adjustment. This invention, by dividing wastewater treatment areas, collecting wastewater treatment data, analyzing and predicting water quality data, formulating initial adjustment measures based on the results, and further adjusting wastewater treatment measures based on a comparison of wastewater treatment data from standard areas and areas to be optimized, and by collecting energy generated during the wastewater treatment process in real time for energy self-supply of the wastewater treatment equipment, achieves dynamic optimization of the wastewater treatment process, improves wastewater treatment efficiency and energy utilization efficiency, reduces operating costs of the wastewater treatment process, and reduces environmental pollution.

[0005] Based on the above solutions, it can be found that existing technologies rarely address prior and projected production information for industrial parks, thus failing to predict monitoring parameters and pollutant indicators for wastewater treatment equipment. This makes it difficult to adjust the monitoring frequency or data acquisition interval of relevant sensors for pollutant indicators when conducting real-time monitoring of current production in industrial parks, increasing data redundancy and reducing data monitoring and processing efficiency. Furthermore, there is a lack of regulation of the operating modes of wastewater treatment equipment. On the one hand, it is difficult to ensure the treatment efficiency of wastewater treatment equipment while conserving its resources, easily leading to overtreatment and resource waste. On the other hand, it neglects whether the condition and treatment capacity of the wastewater treatment equipment itself can match the wastewater generated by production workshops within the industrial park, affecting equipment lifespan and reducing wastewater treatment effectiveness. Summary of the Invention

[0006] The purpose of this invention is to provide an industrial equipment monitoring and management system and method based on a cloud management platform, which solves the problems existing in the background technology.

[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The first aspect of the present invention provides an industrial equipment monitoring and management system based on a cloud management platform, including: a wastewater treatment equipment monitoring module, which adopts sensor fusion technology to monitor the routine operation data and processing data of several wastewater treatment equipment in an industrial park, and generates a set of routine operation data and processing data of several wastewater treatment equipment in the industrial park under time-series characteristics and uploads them to the cloud management platform.

[0008] The wastewater treatment equipment prediction module obtains prior production information and expected production information of the industrial park from the cloud management platform, predicts the monitoring parameters and wastewater pollution index of several wastewater treatment equipment in the industrial park, and uploads them to the cloud management platform.

[0009] The wastewater treatment equipment mode confirmation module determines the predicted operation mode of several wastewater treatment equipment in the industrial park based on the set of routine operation data and the set of treatment data under the wastewater pollution index and time-series characteristics of several wastewater treatment equipment in the industrial park. The operation mode includes routine mode, energy-saving mode, emergency mode and auxiliary mode.

[0010] The management terminal will adjust the operating mode of several wastewater treatment devices in the industrial park to a predictive operating mode.

[0011] The second aspect of the present invention provides a method for implementing the industrial equipment monitoring and management system described in the present invention, comprising: ST1, using sensor fusion technology to monitor the routine operation data and processing data of several wastewater treatment devices in an industrial park, and generating a set of routine operation data and processing data of several wastewater treatment devices in the industrial park under time-series characteristics and uploading it to a cloud management platform.

[0012] ST2. Predict the monitoring parameters and wastewater pollution index of several wastewater treatment equipment in the industrial park and upload them to the cloud management platform.

[0013] ST3. Determine the predicted operating modes of several wastewater treatment devices in the industrial park. The operating modes include normal mode, energy-saving mode, emergency mode and auxiliary mode.

[0014] ST4. Adjust the operating mode of several wastewater treatment devices in the industrial park to a predictive operating mode.

[0015] The beneficial effects of this invention are as follows: 1. This invention uses a wastewater treatment equipment prediction module based on the raw material set and pollutant water quality index set of each production workshop in an industrial park, combined with the expected raw material set of each production workshop in the industrial park, to predict the monitoring parameters and wastewater pollution index of several wastewater treatment equipment in the industrial park. After accurately predicting the pollutant index set, it provides solid data support for correcting the monitoring frequency or data acquisition time interval of relevant sensors for the pollutant index set when conducting real-time monitoring of the current production in the industrial park, reducing data redundancy and improving the efficiency of data monitoring and processing.

[0016] 2. This invention uses a wastewater treatment equipment mode confirmation module. Based on the regular operation and processing data of the wastewater treatment equipment, and taking into account the predicted pollution index of the wastewater treatment equipment, it considers whether the equipment's own condition and processing capacity can match the treatment of wastewater generated in the production workshops within the industrial park. This ensures the treatment effect of the wastewater treatment equipment, maintains its lifespan, saves on the equipment's resource consumption, avoids over-treatment, and prevents resource waste. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0019] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Reference Figure 1 As shown, the first aspect of the present invention provides an industrial equipment monitoring and management system based on a cloud management platform, including: a wastewater treatment equipment monitoring module, a wastewater treatment equipment prediction module, a wastewater treatment equipment mode confirmation module, a management terminal, and a data warehouse.

[0022] It should be noted that the wastewater treatment equipment monitoring module and the wastewater treatment equipment prediction module are both connected to the wastewater treatment equipment mode confirmation module. The wastewater treatment equipment mode confirmation module is connected to the management terminal. The data warehouse is connected to both the wastewater treatment equipment prediction module and the wastewater treatment equipment mode confirmation module.

[0023] The wastewater treatment equipment monitoring module uses sensor fusion technology to monitor the routine operation data and processing data of several wastewater treatment devices in the industrial park, and generates a set of routine operation data and processing data of several wastewater treatment devices in the industrial park under time-series characteristics, which is then uploaded to the cloud management platform.

[0024] It should be noted that the sensor fusion technology is used to monitor the routine operation and processing data of several wastewater treatment devices in the industrial park. Specific sensors include, for example, image acquisition devices, and COD, BOD, and SS sensors equipped on the wastewater treatment devices.

[0025] It should also be noted that the timing feature represents a processing cycle.

[0026] As a preferred embodiment, the routine operating data includes appearance images.

[0027] The processed data includes pre- and post-feature parameters of each polluted water quality indicator.

[0028] It should be noted that the pre- and post-characteristic parameters of the various polluted water quality indicators include, but are not limited to, parameters of polluted water quality such as chemical oxygen demand, biochemical oxygen demand, suspended solids, and pH before and after treatment by wastewater treatment equipment.

[0029] The wastewater treatment equipment prediction module obtains prior production information and expected production information of the industrial park from the cloud management platform, predicts the monitoring parameters and wastewater pollution index of several wastewater treatment equipment in the industrial park, and uploads them to the cloud management platform.

[0030] It should be noted that the prior production information of the industrial park includes the set of raw materials used in each historical processing of several production workshops, the set of polluting water quality indicators, and the amount of wastewater discharged.

[0031] It should be noted that the set of raw materials used in the prior production information of the industrial park can be obtained from the production plan. The set of pollutant water quality indicators is collected by installing sensors such as COD sensors, BOD sensors, and SS sensors at the drainage outlets of each production workshop. The wastewater discharge volume can be monitored by a flow meter.

[0032] As a preferred approach, the specific prediction method for the monitoring parameters and wastewater pollution index of several wastewater treatment equipment in the industrial park is as follows: extract the set of raw materials used in each historical processing of several production workshops and the set of pollutant water quality indicators from the prior production information of the industrial park, and combine them with the expected production information of the industrial park to determine the predicted pollutant indicator set of several production workshops in the industrial park, and predict the wastewater pollution index of several wastewater treatment equipment in the industrial park.

[0033] As a preferred approach, the method for determining the predicted pollutant index set of several production workshops in the industrial park is as follows: based on the set of raw materials used in each historical processing of each production workshop in the industrial park and the set of polluted water quality indicators, and extracting the set of raw materials expected to be used in each production workshop from the expected production information of the industrial park, first execute A1, and if A1 fails, then execute A2. The set of polluted water quality indicators includes the characteristic parameters of each polluted water quality indicator.

[0034] It should be noted that the polluted water quality indicators of each production workshop in the industrial park refer to the set of polluted water quality indicators monitored from the drainage outlets of each production workshop.

[0035] A1. By comparing and analyzing the historical processing data of each production workshop in the industrial park, we extract the pollutant water quality indicators from the set of pollutant water quality indicators of each historical processing data of each production workshop in the industrial park. We then map each pollutant water quality indicator to the corresponding historical processing data of each production workshop. We summarize the number of corresponding historical processing data of each pollutant water quality indicator and the total number of corresponding historical processing data of each production workshop. We divide the number of corresponding historical processing data of each pollutant water quality indicator by the total number of corresponding historical processing data of each production workshop to obtain the frequency of each pollutant water quality indicator. We then summarize the pollutant water quality indicators with frequencies higher than or equal to the preset reference frequencies into the predicted pollutant indicator set.

[0036] It should be noted that the comparative analysis obtains several reference historical processing data of each production workshop in the industrial park. The specific comparison method is as follows: several data in the expected raw material set of each production workshop in the industrial park are mapped and matched with several data in the raw material set of each historical processing. If all matches are successful, the first matching value of the historical processing is recorded as 1; otherwise, it is recorded as -1. The mapping and matching is a one-to-one matching.

[0037] Specifically, if the expected raw material usage of a production workshop in an industrial park is... ,in , , , These represent the expected usage amounts of Type I, Type II, Type III, and Type IV raw materials in the raw material set.

[0038] If the set of raw materials used in a certain historical processing of this production workshop in the industrial park is as follows: ,in , , , These represent the usage quantities of Type I, Type II, Type III, and Type IV raw materials in the raw material set, respectively. The expected raw material set for this production workshop maps one-to-one with the historical raw material set used in this processing session. , , , If the deviations are all less than the allowable deviations stored in the data warehouse, then the first matching value of this historical processing is recorded as 1.

[0039] If the set of raw materials used in a certain historical processing of this production workshop in the industrial park is as follows: The raw materials expected to be used in this production workshop do not include... The mapping is then recorded as -1 for the first matching value of this historical processing.

[0040] It should be noted again that the preset reference frequency is specifically used as a basis for measuring whether polluted water quality indicators are included in the predicted pollutant indicator set. For example, in order to reduce the burden of data monitoring and analysis, the preset reference frequency is set higher, such as 0.7, which is specifically set by the industrial park management personnel.

[0041] A2. Construct a database relating the pollutant index set and the raw material usage set of the industrial park. Based on the expected raw material usage set of each production workshop in the industrial park, filter out the pollutant index set of each production workshop in the industrial park, and use it as the predicted pollutant index set of each production workshop in the industrial park.

[0042] It should be noted that the specific method for constructing the database of the relationship between the pollution index set and the usage of various types of raw materials in the industrial park is as follows: Based on the set of raw materials used in each historical processing of each production workshop in the industrial park and the set of polluted water quality indicators, the set of polluted water quality indicators in the industrial park is mapped to the set of raw materials used in each historical processing of each production workshop. The sets of raw materials used corresponding to the sets of polluted water quality indicators in the industrial park are then summarized. The maximum and minimum usage of each type of raw material are selected to obtain the usage range of each type of raw material, which is then summarized into the set of raw materials used corresponding to each set of polluted water quality indicators. Finally, the set of raw materials used corresponding to each pollutant index set is extracted.

[0043] When predicting pollutant indicators for several workshops in an industrial park, this invention considers whether there is similarity between the current expected production information and historical production. If there is no similar historical production, a database is constructed to link the sets of polluted water quality indicators and raw material usage sets in the industrial park. If there is similar historical production, it indicates that the polluted water quality indicators generated in the past can be used as polluted water quality indicators for the current expected production information, resulting in more accurate processing and improved precision.

[0044] As a preferred approach, the specific prediction method for predicting the wastewater pollution index of several wastewater treatment facilities in an industrial park is as follows: extract the characteristic parameters of each wastewater pollution index from the set of historical processing wastewater quality indicators of each production workshop in the industrial park, and perform homogenization processing to obtain the characteristic parameters of each wastewater pollution index after treatment.

[0045] It should be noted that the homogenization method adopts Min-Max standardization. For example, the maximum and minimum characteristic parameters of each polluted water quality index are selected from the characteristic parameters of each historical processing of each production workshop in the industrial park and taken as 1 and 0 respectively. Then, the characteristic parameters of each polluted water quality index of each historical processing of each production workshop in the industrial park are homogenized. The processed characteristic parameters are in the same order of magnitude, avoiding the large difference in the range of data values ​​from affecting subsequent calculations.

[0046] The comprehensive pollution index method was used to calculate the wastewater pollution index of each production workshop in the industrial park for each historical processing.

[0047] It should be noted that the comprehensive pollution index method specifically involves: obtaining the weighting factors corresponding to each pollution indicator from the data warehouse; dividing the characteristic parameters of each pollution water quality indicator from each historical processing in each production workshop of the industrial park by the standard values ​​corresponding to each pollution indicator stored in the data warehouse; multiplying the result by the corresponding weighting factor and summing the results to obtain the wastewater pollution index for each historical processing in each production workshop of the industrial park. The standard values ​​corresponding to each pollution indicator are used to measure whether the pollution indicator meets the pollution standard. When the characteristic parameter corresponding to a pollution indicator exceeds the standard value, it indicates that the pollution indicator has met the pollution standard. The larger the characteristic parameter, the larger the pollution index. The specific value is determined by experts related to water pollution control.

[0048] It should also be noted that the weighting factors of each pollution indicator specifically reflect the degree of harm that each pollution indicator poses to the environment and human health. The larger the weighting factor, the greater the degree of harm that the pollution indicator poses to the environment and human health. The weighting factor includes a value of 0-1 and is specifically determined by experts related to water pollution control.

[0049] Extract the wastewater discharge volume of each historical processing from the production data of each production workshop in the industrial park. Based on the expected set of raw materials used in each production workshop in the industrial park, and combining the set of raw materials used in each historical processing of each production workshop in the industrial park, wastewater discharge volume and wastewater pollution index, if A1 feedback is successful, then execute B1; otherwise, execute B2.

[0050] B1. Based on several reference historical processing data of each production workshop in the industrial park, the wastewater pollution index of each reference historical processing data of each production workshop in the industrial park is extracted, and the average value is processed to obtain the wastewater pollution index of each production workshop. The wastewater discharge of each production workshop in the industrial park is obtained through similar processing.

[0051] B2. Construct a database of the relationship between the wastewater pollution index and raw material usage of each industrial park. Based on the expected raw material usage of each production workshop in the industrial park, screen out the wastewater pollution index of each production workshop in the industrial park, and obtain the wastewater discharge of each production workshop in the industrial park through similar treatment.

[0052] It should be noted that the method for constructing the database of relationships between wastewater pollution indices and raw material usage in an industrial park is as follows: Based on the set of raw materials used in each historical processing of each production workshop in the industrial park and the wastewater pollution index, the set of raw materials used in each historical processing of each wastewater pollution index in the industrial park is mapped to the set of raw materials used in each historical processing of each production workshop. Each wastewater pollution index is divided into intervals according to a preset step size, and then the set of raw materials used in each historical processing of each production workshop in each interval is obtained. The sets of raw materials used in each interval of the industrial park are summarized to obtain the set of raw materials used in each interval. The maximum and minimum usage of each type of raw material are selected to obtain the usage interval of each type of raw material, which is then summarized into the set of raw materials used in each interval. The median value of each interval is selected as each wastewater pollution index, thereby constructing the set of raw material usage corresponding to each wastewater pollution index in the industrial park.

[0053] The system retrieves information from the cloud management platform regarding the associated production workshops corresponding to various wastewater treatment facilities in the industrial park. It then maps these workshops together, obtaining the wastewater pollution index and wastewater discharge volume for each associated production workshop within the industrial park. Finally, it sets the wastewater pollution index for each associated production workshop within the industrial park as follows: Wastewater discharge Imported into the wastewater pollution index correction model The output shows the wastewater pollution index of each wastewater treatment facility within the industrial park. , This indicates the serial number of each wastewater treatment device. , It is any integer greater than 2. This indicates the number of each associated production workshop. , It can be any integer greater than 2.

[0054] It should be noted that the wastewater pollution index correction model adopts a weighted average method based on water quality and quantity. It takes into account both the water quality of wastewater from each production workshop, that is, the comprehensive impact of various pollutants in wastewater is reflected by the wastewater pollution index, and the water quantity factor of wastewater from each production workshop. It recognizes the different contributions of wastewater discharge from different workshops to the final degree of wastewater pollution, and avoids the one-sidedness caused by focusing only on a single factor of water quality or water quantity. It can more comprehensively reflect the actual situation.

[0055] The cloud management platform obtains the associated production workshops corresponding to several wastewater treatment devices in the industrial park. Each associated production workshop specifically reflects the wastewater treatment by the wastewater treatment devices. The predicted pollutant index set of each associated production workshop corresponding to several wastewater treatment devices in the industrial park is mapped out. The predicted pollutant index set of several wastewater treatment devices in the industrial park is then summarized and used as the monitoring parameter of several wastewater treatment devices in the industrial park.

[0056] It should also be noted that this invention, based on the raw material sets and pollutant water quality index sets of various production workshops in an industrial park, combined with the projected raw material sets of each workshop, predicts the monitoring parameters and wastewater pollution indices of several wastewater treatment equipment within the industrial park. The historical raw material sets and pollutant water quality index sets include the usage of various raw materials and corresponding pollutant emission data during past production processes. Simultaneously considering the current raw material set, it combines the current production situation with historical data. By analyzing this historical data, the types, quantities, and emission patterns of pollutants generated during the processing of different raw materials can be understood. For example, if historical data shows that a certain raw material will produce a high concentration of a certain type of pollutant, then when using the same raw material in current production, the emission of that pollutant can be predicted more accurately. Accurate prediction of the pollutant index set provides solid data support for subsequent real-time monitoring of the current production in the industrial park, adjusting the monitoring frequency or data acquisition time interval of relevant sensors for the pollutant index set, reducing data redundancy, and improving the efficiency of data monitoring and processing.

[0057] The wastewater treatment equipment mode confirmation module determines the predicted operation mode of several wastewater treatment equipment in the industrial park based on the wastewater pollution index and time-series characteristics of the equipment's regular operation data set and processing data set. The operation mode includes regular mode, energy-saving mode, emergency mode and auxiliary mode.

[0058] As a preferred approach, the method for determining the predicted operation mode of several wastewater treatment devices in the industrial park is as follows: based on the set of routine operation data and the set of treatment data of several wastewater treatment devices in the industrial park under time-series characteristics, the treatment efficiency indicator factors of several wastewater treatment devices in the industrial park are evaluated.

[0059] As a preferred approach, the specific evaluation method for assessing the treatment efficiency index factors of several wastewater treatment devices in the industrial park is as follows: extract the appearance images of each time-series feature from the set of routine operating data of several wastewater treatment devices in the industrial park under time-series features, and obtain the first treatment efficiency index factor of several wastewater treatment devices in the industrial park through data processing.

[0060] As a preferred embodiment, the first treatment efficiency indicator factor of several wastewater treatment devices in the industrial park is specifically processed as follows: based on the appearance images of several wastewater treatment devices in the industrial park at various time-series characteristics, defect data of several wastewater treatment devices in the industrial park at various time-series characteristics are obtained through image recognition technology, and the defect data includes several defect types.

[0061] Risk factors corresponding to each defect type are obtained from the data warehouse. These risk factors include values ​​from 0 to 1. Risk factors for several defect types of several wastewater treatment equipment in the industrial park are screened for different time-series characteristics. After averaging these risk factors, the overall risk factor for several wastewater treatment equipment is obtained. The first treatment efficiency indicator factor of several wastewater treatment devices in the industrial park was obtained through processing. , It serves as the primary indicator of the treatment efficiency of several wastewater treatment facilities within the industrial park.

[0062] It should be noted that the risk factors corresponding to each defect type specifically reflect the impact of the defect type on the use of wastewater treatment equipment. The higher the risk factor, the greater the impact of the defect type on the use of wastewater treatment equipment. For example, defect types include deformation, breakage, corrosion, and leakage. Breakage may directly damage the structural integrity of the equipment, making it unable to operate normally, which has a significant impact. Leakage will cause liquid loss during the treatment process, affecting the continuity of the treatment process, and may also cause local water immersion of the equipment, leading to damage to other components, which also has a significant impact. Deformation may change the internal spatial structure of the equipment, affecting material flow or treatment effect, but it generally will not immediately stop the equipment from operating, so the impact is relatively small. Corrosion is a gradual process, and its impact is relatively larger than that of deformation. Specifically, the risk factors corresponding to breakage, leakage, corrosion, and deformation can be set to 0.9, 0.9, 0.5, and 0.2, respectively, and the specific settings should be made by wastewater treatment equipment experts.

[0063] The pre- and post-factor parameters of each pollutant water quality index and the characteristic parameters of each operational index under time-series characteristics are extracted from the treatment data set of several wastewater treatment equipment in the industrial park. After normalization, these parameters are imported into the second treatment efficiency indicator factor model.

[0064] The second processing effectiveness indicator factor model is as follows:

[0065] ,

[0066] in , For the i-th wastewater treatment equipment after homogenization, let p be the pre- and post-characteristic parameters of the p-th pollutant water quality index at the h-th time-series characteristic. Given the acceptable characteristic parameter range for the p-th pollutant water quality indicator in the data warehouse, output the second treatment efficiency indicator factor for several wastewater treatment devices in the industrial park. The number representing each time-series feature. , It is any integer greater than 2. This indicates the number of each polluted water quality indicator. , It can be any integer greater than 2.

[0067] It should be noted that the qualified characteristic parameter range of each polluted water quality indicator represents the reasonable range of each polluted water quality indicator. If it is not within this range, there is a risk of pollutants exceeding the standard. The specific parameters are obtained from industry standards and stored in the data warehouse.

[0068] The treatment efficiency index of several wastewater treatment devices in the industrial park is obtained by weighted averaging the first and second treatment efficiency index factors.

[0069] It should be noted that the weighted average of the first and second treatment efficiency indicators of several wastewater treatment devices in the industrial park means that both the first and second treatment efficiency indicators have corresponding weight factors. The weight factors of the first and second treatment efficiency indicators reflect the influence of the first and second treatment efficiency indicators on the overall treatment efficiency indicator. The greater the influence, the larger the weight factor. The specific weighting is determined by experts in water pollution control. The weighted average method is an existing technology and is relatively simple, so it will not be elaborated here.

[0070] Based on the wastewater pollution index of several wastewater treatment devices within the industrial park, the wastewater pollution index ranges corresponding to the characteristic values ​​of each initial operation mode are obtained from the cloud management platform. After comparison and processing, the characteristic values ​​of the initial operation modes of several wastewater treatment devices within the industrial park are obtained. .

[0071] It should be noted that the wastewater pollution index range corresponding to the characteristic values ​​of each initial operation mode is specifically the wastewater pollution index range corresponding to the ideal operation mode without considering the treatment efficiency of the wastewater treatment equipment. The larger the wastewater pollution index, the larger the characteristic value of the initial operation mode and the higher the intensity of the operation mode. The specific settings are determined by experts related to water pollution control.

[0072] The treatment efficiency indicators of several wastewater treatment facilities in the industrial park The initial operating mode feature values ​​are imported into the predicted operating mode correction model, and the predicted operating mode feature values ​​of several wastewater treatment devices in the industrial park are output, thereby matching the predicted operating mode of each wastewater treatment device in the industrial park.

[0073] It should be noted that the initial operating mode feature value includes the values ​​1, 2, 3, and 4. When the initial operating mode feature value is 1, 2, 3, or 4, the corresponding initial operating modes are energy-saving mode, normal mode, emergency mode, and auxiliary mode, respectively. The auxiliary mode is a mobile auxiliary device assisting in the processing.

[0074] It should also be noted that, regarding the predicted operating modes matched to each wastewater treatment device in the industrial park, if the predicted operating mode feature value of a certain wastewater treatment device in the industrial park is greater than or equal to 4, then the predicted operating mode of the wastewater treatment device is the auxiliary mode; if the value is less than or equal to 1, then the predicted operating mode of the wastewater treatment device is the energy-saving mode; and if the value is 2 or 3, then the corresponding predicted operating modes are the normal mode and the emergency mode, respectively.

[0075] As a preferred embodiment, the predicted operating mode correction model is specifically as follows:

[0076] ,

[0077] in , , , These represent the adjustment parameters for the decrease and increase of the operating mode for the i-th wastewater treatment device, respectively. Demand processing efficiency indicator factor for adjusting the characteristic values ​​of the unit operation mode. Let i be the interval of the demand treatment efficiency indicator factor corresponding to the characteristic value of the i-th wastewater treatment equipment in the initial operation mode. To round up, output the predicted operating mode characteristic values ​​of several wastewater treatment devices in the industrial park. This allows for the matching of predicted operating modes of various wastewater treatment equipment within the industrial park.

[0078] It should be noted that the specific range of demand treatment efficiency indicator factors corresponding to the initial operating mode characteristic values ​​of each wastewater treatment device is located from the demand treatment efficiency indicator factor range corresponding to each initial operating mode characteristic value stored in the data warehouse. The larger the initial operating mode characteristic value, the larger the treatment efficiency indicator factor. The specific settings are made by wastewater treatment equipment experts.

[0079] This invention utilizes a wastewater treatment equipment mode confirmation module. Based on the regular operation and processing data of the wastewater treatment equipment, and taking into account the predicted pollution index of the wastewater treatment equipment, it determines whether the equipment's own condition and processing capacity are suitable for treating the wastewater generated in the production workshops within the industrial park. This ensures the treatment effect and maintains the lifespan of the wastewater treatment equipment while also saving on resource consumption, avoiding over-treatment, and preventing resource waste.

[0080] The management terminal adjusts the operating mode of several wastewater treatment devices in the industrial park to a predictive operating mode.

[0081] Reference Figure 2 As shown, the second aspect of the present invention provides a method for implementing the industrial equipment monitoring and management system of the present invention, comprising: ST1, using sensor fusion technology to monitor the routine operation data and processing data of several wastewater treatment devices in an industrial park, and generating a set of routine operation data and processing data of several wastewater treatment devices in the industrial park under time-series characteristics and uploading it to a cloud management platform.

[0082] ST2. Predict the monitoring parameters and wastewater pollution index of several wastewater treatment equipment in the industrial park and upload them to the cloud management platform.

[0083] ST3. Determine the predicted operating modes of several wastewater treatment devices in the industrial park. The operating modes include normal mode, energy-saving mode, emergency mode and auxiliary mode.

[0084] ST4. Adjust the operating mode of several wastewater treatment devices in the industrial park to a predictive operating mode.

[0085] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A cloud management platform based industrial equipment monitoring management system, characterized in that, The method comprises the following steps: a wastewater treatment equipment monitoring module adopts sensor fusion technology to monitor the conventional operation data and processing data of a plurality of wastewater treatment equipment in an industrial park, and generates conventional operation data sets and processing data sets of the plurality of wastewater treatment equipment in the industrial park under time sequence characteristics and uploads them to a cloud management platform; a wastewater treatment equipment prediction module obtains prior production information and predicted production information of the industrial park from the cloud management platform, predicts the monitoring parameters and wastewater pollution index of the plurality of wastewater treatment equipment in the industrial park, and uploads them to the cloud management platform; The specific prediction method of the monitoring parameters and wastewater pollution index of the plurality of wastewater treatment equipment in the industrial park is as follows: extracting the use of raw material set and the pollution water quality index set of each historical processing of a plurality of production workshops from the prior production information of the industrial park, combining the predicted production information of the industrial park, determining the predicted pollutant index set of the plurality of production workshops in the industrial park, and predicting the wastewater pollution index of the plurality of wastewater treatment equipment in the industrial park; obtaining the corresponding associated production workshops of the plurality of wastewater treatment equipment in the industrial park from the cloud management platform, mapping the predicted pollutant index set of the corresponding associated production workshops of the plurality of wastewater treatment equipment in the industrial park, and obtaining the predicted pollutant index set of the plurality of wastewater treatment equipment in the industrial park by summarizing, which is used as the monitoring parameters of the plurality of wastewater treatment equipment in the industrial park; a wastewater treatment equipment mode confirmation module determines the predicted operation mode of the plurality of wastewater treatment equipment in the industrial park based on the wastewater pollution index and the conventional operation data set and the processing data set under the time sequence characteristics of the plurality of wastewater treatment equipment in the industrial park, wherein the operation mode includes a conventional mode, an energy-saving mode, an emergency mode and an auxiliary mode; a management terminal adjusts the operation mode of the plurality of wastewater treatment equipment in the industrial park to the predicted operation mode; The specific determination method of the predicted operation mode of the plurality of wastewater treatment equipment in the industrial park is as follows: based on the conventional operation data set and the processing data set under the time sequence characteristics of the plurality of wastewater treatment equipment in the industrial park, evaluating the processing efficiency indicative factor of the plurality of wastewater treatment equipment in the industrial park; Based on the wastewater pollution indexes of the several wastewater treatment devices in the industrial park, the wastewater pollution index intervals corresponding to the initial operation mode characteristic values are obtained from the cloud management platform, and the initial operation mode characteristic values of the several wastewater treatment devices in the industrial park are obtained through comparison and processing M' _0i ; The processing efficiency indicator factor of several wastewater treatment devices in an industrial park EI i And the initial operation mode characteristic value is imported into the prediction operation mode correction model, and the prediction operation mode characteristic value of the several wastewater treatment devices in the industrial park is output, so as to match the prediction operation mode of each wastewater treatment device in the industrial park. The predicted operation mode correction model is specifically: ， wherein , , M _i_down , M _i_up respectively represent the running mode down adjustment variable, the running mode up adjustment variable of the i th wastewater treatment equipment, EI' is the demand treatment efficiency indicator factor of the unit adjustment running mode characteristic value, is the demand treatment efficiency indicator factor interval corresponding to the initial running mode characteristic value of the i th wastewater treatment equipment, is the upward rounding, and the predicted running mode characteristic value of the several wastewater treatment equipments in the industrial park is output M i , so as to match the predicted running mode of each wastewater treatment equipment in the industrial park.

2. The cloud management platform based industrial equipment monitoring management system of claim 1, wherein, The conventional operation data includes appearance images; The processing data includes the front feature parameters and the rear feature parameters of each pollution water quality index.

3. The cloud management platform based industrial equipment monitoring management system of claim 1, wherein, The specific evaluation method of the processing efficiency indicative factor of the plurality of wastewater treatment equipment in the industrial park is as follows: extracting the appearance images of each time sequence characteristic from the conventional operation data set under the time sequence characteristics of the plurality of wastewater treatment equipment in the industrial park, and obtaining the first processing efficiency indicative factor of the plurality of wastewater treatment equipment in the industrial park through data processing; The pre-position characteristic parameters, post-position characteristic parameters and characteristic parameters of each operation index of each pollution water quality index of each time sequence characteristic in the processing data set of the time sequence characteristics of several wastewater treatment equipment in the industrial park are uniformly processed and introduced into the second processing efficiency index factor model In the embodiment, wherein τ' _ihp , τ _ihp is the pre- and post- characteristic parameter of the pth pollution water quality index of the ith wastewater treatment device at the hth time sequence characteristic after homogenization processing, τ1 _p is the qualified characteristic parameter interval of the pth pollution water quality index in the data warehouse, and the second treatment efficiency indicator factor of the plurality of wastewater treatment devices in the industrial park is output, h represents the number of each time sequence characteristic, h=1,2,…,g , g is any integer greater than 2, p represents the number of each pollution water quality index, p=1,2,…,q , q is any integer greater than 2; The processing efficiency indicative factor of the plurality of wastewater treatment equipment in the industrial park is obtained by weighted average of the first processing efficiency indicative factor and the second processing efficiency indicative factor of the plurality of wastewater treatment equipment in the industrial park.

4. The cloud management platform based industrial equipment monitoring management system of claim 1, wherein, The specific processing method of the first processing efficiency indicative factor of the plurality of wastewater treatment equipment in the industrial park is as follows: Based on the appearance images of the wastewater treatment equipment in the industrial park at each time sequence feature, the defect data of the wastewater treatment equipment in the industrial park at each time sequence feature is obtained through image recognition technology, and the defect data includes a plurality of defect types; Obtain risk factors corresponding to each defect type from the data warehouse, the risk factors including 0-1 numerical values, screen risk factors of a plurality of defect types of each time sequence characteristics of a plurality of wastewater treatment equipment in the industrial park, and obtain overall risk factors θ of the plurality of wastewater treatment equipment after mean processing i , and obtain the first treatment efficiency indicator factor of the plurality of wastewater treatment equipment in the industrial park , i is the first treatment efficiency indicator factor of the plurality of wastewater treatment equipment in the industrial park.

5. A method for performing the industrial equipment monitoring management system of any one of claims 1-4, characterized by, It comprises: ST1, using sensor fusion technology, monitoring the conventional operation data and processing data of the wastewater treatment equipment in the industrial park, and generating the conventional operation data set and processing data set of the wastewater treatment equipment in the industrial park at the time sequence feature and uploading to the cloud management platform; ST2, predicting the monitoring parameters and wastewater pollution index of the wastewater treatment equipment in the industrial park and uploading to the cloud management platform; ST3, determining the predicted operation mode of the wastewater treatment equipment in the industrial park, the operation mode including normal mode, energy saving mode, emergency mode and auxiliary mode; ST4, adjusting the operation mode of the wastewater treatment equipment in the industrial park to the predicted operation mode.

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