An equipment detection method, system and equipment applicable to multiple cooling systems

Abstract

The present invention relates to the technical field of equipment detection and monitoring, and in particular to an equipment detection method, system and equipment applicable to multiple cooling systems. The method includes: constructing a plurality of switched detection modules, where the switched detection modules include single-medium detection modules and compatible detection modules; determining the cooling system to be detected and obtaining the equipment detection standards for the corresponding cooling medium; constructing a scheduling and detection center, selecting a number of switched detection modules for connection combination according to the cooling system to be detected to generate a cooling detection configuration; the cooling detection configuration performs sampling detection on the cooling system to be detected, and obtains the cooling equipment detection result according to the equipment detection standards. Through the present invention, the problems of compatibility and efficiency in the detection of multiple cooling systems in copper material production and manufacturing are effectively solved, flexible adaptation and efficient detection of multiple cooling media are realized, and the stable operation of the cooling system and the improvement of product quality are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment detection and monitoring, and particularly to a method, system and equipment for detecting equipment applicable to multiple cooling systems. Background Art

[0002] In modern industrial production, the cooling system is a key link to ensure the stable operation of equipment and product quality. Especially in the process of copper material production, the performance of the cooling system directly affects the forming quality and production efficiency of copper materials. Copper material production usually involves high-temperature processing, and multiple cooling media (such as water, oil, gas, etc.) are required to quickly cool the equipment and products to control the temperature, reduce deformation and improve material properties. Therefore, multiple cooling systems are widely used in copper material manufacturing, and their stability and detection accuracy are crucial for the optimization of the production process.

[0003] However, the existing cooling system detection technologies have significant defects. First, traditional detection methods are usually designed for a single cooling medium and cannot be compatible with the detection requirements of multiple media, resulting in the need to configure multiple sets of detection equipment in the application of multiple cooling systems, increasing costs and complexity. Second, the existing technologies lack intelligent scheduling and configuration capabilities and cannot dynamically adjust the detection modules according to different cooling systems, resulting in low detection efficiency and insufficient adaptability.

[0004] The information disclosed in this background art section is only intended to deepen the understanding of the overall background art of the present disclosure, and should not be regarded as an admission or any form of suggestion that this information constitutes the prior art known to those skilled in the art. Summary of the Invention

[0005] The present invention provides a method, system and equipment for detecting equipment applicable to multiple cooling systems, which can effectively solve the problems in the background art.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] A method for detecting equipment applicable to multiple cooling systems, the method comprising:

[0008] Constructing a plurality of switched detection modules, the switched detection module comprising a single-medium detection module and a compatible detection module;

[0009] Determining the cooling system to be detected and obtaining the equipment detection standard for the corresponding cooling medium;

[0010] Constructing a scheduling and detection center, selecting a plurality of the switched detection modules according to the cooling system to be detected for connection and combination to generate a cooling detection configuration;

[0011] The cooling detection configuration samples and detects the cooling system to be detected, and obtains the detection results of the cooling equipment according to the equipment detection standard.

[0012] Further, a plurality of switched detection modules are constructed, including:

[0013] Collect cooling detection process information, obtain a number of cooling detection process chains, extract several types of cooling media, and construct single-medium detection modules according to the several cooling media, and the single-medium detection modules correspond to the cooling media one by one;

[0014] Divide the several cooling detection process chains into process sections, identify and integrate the detection requirements and process characteristics of the several detection process sections to obtain compatible process sections, and construct compatible detection modules according to the compatible process sections.

[0015] Further, select several of the switched detection modules according to the cooling system to be detected for connection and combination to generate a cooling detection configuration, including:

[0016] Determine the cooling medium according to the cooling system to be detected, and match the single-medium detection module;

[0017] Match the cooling detection process chain according to the cooling medium to obtain several detection process sections;

[0018] Obtain the cooling equipment detection standard, match the detection parameters of the several detection process sections respectively according to the cooling equipment detection standard to obtain several compatible detection modules;

[0019] Sort the several compatible detection modules, select the compatible detection modules according to the sorting result, and combine the single-medium detection module and the compatible detection module to generate a cooling detection configuration;

[0020] Among them, each detection process section corresponds to a switched detection module.

[0021] Further, the scheduling and detection center performs parallel detection on at least two cooling systems to be detected, including:

[0022] Collect several cooling systems to be detected, respectively obtain several detection process sections, and match the cooling detection configuration;

[0023] Generate a detection timeline according to the several detection process sections, perform parallel detection on the several cooling systems to be detected according to the detection timeline, and allocate the compatible detection modules according to the detection timeline;

[0024] Extract several overlapping compatibility detection modules, perform peak staggering processing on the several overlapping compatibility detection modules to obtain a peak-staggered detection timeline, and perform parallel detection on several of the cooling systems to be detected according to the peak-staggered detection timeline.

[0025] Further, the cooling detection configuration performs sampling detection on the cooling system to be detected, and obtains a cooling equipment detection result according to the equipment detection standard, including:

[0026] Divide the cooling system to be detected into several detection sections according to the cooling detection process information, and obtain several detection sections;

[0027] Collect historical cooling detection information, assign weights to the several detection sections according to the historical cooling detection information, and obtain stage weights;

[0028] Construct a detection information database, and obtain an equipment detection standard according to the detection information database;

[0029] Detect the cooling system to be detected according to the stage weights and the equipment detection standard, and output a cooling equipment detection result.

[0030] Further, constructing a detection information database includes:

[0031] Collect the factory-rated life of the cooling equipment, and obtain the historical equipment life cycle set of the cooling equipment;

[0032] Obtain several equipment life deviation values according to the factory-rated life and the historical equipment life cycle set, and the equipment life deviation values correspond one by one to the elements in the historical equipment life cycle set;

[0033] Use the several equipment deviation life values as a combined index for the equipment detection standard and the several equipment life cycles, and dynamically update the equipment detection standard according to real-time monitoring data to construct a detection information database.

[0034] Further, assigning weights to the several detection sections according to historical cooling detection information to obtain stage weights includes:

[0035] Assign an initial weight to the detection section based on historical cooling detection information, perform equipment evaluation on the cooling system to be detected according to the initial weight, and obtain an initial evaluation result;

[0036] S1: Adjust the weight of any one of the detection sections, keep the initial weights of the remaining detection sections, perform equipment evaluation again to obtain a re-evaluation result, and compare it with the initial evaluation result to obtain an evaluation comparison result;

[0037] Repeat step S1 until weight adjustment is performed on all the detection sections, and allocate weights according to the proportion results of several evaluation comparison results to obtain stage weights.

[0038] Further, dynamically update the equipment detection standards according to real-time monitoring data, including:

[0039] Use a machine learning algorithm to construct a life deviation prediction model, and obtain a time life subset and a physical life subset according to the historical equipment life cycle set;

[0040] Divide the time life subset and the physical life subset into a training set and a validation set, train and evaluate the life according to the training set and the validation set to obtain a life deviation prediction result;

[0041] Compare the life deviation prediction result with the equipment detection standard, and dynamically update the equipment detection standard.

[0042] An equipment detection system applicable to multiple cooling systems, the system includes:

[0043] A switched detection module construction module that constructs multiple switched detection modules, and the switched detection module includes a single-medium detection module and a compatible detection module;

[0044] A cooling system determination and standard acquisition module that determines the cooling system to be detected and acquires the equipment detection standards for the corresponding cooling medium;

[0045] A scheduling and detection center construction module that constructs a scheduling and detection center, selects several of the switched detection modules for connection combination according to the cooling system to be detected, and generates a cooling detection configuration;

[0046] A cooling detection configuration execution module that samples and detects the cooling system to be detected and obtains a cooling equipment detection result according to the equipment detection standard.

[0047] An equipment detection device applicable to multiple cooling systems, and the device applies any one of the equipment detection methods applicable to multiple cooling systems.

[0048] Through the technical solution of the present invention, the following technical effects can be achieved:

[0049] Effectively solve the problems of compatibility and efficiency in the detection of multiple cooling systems in copper material production and manufacturing, realize flexible adaptation and efficient detection of multiple cooling media, ensure the stable operation of the cooling system and the improvement of product quality, and at the same time reduce equipment costs and maintenance difficulties, with significant economic benefits and industrial application value.

[0050] The above description is only an overview of the technical solution of the present application. In order to understand the technical means of the present application more clearly, it can be implemented in accordance with the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically illustrates the specific embodiments of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0052] Figure 1 Flow schematic diagram of the equipment detection method applicable to multiple cooling systems;

[0053] Figure 2 Schematic diagram of the architecture of Embodiment 1;

[0054] Figure 3 Schematic diagram of the structure for constructing multiple switched detection modules;

[0055] Figure 4 Flow schematic diagram for obtaining the detection result of the cooling equipment;

[0056] Figure 5 Flow schematic diagram for constructing the detection information database. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0059] Embodiment 1;

[0060] As Figure 1 and 2 shown, the present application provides an equipment detection method applicable to multiple cooling systems, and the method includes:

[0061] S10: Construct multiple switching detection modules, where the switching detection module includes a single-medium detection module and a compatibility detection module;

[0062] S20: Determine the cooling system to be detected and obtain the device detection standard for the corresponding cooling medium;

[0063] S30: Construct a scheduling and detection center, select several switching detection modules according to the cooling system to be detected for connection and combination, and generate a cooling detection configuration;

[0064] S40: The cooling detection configuration performs sampling detection on the cooling system to be detected, and obtains the cooling device detection result according to the device detection standard.

[0065] Specifically, multiple switched detection modules are constructed. Each switched detection module consists of a single-medium detection module and a compatible detection module. The single-medium detection module is designed to detect a specific cooling medium and adopts a one-to-one correspondence design with the type of cooling medium. The compatible detection module is used to handle the detection scenarios where different cooling media coexist and can accommodate the detection requirements of multiple cooling media. In copper production, if cooling water and cooling oil are used simultaneously, the single-medium detection module can be used to monitor parameters such as the temperature and flow rate of water and oil respectively to ensure the accuracy of the detection of each cooling medium. At the same time, the compatible detection module will conduct a comprehensive detection of the water-oil mixed cooling environment to ensure the compatibility and effectiveness of different cooling media. Before starting the detection, it is first necessary to analyze the cooling system to be detected, clarify its type, and obtain the equipment detection standards for the corresponding cooling medium. The following are the specific steps: It is necessary to select a cooling system from multiple cooling systems to be detected, which may be based on the actual working conditions of a certain copper production line. This step involves system presetting, selection of cooling medium, etc.; According to the type of cooling medium of the cooling system to be detected, obtain the corresponding equipment detection standards. The equipment detection standards include multiple indicators such as temperature, flow rate, pressure, and cooling efficiency. The standards can be obtained through analysis of historical detection data, process characteristics of the cooling medium, and other means. According to the specific requirements of the cooling system to be detected, the scheduling and detection center will select suitable switched detection modules for connection and combination to finally generate a cooling detection configuration. This configuration samples and detects the cooling system and outputs results according to the equipment detection standards; According to the type of cooling medium of the cooling system to be detected, the system first matches the corresponding single-medium detection module. At the same time, according to the selected cooling medium, the system automatically matches the corresponding cooling detection process chain and identifies the relevant detection sections. Each section needs to be customized according to the different characteristics of the cooling medium. Each detection section may correspond to multiple compatible detection modules. The scheduling and detection center will automatically select and sort the compatible detection modules according to the process characteristics of the selected detection section and combine them with the single-medium detection module to generate a complete cooling detection configuration; After the cooling detection configuration is generated, the actual detection work can be carried out. Through sampling detection, the system evaluates the cooling system to be detected according to the equipment detection standards and outputs the cooling equipment detection results.

[0066] The present invention realizes the compatibility and adaptation of different cooling systems by constructing flexible switched detection modules, and generates the most suitable cooling detection configuration through the optimized scheduling of the scheduling and detection center, ensuring that the equipment detection can be completed efficiently and accurately in an environment of multiple cooling media and process chains.

[0067] Furthermore, as Figure 3 shown, multiple switched detection modules are constructed, including:

[0068] Collect cooling detection process information, obtain a number of cooling detection process chains, extract several types of cooling media, and construct single-media detection modules according to the several cooling media respectively. The single-media detection modules correspond to the cooling media one by one.

[0069] Divide the several cooling detection process chains into work sections, identify and integrate the detection requirements and process characteristics of the several detection work sections to obtain compatible process sections, and construct a compatible detection module according to the compatible process sections.

[0070] To meet the detection requirements of various cooling systems, in this embodiment, device detection is first achieved by constructing multiple switched detection modules. These switched detection modules include two types of modules: single-media detection modules, which are specifically designed for different types of cooling media (such as water, oil, gas, etc.). Each cooling media has different heat exchange characteristics and detection requirements. Therefore, each single-media detection module corresponds to a specific cooling media one by one; compatible detection modules. The compatible detection module is designed to support multiple different combinations of process sections and can adapt to the detection requirements of multiple cooling media. Through a multi-functional sensor and an automated control system, the compatible detection module can be flexibly configured according to the required detection process to meet the requirements of different cooling process sections. In this way, the detection requirements of different cooling systems can be completed by combining different single-media detection modules and compatible detection modules, thus providing a highly flexible and efficient detection system. During the implementation process, it is necessary to divide the cooling system to be detected into work sections according to the cooling detection process information. The specific steps include: by analyzing the working principles and historical detection data of different cooling systems, extracting the key process sections during the cooling process, and defining corresponding detection tasks and parameters for each process section. These process sections may include important parameters such as coolant flow rate, temperature change, and cooling efficiency; determining the cooling media used in the cooling system to be detected. For example, water cooling, oil cooling, or gas cooling, and selecting a suitable single-media detection module according to the characteristics of each cooling media. For example, for an oil cooling system, special attention needs to be paid to the pollution degree and temperature change of the oil, while for a water cooling system, the flow rate and heat exchange efficiency of the water flow are mainly detected. According to the type of cooling media of the cooling system to be detected, select a single-media detection module that matches it. The selection of the single-media detection module is based on the media characteristics and working conditions of the cooling system to ensure that the selected module can detect the corresponding cooling system efficiently and accurately. To improve the compatibility of the detection system, the division of the process sections should not only consider the characteristics of each cooling media but also integrate multiple detection requirements. In this way, the device detection method provided in this embodiment can flexibly adjust the detection module and process chain configuration according to the requirements of different cooling systems, thus achieving more efficient and intelligent device detection.

[0071] Furthermore, select several switched detection modules according to the cooling system to be detected for connection and combination to generate a cooling detection configuration, including:

[0072] Determine the cooling medium according to the cooling system to be detected, and match the single-medium detection module;

[0073] Match the cooling detection process chain according to the cooling medium, and obtain a number of detection sections;

[0074] Obtain the cooling equipment detection standards, match the detection parameters for each of the several detection sections according to the cooling equipment detection standards, and obtain a number of compatible detection modules;

[0075] Sort the several compatible detection modules, select the compatible detection modules according to the sorting result, and combine the single-medium detection module with the compatible detection modules to generate a cooling detection configuration;

[0076] Among them, each detection section corresponds to a switched detection module.

[0077] In this embodiment, first, determine the cooling medium used according to the type of the cooling system to be detected. According to the different requirements in the copper production process, the cooling system may use water cooling, oil cooling or other special cooling media. After determining the cooling medium, match the corresponding cooling detection process chain according to the cooling medium. Each cooling process chain usually includes multiple detection sections, and each section corresponds to different detection requirements and parameters. For example, for a water cooling system, the cooling process chain may include a temperature detection section, a flow detection section, a pressure detection section, etc. By matching the cooling detection process chain, the system can obtain multiple detection sections and automatically select the appropriate detection sections according to the requirements of the system to be detected. Next, the system will obtain the detection standards of the cooling equipment. These detection standards usually contain the standard parameters required for each detection section, such as temperature range, flow range, pressure range, etc. By obtaining the cooling equipment detection standards, the system can match the parameters for each detection section, thereby generating compatible detection modules. According to the above steps, the system will select the switched detection modules suitable for the cooling system to be detected and connect and combine these modules according to the detection requirements to generate the final cooling detection configuration. This configuration can meet all the detection requirements of the cooling system to be detected and ensure the compatibility of each detection section. To ensure the efficient use of the detection modules, the present invention also includes a sorting process for multiple detection modules. By sorting the detection modules, the system can perform detections in the optimal time and order, avoiding resource conflicts or detection delays caused by the simultaneous use of multiple detection modules.

[0078] Furthermore, the scheduling and detection center performs parallel detections on at least two cooling systems to be detected, including:

[0079] Collect a number of cooling systems to be detected, respectively obtain a number of detection sections, and match the cooling detection configuration;

[0080] Generate a detection timeline for each of several detection sections, perform parallel detection on several cooling systems to be detected according to the detection timeline, and allocate compatible detection modules according to the detection timeline;

[0081] Extract several overlapping compatible detection modules, perform peak shifting processing on the several overlapping compatible detection modules to obtain a peak-shifted detection timeline, and perform parallel detection on several cooling systems to be detected according to the peak-shifted detection timeline.

[0082] As the above preferred implementation manner, specifically, first, the scheduling and detection center needs to collect the basic information of multiple cooling systems to be detected. Each cooling system to be detected will generate a cooling detection configuration file containing specific section requirements according to its type and working environment characteristics. This configuration file includes section division information, detection standards, measurement points, detection frequencies, etc. of the cooling system. The scheduling and detection center will automatically generate a corresponding detection section list based on the type, section, and detection requirements of the cooling systems to be detected, and allocate a dedicated switched detection module for each section. The detection module for each section is closely matched with the working environment of the cooling system to ensure the accuracy and reliability of the detection; after multiple cooling systems to be detected are ready, the scheduling and detection center will generate an independent detection timeline for each cooling system to be detected. This timeline lists the detection time points for each section, and considering the detection duration of each section and the mutual influence between sections, reasonably arranges the detection order. The parallel detection of multiple cooling systems requires special attention to the allocation and scheduling of system resources. To ensure the detection efficiency of each cooling system, the scheduling and detection center will reasonably arrange the detection sections of each cooling system according to the detection timeline and perform peak shifting processing on possible resource conflicts. Specifically, the process of peak shifting processing includes the following steps: the scheduling center analyzes the time arrangement of the detection sections, identifies the sections with module conflicts; by adjusting the task order on the detection timeline, avoids the simultaneous detection of conflicting sections; through peak shifting arrangement, the utilization rate of system resources can be improved, while ensuring the detection accuracy, minimizing the overall detection cycle.

[0083] Furthermore, as Figure 4 shown, the cooling detection configuration performs sampling detection on the cooling system to be detected and obtains the cooling equipment detection results according to the equipment detection standard, including:

[0084] S41: Divide the cooling system to be detected into several detection sections according to the cooling detection process information to obtain several detection sections;

[0085] S42: Collect historical cooling detection information, allocate weights to several detection sections according to the historical cooling detection information to obtain stage weights;

[0086] S43: Build a detection information database and obtain the device detection standard according to the detection information database;

[0087] S44: Detect the cooling system to be detected according to the stage weight and the device detection standard, and output the detection result of the cooling device.

[0088] As a preferred embodiment, first, it is necessary to collect the cooling detection process information of the cooling system to be detected. The cooling detection process information includes, but is not limited to, parameters such as the type of cooling medium, flow rate, pressure, temperature change, heat transfer efficiency, etc. These information can be obtained in real time from various links of the cooling system through devices such as sensors and data acquisition modules. Next, based on the collected cooling detection process information, the cooling system is divided into sections. The cooling system usually includes multiple sections, such as the temperature control section, the heat exchange section, the coolant circulation section, etc. The operation of each section will affect the overall cooling effect. Therefore, it is necessary to separately evaluate the detection of each section; in order to further improve the accuracy of the cooling equipment detection, this embodiment also introduces the collection of historical cooling detection information and the weight assignment mechanism. The historical cooling detection information can include the operation data, maintenance records, performance evaluation results, etc. of the cooling system in the past period of time. These historical data can help analyze the performance of the cooling system under different working conditions and identify its possible weaknesses and potential problems. For example, if it is found that the temperature fluctuation in the temperature control section is relatively large in the past detection of a certain cooling system, a higher weight can be assigned to the temperature control section through historical data to ensure more detailed monitoring of this section in subsequent detections. The process of weight assignment can identify the detection sections that have a greater impact on the system performance by analyzing the trends in historical data and increase the detection frequency and accuracy of these sections accordingly. The specific implementation method of weight assignment includes the following steps: based on the historical cooling detection information, assign an initial weight to each detection section; through the preliminary evaluation of the cooling system to be detected, determine the initial evaluation result; adjust the weight of each detection section and optimize the weight assignment by comparing the initial evaluation and the re-evaluation results, and repeat the adjustment process until the weight assignment of all detection sections is optimized to ensure the detection accuracy of each section. In order to enhance the accuracy and real-time nature of the detection standard, further construct a detection information database and dynamically update it based on real-time monitoring data. The detection information database is used to store important information such as the factory-rated life, historical equipment life cycle, and equipment life deviation of the cooling equipment. The dynamically updated equipment detection standard will be applied to the detection process of the cooling equipment. According to the updated standard, the cooling system is detected in detail and the detection results of the cooling equipment are output. The detection results include not only the real-time data of each section but also the overall operation status evaluation of the equipment. In the preferred implementation manner of the present invention, the detection information database is closely integrated with the real-time monitoring system, and the data collection and analysis process has a high degree of automation. Especially when multiple cooling systems are detected in parallel, the system can quickly adjust the detection parameters according to the real-time monitoring data and reasonably allocate the detection resources among each section. Through the collection of historical cooling detection information, weight assignment, construction of the detection information database, and dynamic update mechanism, the accuracy and real-time nature of the cooling equipment detection are significantly improved.The preferred solutions in the embodiments combine intelligent data analysis and dynamic adjustment mechanisms while ensuring the high efficiency of detection, providing a reliable guarantee for the efficient operation of complex cooling systems.

[0089] Furthermore, as Figure 5 shown, construct a detection information database, including:

[0090] S431: Collect the factory-rated life of the cooling equipment and obtain the set of historical equipment life cycles of the cooling equipment;

[0091] S432: Obtain a number of equipment life deviation values based on the factory-rated life and the set of historical equipment life cycles. The equipment life deviation values correspond one by one to the elements in the set of historical equipment life cycles;

[0092] S433: Use a number of equipment deviation life values as a combined index for equipment detection standards and a number of equipment life cycles, and dynamically update the equipment detection standards according to real-time monitoring data to construct a detection information database.

[0093] As a preferred embodiment, first, during the detection process, it is necessary to collect the factory-rated life of each cooling equipment, which reflects the expected service life of the equipment under standard working conditions. The rated life is an important reference index for equipment use and is the basis for subsequent detection data evaluation and life prediction; in addition, it is also necessary to collect the historical life cycle data of the cooling equipment, which can be obtained through the real-time monitoring results of the equipment at different usage stages, including the running duration, cooling medium usage, frequent failure records, etc. during the actual operation of the equipment. These historical data will help analyze whether the equipment operates according to the expected life and identify potential deviations or anomalies; after collecting the factory-rated life of the cooling equipment and the set of historical equipment life cycles, the next step is to calculate the deviation value of the equipment life. The equipment life deviation value refers to the gap between the actual operating life and the rated life, which can reflect whether the equipment is working properly and whether it has entered the decline period in advance; in this way, the system can generate a set of data for the life deviation of each equipment, and these data will become an important basis for evaluating the current state and future life of the equipment; after calculating the life deviation value, the system combines these values with the set of historical equipment life cycles and indexes them. Each life deviation value will correspond to the actual operation record of the equipment for subsequent data retrieval and update. This combined index can not only classify different equipment but also facilitate the quick query of the historical operation conditions of the equipment. Through the above steps, the system can dynamically update the equipment detection standards according to the equipment life deviation value and the historical life cycle data. Specifically, when the life deviation value of the equipment exceeds the preset threshold, the system will automatically adjust the detection standards of the equipment, including the detection frequency, detection parameters, etc.

[0094] Furthermore, weight distribution is performed on several detection sections according to historical cooling detection information to obtain stage weights, including:

[0095] Based on the historical cooling detection information, initial weights are assigned to the detection sections. According to the initial weights, equipment evaluation is carried out on the cooling system to be detected to obtain an initial evaluation result;

[0096] S1: Adjust the weight of any detection section, keep the initial weights of the remaining detection sections, perform equipment evaluation again to obtain a re-evaluation result, and compare it with the initial evaluation result to obtain an evaluation comparison result;

[0097] Repeat step S1 until the weights of all detection sections are adjusted. According to the proportion results of several evaluation comparison results, weights are assigned to obtain stage weights.

[0098] As an optimization of the above embodiment, a large amount of historical cooling detection information needs to be collected first, and an initial weight distribution model is constructed based on this. The data acquisition methods include sensor real-time monitoring data, equipment maintenance records, production logs, etc. According to the cooling process chain, the detection process of the cooling system is divided into multiple sections, and each detection section corresponds to specific cooling medium characteristics and detection indicators. Through statistical analysis methods, such as the mean method or empirical model, initial weights are assigned to each detection section. The initial weights reflect the importance of each section in the overall detection process; Equipment evaluation is carried out based on the initial weights to determine the overall performance of the cooling system. In order to optimize the detection weights, dynamic weight adjustment needs to be carried out on each detection section, and the performance of the cooling system is re-evaluated; After the weights of all detection sections are adjusted, all re-evaluation results are statistically analyzed, and the final stage weights are calculated. This embodiment dynamically adjusts each detection section of the cooling system and optimizes the detection process. Through steps such as initial evaluation, weight adjustment, and re-evaluation, accurate stage weights are finally obtained, improving the detection accuracy.

[0099] Furthermore, the equipment detection standard is dynamically updated according to the real-time monitoring data, including:

[0100] A life deviation prediction model is constructed using a machine learning algorithm, and a time life subset and a physical life subset are obtained according to the historical equipment life cycle set;

[0101] The time life subset and the physical life subset are divided into a training set and a validation set. According to the training set and the validation set, the life is trained and evaluated to obtain a life deviation prediction result;

[0102] According to the comparison between the life deviation prediction result and the equipment detection standard, the equipment detection standard is dynamically updated.

[0103] Preferably, as in the above embodiments, the construction of the life deviation prediction model is based on the historical equipment life cycle data of the cooling equipment. These historical data usually include information in multiple aspects such as the operating duration of the equipment, fault records, maintenance records, and environmental factors. By deeply analyzing these data, machine learning algorithms are used to model the life deviation, so as to realize the prediction of the future operating state of the equipment. First, the system needs to obtain the relevant data of the equipment through devices such as sensors and historical record systems; after obtaining the above data, select a suitable machine learning algorithm to model the life deviation; according to the historical data, divide the life cycle of the equipment into a training set and a validation set for machine learning training; based on the trained model, when the equipment enters a new operating cycle, the system will automatically input real-time monitoring data and calculate the life deviation value of the equipment through the trained life deviation prediction model. These deviation values can reflect whether the equipment is currently within the normal operating range and whether there is a risk of early failure. Among them, the time life subset is mainly calculated based on the actual operating time of the equipment; the physical life subset focuses on the physical state evaluation during the operation of the equipment; according to the calculation results of the life deviation prediction model and the life subset, the system will dynamically adjust the detection standard of the cooling equipment; this adjustment will be based on the real-time operating state and historical data of the equipment to ensure that the equipment can be detected in a timely and accurate manner.

[0104] Embodiment 2;

[0105] Based on the same inventive concept as a device detection method applicable to a multi-cooling system in the foregoing embodiments, the present invention also provides a device detection system applicable to a multi-cooling system. The system includes:

[0106] A switched detection module construction module that constructs a plurality of switched detection modules. The switched detection module includes a single-medium detection module and a compatibility detection module;

[0107] A cooling system determination and standard acquisition module that determines the cooling system to be detected and acquires the device detection standard for the corresponding cooling medium;

[0108] A scheduling and detection center construction module that constructs a scheduling and detection center, selects a number of switched detection modules for connection and combination according to the cooling system to be detected, and generates a cooling detection configuration;

[0109] A cooling detection configuration execution module that samples and detects the cooling system to be detected according to the cooling detection configuration and obtains the cooling device detection result according to the device detection standard.

[0110] The above adjustment system in the present invention can effectively implement a device detection method applicable to a multi-cooling system, and the technical effects that can be achieved are as described in the above embodiments, which will not be elaborated here.

[0111] Embodiment 3;

[0112] Based on the same inventive concept as the device detection method applicable to multiple cooling systems in the foregoing embodiments, the present invention also provides a device detection device applicable to multiple cooling systems, and the device applies any device detection method applicable to multiple cooling systems.

[0113] Similarly, the above device in the present invention can also effectively implement a device detection method applicable to multiple cooling systems, and the technical effects that can be achieved are as described in the foregoing embodiments, which will not be elaborated herein.

[0114] Although the present application has been described in conjunction with specific features and their embodiments, it is obvious that various modifications and combinations can be made without departing from the spirit and scope of the present application. Accordingly, the present specification and the drawings are merely exemplary illustrations of the present application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. A device detection method applicable to multiple cooling systems, characterized in that: The method comprises: Constructing a plurality of exchangeable detection modules, wherein the exchangeable detection modules include a single medium detection module and a compatible detection module; Determine the cooling system to be tested and obtain the equipment testing standards for the corresponding cooling medium; Constructing a scheduling and detection center, selecting a number of the exchangeable detection modules for connection and combination according to the cooling system to be detected, and generating a cooling detection configuration; The cooling detection configuration performs sampling detection on the cooling system to be detected, and obtains the cooling equipment detection result according to the equipment detection standard; Build multiple exchangeable detection modules, including: Collect cooling detection process information, obtain several cooling detection process chains, and extract several types of cooling media, and construct single medium detection modules according to the several cooling media, wherein the single medium detection modules correspond to the cooling media one by one; Divide the cooling detection process chains into sections, identify and integrate the detection requirements and process characteristics of the detection sections, obtain compatible process sections, and construct compatible detection modules according to the compatible process sections; According to the cooling system to be detected, a plurality of the exchangeable detection modules are selected for connection and combination to generate a cooling detection configuration, including: Determine the cooling medium according to the cooling system to be detected, and match the single medium detection module; According to the cooling medium matching the cooling detection process chain, a plurality of detection sections are obtained; Acquire a cooling equipment inspection standard, match inspection parameters of the plurality of inspection sections respectively according to the cooling equipment inspection standard, and acquire a plurality of compatible inspection modules; Sorting a plurality of the compatible detection modules, selecting the compatible detection module according to the sorting result, combining the single medium detection module with the compatible detection module, and generating a cooling detection configuration; Among them, each detection section corresponds to an exchangeable detection module.

2. The device detection method applicable to multiple cooling systems according to claim 1, characterized in that: Also includes: The dispatching and testing center conducts parallel testing on at least two cooling systems to be tested, including: Collecting a number of the cooling systems to be tested, respectively obtaining a number of the testing sections, and matching the cooling testing configuration; Generating a detection time axis respectively according to the plurality of detection sections, performing parallel detection on the plurality of cooling systems to be detected according to the detection time axis, and allocating the compatible detection modules according to the detection time axis; Extract a number of overlapping compatible detection modules, perform peak-shifting processing on the number of overlapping compatible detection modules, obtain a peak-shifting detection time axis, and perform parallel detection on the number of cooling systems to be detected according to the peak-shifting detection time axis.

3. The device detection method applicable to multiple cooling systems according to claim 1, characterized in that: The cooling detection configuration performs sampling detection on the cooling system to be detected, and obtains the cooling equipment detection result according to the equipment detection standard, including: Divide the cooling system to be inspected into sections according to the cooling inspection process information to obtain a plurality of inspection sections; Collect historical cooling detection information, assign weights to several detection sections according to the historical cooling detection information, and obtain stage weights; Building a detection information database, and obtaining equipment detection standards according to the detection information database; The cooling system to be detected is detected according to the stage weight and the equipment detection standard, and the cooling equipment detection result is output.

4. The device detection method applicable to multiple cooling systems according to claim 3, characterized in that: Build a detection information database, including: Collect the factory rated life of the cooling equipment and obtain a set of historical equipment life cycles of the cooling equipment; Acquire a number of equipment life deviation values ​​according to the factory rated life and the historical equipment life cycle set, wherein the equipment life deviation values ​​correspond one-to-one to the elements in the historical equipment life cycle set; The device deviation life values ​​are combined and indexed as device detection standards with the device life cycles, and the device detection standards are dynamically updated according to real-time monitoring data to build a detection information database.

5. The device detection method applicable to multiple cooling systems according to claim 4, characterized in that: According to the historical cooling detection information, weights are assigned to the detection sections to obtain stage weights, including: Based on historical cooling detection information, an initial weight is assigned to the detection section, and an equipment evaluation is performed on the cooling system to be detected according to the initial weight to obtain an initial evaluation result; S1: adjusting the weight of any of the detection sections, keeping the initial weights of the other detection sections, performing equipment evaluation again to obtain a re-evaluation result, and comparing it with the initial evaluation result to obtain an evaluation comparison result; Repeat step S1 until all the inspection stages have undergone weight adjustment, and assign weights according to the proportions of several evaluation and comparison results to obtain stage weights.

6. The device detection method applicable to multiple cooling systems according to claim 5, characterized in that: Dynamically update equipment testing standards based on real-time monitoring data, including: A life deviation prediction model is constructed using a machine learning algorithm, and a time life subset and a physical life subset are obtained according to the historical equipment life cycle set, wherein the time life subset is calculated based on the actual operating time of the equipment, and the physical life subset is evaluated by the physical state during the operation of the equipment; Dividing the temporal life subset and the physical life subset into a training set and a validation set, training and evaluating the life according to the training set and the validation set, and obtaining a life deviation prediction result; According to the comparison between the life deviation prediction result and the equipment detection standard, the equipment detection standard is dynamically updated.

7. An equipment detection system applicable to multiple cooling systems, characterized in that: The device detection method applicable to multiple cooling systems as claimed in claim 1 is adopted, wherein the system comprises: An exchangeable detection module construction module is used to construct a plurality of exchangeable detection modules, wherein the exchangeable detection modules include a single medium detection module and a compatible detection module; The cooling system determination and standard acquisition module determines the cooling system to be tested and obtains the equipment testing standard of the corresponding cooling medium; A scheduling and detection center construction module is used to construct a scheduling and detection center, select a number of the exchangeable detection modules according to the cooling system to be detected, connect and combine them, and generate a cooling detection configuration; A cooling detection configuration execution module, wherein the cooling detection configuration performs sampling detection on the cooling system to be detected, and obtains a cooling equipment detection result according to the equipment detection standard.

8. An equipment detection device suitable for multiple cooling systems, characterized in that: The device applies the device detection method applicable to multiple cooling systems as described in any one of claims 1-6.

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