Dynamic monitoring platform of pollution source treatment system

Abstract

The invention discloses a dynamic monitoring platform of a pollution source processing system, which relates to the technical field of pollution source processing, and comprises the following steps: the dynamic monitoring platform loads a preset protocol template through a device ID, dynamically adjusts legality communication parameters, locks a device type function code, and generates an initialization verification report; generating a dynamic polling task based on the initialization report, collecting equipment data in parallel through a thread pool, and executing validity mark judgment to form a standardized data packet; an analysis engine extracts plaintext parameters in the standardized data packet, converts a state code for service description and marks data quality based on a rule base, and generates a structured state analysis report; and performing multi-level anomaly detection on the structured state analysis report, triggering a hierarchical warning in combination with a logic association rule, accurately positioning a risk and triggering control strategy matching. According to the method, multi-dimensional judgment of data quality is realized through three-stage verification (frame structure verification, data type forced conversion and logic integrity verification) and a state code linkage mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of pollution source treatment, and particularly to a dynamic monitoring platform for a pollution source treatment system. Background Art

[0002] In recent years, environmental monitoring devices have been widely used in industrial scenarios. Their communication protocols are mostly based on industrial standards such as ModbusRTU. However, due to differences in device types and manufacturers, there are heterogeneities in protocol parameters (such as baud rate, register mapping). Existing technologies usually adopt static protocol configuration or manual intervention methods to adapt to different devices, and it is difficult to dynamically adapt communication parameters and parsing rules. In addition, when multiple devices collect data in parallel, the traditional polling mechanism is prone to data delay or packet loss due to rigid task scheduling. Moreover, the determination of data quality depends on a single verification logic (such as CRC verification), and it is impossible to effectively combine device status codes with business logics for comprehensive verification. For example, data anomalies in a flue gas analyzer during the backflush state are often misjudged as valid values, and a wastewater analyzer lacks a dynamic data marking linkage mechanism, resulting in invalid data not being eliminated in a timely manner.

[0003] The main deficiencies of the existing technologies are as follows: First, protocol adaptation and data parsing highly rely on manual pre-configuration, and it is impossible to dynamically load register mapping tables and function codes according to device types, resulting in low access efficiency for heterogeneous devices. Second, data collection and anomaly detection lack a multi-level verification system, and the collaborative verification of the communication layer (frame structure), business layer (status code), and logic layer (range association) is not realized, making it difficult to accurately identify latent device failures (such as sensor drift) or abnormal working conditions (such as backflush timeout). Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a dynamic monitoring platform for a pollution source treatment system to solve the problems of poor protocol adaptability, low data collection efficiency, and lagging anomaly response of multiple types of environmental monitoring devices.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: The present invention provides a dynamic monitoring platform for a pollution source treatment system, which includes, A protocol adaptation module. The dynamic monitoring platform loads a preset protocol template through a device ID, dynamically adjusts legal communication parameters, locks the function code of the device type, and generates an initialization verification report; A parallel collection module. Based on the initialization report, a dynamic polling task is generated, and device data is collected in parallel through a thread pool and the determination of validity marking is executed to form a standardized data packet; The engine parsing module parses the plaintext parameters in the standardized data packet extracted by the parsing engine, converts the status code into a business description based on the rule library, marks the data quality, and generates a structured status analysis report; The intelligent warning module performs multi-level anomaly detection on the structured status analysis report, triggers hierarchical warnings in combination with logical association rules, accurately locates risks, and triggers control strategy matching; The anti-control execution module dynamically calls the preset control strategy to generate a dual-verification instruction, drives the external device to perform physical actions through the timeout retry mechanism, and generates an anti-control operation log; The operation and maintenance management module automatically constructs a structured work order based on the anti-control log, combines historical trends with the verification of the matching degree of third-party data, and generates a root cause traceability report.

[0007] As a preferred solution of the dynamic monitoring platform of the pollution source treatment system described in the present invention, wherein: the generation of the initialization verification report includes the following steps, Retrieve the protocol template in the local database based on the device ID, load the basic communication parameters, and verify their legality; Lock the standard Modbus function code according to the device type, load the device-specific register mapping table, generate a customized test instruction, receive the device return data and perform three-level verification, and generate an initialization verification report.

[0008] As a preferred solution of the dynamic monitoring platform of the pollution source treatment system described in the present invention, wherein: the formation of the standardized data packet includes the following steps, Set the polling frequency and core parameters according to the device type, dynamically construct a ModbusRTU request frame through the thread pool and send it; After receiving the response, verify the frame structure, parse the byte order and data type, and determine the data validity in combination with the data marker register and the status code; Serialize the valid data and encapsulate it into a standardized data packet after encryption.

[0009] As a preferred solution of the dynamic monitoring platform of the pollution source treatment system described in the present invention, wherein: the generation of the structured status analysis report includes the following steps, Verify the protocol header and signature and then decrypt the data, and map the Modbus status code to a business status description; Extract the core indicators, verify the unit and type, calculate the deviation rate by comparing the configured threshold, determine the data quality in combination with the data marker value, and integrate the results to generate a status analysis report.

[0010] As a preferred solution of the dynamic monitoring platform for the pollution source treatment system of the present invention, wherein: the accurate positioning of risks and triggering of control strategy matching refers to dividing into three levels of warnings according to over-standard, parameter anomalies and status anomalies, comparing the dynamic threshold with the logical correlation conditions, grading by severity and matching the preset control strategies.

[0011] As a preferred solution of the dynamic monitoring platform for the pollution source treatment system of the present invention, wherein: the generation of anti-control operation logs refers to generating calibration, cleaning and mode switching instructions according to the warning level, double-checking the parameter range and CRC value, asynchronously sending instructions and managing timeout retries, and linking external devices to perform physical actions.

[0012] As a preferred solution of the dynamic monitoring platform for the pollution source treatment system of the present invention, wherein: the generation of the root cause traceability report includes the following steps, Create a work order based on the anti-control operation log and associate it with the device topology, and start the electronic maintenance process through the QR code; Collect the calibration records and the third-party test data to calculate the matching degree. When it does not meet the standard, retrieve the historical data to identify the trend anomaly and generate the root cause traceability report.

[0013] As a preferred solution of the dynamic monitoring platform for the pollution source treatment system of the present invention, wherein: the three-level verification includes frame structure verification, data type parsing and logical integrity verification.

[0014] As a preferred solution of the dynamic monitoring platform for the pollution source treatment system of the present invention, wherein: the determination of data validity includes that the wastewater analyzer triggers a logical warning through the data marker register value and the data quality label, and the flue gas analyzer verifies the system status code and combines the communication parameters.

[0015] As a preferred solution of the dynamic monitoring platform for the pollution source treatment system of the present invention, wherein: the comparison of the dynamic threshold includes quantifying the deviation rate of the core index and matching the compliance range according to the device type.

[0016] The beneficial effects of the present invention are as follows: Automatically matching the preset protocol template based on the device ID and dynamically adjusting communication parameters (such as baud rate adaptation) solves the protocol conflict problem caused by traditional static configuration, improving the communication frame construction efficiency of the flue gas and wastewater analyzer; Through the three-level verification and status code linkage mechanism, multi-dimensional determination of data quality is achieved; The thread pool parallel acquisition and dynamic threshold grading warning mechanism optimize the resource scheduling efficiency and abnormal response speed; Triggering a secondary warning based on the quantization deviation rate (such as the backflush interval exceeding the limit by 25%), compared with the traditional fixed threshold warning, the fault location accuracy is improved; The dual verification (parameter range, CRC) of the control strategy and the timeout retry mechanism ensure the security and execution success rate of the reverse control instruction. For example, the instruction retransmission success rate of the AB bucket sample retention action can reach 99.5%, effectively supporting the closed-loop management of environmental monitoring data and the optimization of operation and maintenance decisions. Brief Description of the Drawings

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is the initialization flowchart of the dynamic monitoring platform in Embodiment 1.

[0019] Figure 2 It is the schematic diagram of data acquisition and standardization processing in Embodiment 1.

[0020] Figure 3 It is the schematic diagram of abnormal detection and grading warning in Embodiment 1.

[0021] Figure 4 It is the schematic diagram of reverse control execution and operation and maintenance closed-loop in Embodiment 1. Detailed Embodiments

[0022] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the detailed embodiments of the present invention will be described in detail below with reference to the drawings in the specification.

[0023] Many specific details are set forth in the following description in order to provide a thorough understanding of the present invention. However, the present invention may be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0024] Second, the "one embodiment" or "embodiment" referred to herein means a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it an individual or alternative embodiment that is mutually exclusive with other embodiments.

[0025] Embodiment 1, referring to Figures 1 to 4 , is the first embodiment of the present invention. This embodiment provides a dynamic monitoring platform for a pollution source treatment system, including the following steps: Protocol adaptation module. The dynamic monitoring platform loads a preset protocol template through the device ID, dynamically adjusts the legal communication parameters, locks the device type function code, and generates an initialization verification report.

[0026] Start the dynamic monitoring platform, retrieve the corresponding preset protocol template in the local database through the device ID (such as "Juguang CEMS-2000"), and load the basic communication parameters in the preset protocol template, including the default device address, baud rate, data bits, parity mode, and stop bits; perform a legality check on the loaded basic communication parameters and dynamically adjust them according to environmental requirements. For example, check whether the baud rate is within the supported range (such as below 115200), and if it exceeds the limit, default to 9600; verify whether the data bits and parity mode conform to the ModbusRTU specification (such as the data bits must be 8, and the parity mode only supports no parity or CRC); lock the corresponding Modbus function code based on the device type, initialize the instruction frame structure, and obtain the standard function code from the rule library according to the device type. For example, the flue gas analyzer locks 03 (read register instruction), and the wastewater analyzer locks 06 (write register instruction) to generate an initial instruction template framework.

[0027] Read the parsing mode of the flue gas analyzer from the initial instruction template framework and load the register mapping table exclusive to the flue gas analyzer; the wastewater analyzer reuses the communication parameters of the flue gas analyzer, but switches the register parsing mode to the standard high and low byte order and loads the wastewater-specific mapping table; after the mapping tables of the flue gas analyzer and the wastewater analyzer are loaded, generate customized test instructions for the flue gas analyzer and the wastewater analyzer respectively; receive the data returned by the flue gas analyzer and the wastewater analyzer and perform three-level verification to generate an initialization verification report.

[0028] Further explanation, the mapping relationship of the flue gas analyzer includes register number 40001 corresponding to Concentration (Float32 type); register number 40003 corresponds to the range value (Float32 type); register number 40005 corresponds to the slope coefficient (Float32 type); register number 40381 corresponds to the system status code (Int16 type).

[0029] The mapping relationship of the discarded equipment includes that the registers numbered 40001 - 40002 correspond to the combined floating - point measurement values, the register numbered 40005 corresponds to the data validity flag (Int32 type), the register numbered 40012 corresponds to the operation mode status (Int16 type), and the register numbered 40032 corresponds to the digestion temperature (Float32 type).

[0030] The three - level verification includes frame structure verification, data type parsing, and logical integrity verification.

[0031] Specifically, frame structure verification means checking whether the response frame length, device ID, and CRC check value match; data type parsing means forcibly converting the data type according to the mapping table, for example, converting the hexadecimal in the flue gas response to 40.0 mg / m³ of Float32 type; logical integrity verification means verifying the range register and checking the status code of the system.

[0032] According to the communication parameters in the initialization report, polling tasks are generated according to the device type. Among them, the flue gas analyzer polls 、NO、 and other 5 core parameters every minute, and the wastewater analyzer collects 6 items of data such as measurement values and digestion temperature every 5 minutes; dynamic identification is performed based on the device ID, and parallel processing is achieved through the thread pool to ensure that the data collection of different devices does not interfere with each other; for each device, the system dynamically constructs a ModbusRTU request frame. The flue gas analyzer sends a request instruction frame to read 4 registers, and the wastewater analyzer sends a request instruction frame to read 4 registers. After the request instruction is sent through the RS - 485 interface, a 2 - second timeout timer is started. After successfully receiving the device response frame, it enters the next - step parsing, and if it times out, a retry mechanism is triggered; after successful reception, first, structure verification is performed to check whether the frame length, device address, and CRC value are legal. Then, the byte order is processed according to the device parsing mode (the flue gas analyzer reverses the high and low bytes, and the wastewater analyzer directly parses), and the original bytes are converted into target types such as floating - point numbers and integers; based on the rules in the register mapping table, the data validity is automatically determined; after serializing the valid data, it is encapsulated using the AES - 256 encryption algorithm to generate a standardized encrypted package that conforms to the environmental protection monitoring data transmission specification.

[0033] Further explanation, the determination of data validity means that the wastewater analyzer marks the data quality label through the data flag register value (such as 0 means valid, 4 means maintenance mode); the flue gas analyzer further verifies the system status code (such as 40381 = 6 means "in the process of back - blowing"), and combines the communication parameter value to trigger a logical warning (such as abnormal concentration during back - blowing )

[0034] The encapsulation includes adding a protocol header (such as identification, device type), a timestamp (accurate to milliseconds), an encryption signature, and a length field.

[0035] The parsing engine receives a standardized encrypted packet that complies with the environmental monitoring data transmission specification. First, it verifies the protocol header, device type identifier, and HMAC signature to confirm the legitimacy of the data source. Subsequently, it uses the AES-256 decryption algorithm to extract plaintext parameters (such as the flue gas analyzer status code 40381, backflush interval 150 minutes). Based on the device type, it queries the rule library to convert the Modbus status code into a business status description. For example, the flue gas analyzer status code 40381 = 6 is parsed as "in backflush", and the wastewater analyzer status code 40012 = 1 is parsed as "automatic measurement". Status codes that are not hit are marked as unknown and a warning is triggered. Core indicators are extracted from the plaintext parameters (such as the backflush interval of the flue gas analyzer = 150 minutes, digestion time of the wastewater analyzer = 45 minutes), and the unit format is verified (such as minutes, °C). For example, ensure that the slope coefficient is of type Float32 and the digestion temperature unit is °C. The extracted core indicators are compared with the configured thresholds to quantify the deviation rate. For example, the flue gas analyzer backflush interval = 150 minutes, exceeding the configured threshold ≤ 120 minutes, calculate the deviation rate of 25%, and mark it as "backflush timeout". The wastewater analyzer digestion time = 45 minutes within the range of 30 - 60 minutes is marked as compliant. The data quality is determined according to the data marker register value. For example, the wastewater analyzer data marker = 4 indicates "maintenance mode", and relevant parameters are automatically excluded. If the data marker = 0, the data is retained. The flue gas analyzer has no dedicated marker and is default considered valid. The verification results are integrated to generate a structured status analysis report.

[0036] Extract the key parameters of the flue gas analyzer and wastewater analyzer from the structured status analysis report; according to the comparison results of the key parameters with the dynamic thresholds, warnings are triggered according to the severity level: Level 1 warning (exceeding standard type): For example, the concentration of the flue gas analyzer ≥ 75 mg / m³ (exceeding the range by 50%), trigger a platform pop-up window + SMS notification to the operation and maintenance team leader; the digestion temperature of the wastewater analyzer > 60 °C; Level 2 warning (parameter anomaly type): For example, the backflush interval of the flue gas analyzer = 150 minutes (exceeding the limit by 25%); the flow rate of the wastewater analyzer = 0, lasting for 10 minutes and the data marker ≠ 4; Level 3 warning (status anomaly type): For example, the system status code of the flue gas analyzer = 6 (in backflush), but the concentration = 0; the operation mode of the wastewater analyzer = 2 (manual mode).

[0037] Based on the hierarchical warning results, dynamically match the preset control strategies: Level 1 warning, flue gas The concentration exceeds the standard, triggering the immediate calibration slope strategy (calling the register to write a new slope value); when the wastewater digestion temperature exceeds the standard, send an immediate cleaning instruction to the register.

[0038] Secondary warning, such as when the flue gas backflush interval exceeds the limit, triggering the calibration reminder strategy (pushing a work order and marking the device for maintenance), and when the wastewater flow stagnates, triggering the check inlet valve strategy (recording the event and associating it with the device topology diagram).

[0039] Tertiary warning, when the flue gas backflush is ineffective, triggering the switch to the standby fan strategy (calling the register to start the AB barrel sample retention), and for the wastewater manual mode, triggering the automatic mode recovery strategy (attempting to force the switch by writing register 40012 = 1 through Modbus).

[0040] Generate an instruction frame that conforms to the Modbus RTU specification according to the preset control strategy and perform double verification; asynchronously send the double-verified instruction frame through the RS-485 interface, and start the timeout retry mechanism; after the timeout retry is completed, link to external quality control equipment according to the instruction type, perform physical actions, and generate a reverse control operation log.

[0041] For further explanation, double verification includes verifying the parameter range (such as the slope value is limited to 0.95 - 1.05, and the cleaning instruction value is only allowed 1 - 5) and calculating the CRC check value (such as the flue gas instruction check value 0x483A).

[0042] The timeout retry mechanism includes real-time timeout management and response processing.

[0043] Real-time timeout management means setting a 2-second response time limit, automatically retrying after timeout (up to 3 times), for example, reducing the priority and resending the flue gas calibration instruction after timeout; response processing includes success and failure. When successful, update the device status to calibration in progress and record the new register value. When failed, mark the device communication failure, trigger a tertiary warning, and push it to the operation and maintenance platform.

[0044] Performing physical actions includes flue gas AB barrel sample retention and wastewater standard sample switching.

[0045] Flue gas AB barrel sample retention means that after receiving the calibration instruction, trigger the pneumatic valve action (register 40301 = 6), and synchronously record the sample number and time.

[0046] Wastewater standard sample switching means that after sending the instruction, link to the PLC controller to switch the high and low standard sample bottles (such as register 40302 = 3), and confirm the completion of the action through the HTTP interface.

[0047] Combined with the anti-control operation log and the hierarchical warning results, the dynamic monitoring platform automatically creates structured work orders and pushes them to the designated operation and maintenance personnel; the operation and maintenance personnel start the electronic maintenance process through the device QR code, execute the calibration instructions, and monitor the device response in real time through the APP. After completion, upload the calibration photos, corrected parameter records, and on-site environmental data; the dynamic monitoring platform extracts the AB bucket retention samples for third-party testing (such as concentration comparison test), calculates the matching degree between the laboratory data and the standard value (such as a matching degree of 98%). If it meets the standard, close the work order and file it; if it does not meet the standard (such as a matching degree of 92%), reassign the work order and mark the deviation reason (such as "sensor baseline drift"); for the unclosed work order, the dynamic monitoring platform starts root cause analysis, retrieves historical calibration records and environmental data, identifies abnormal trends (such as the calibration value drift > 2% for 3 consecutive times), generates a suggestion report (such as "replace the probe protective cover"), and at the same time enters the case into the knowledge base to form a reusable fault handling guide; based on the closed work order, generate an operation and maintenance efficiency report, display the work order processing progress through a Gantt chart, and mark the high-frequency fault devices with a heat map.

[0048] In summary, the present invention automatically matches the preset protocol template based on the device ID and dynamically adjusts communication parameters (such as baud rate adaptation), solves the protocol conflict problem caused by traditional static configuration, and improves the communication frame construction efficiency of flue gas and wastewater analyzers; through a three-level verification and status code linkage mechanism, realizes multi-dimensional determination of data quality; a thread pool parallel acquisition and dynamic threshold hierarchical warning mechanism optimizes the resource scheduling efficiency and abnormal response speed; triggers a secondary warning based on the quantization deviation rate (such as the backflush interval exceeding the limit by 25%), compared with the traditional fixed threshold warning, the fault location accuracy is improved; the double verification (parameter range, CRC) of the control strategy and the timeout retry mechanism ensure the safety and execution success rate of the anti-control instruction. For example, the instruction retransmission success rate of the AB bucket retention action can reach 99.5%, effectively supporting the closed-loop management of environmental monitoring data and the optimization of operation and maintenance decisions.

[0049] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A dynamic monitoring platform for a pollution source treatment system, characterized in that: include, Protocol adaptation module, dynamic monitoring platform loads preset protocol templates through device ID, dynamically adjusts legal communication parameters and locks device type function code, and generates initialization verification report; The parallel acquisition module generates dynamic polling tasks based on the initialization report, collects device data in parallel through the thread pool and performs validity marking judgment to form a standardized data packet; The engine parsing module extracts the plaintext parameters in the standardized data packet, converts the status code into a business description based on the rule base, marks the data quality, and generates a structured status analysis report; Intelligent warning module, which performs multi-level anomaly detection on structured status analysis reports and triggers graded warnings in combination with logical association rules, accurately locates risks and triggers control strategy matching; The reverse control execution module dynamically calls the preset control strategy to generate double verification instructions, drives the external device to perform physical actions through the timeout retry mechanism, and generates a reverse control operation log; The operation and maintenance management module automatically builds structured work orders based on the counter-control logs, combines historical trends with third-party data matching verification, and generates root cause tracing reports.

2. The dynamic monitoring platform of the pollution source treatment system according to claim 1, characterized in that: Generating an initialization verification report The following steps are included: Retrieve the protocol template in the local database based on the device ID, load the basic communication parameters and verify their legitimacy; Lock the standard Modbus function code according to the device type, load the device-specific register mapping table, generate customized test instructions, receive the data returned by the device and perform three-level verification, and generate an initialization verification report.

3. The dynamic monitoring platform of the pollution source treatment system according to claim 1, characterized in that: The forming of the standardized data packet comprises the following steps: Set the polling frequency and core parameters according to the device type, and dynamically construct and send ModbusRTU request frames through the thread pool; After receiving the response, check the frame structure, parse the byte order and data type, and determine whether the data is valid based on the data tag register and status code; Serialize the valid data and encrypt and encapsulate it into a standardized data packet.

4. The dynamic monitoring platform of the pollution source treatment system according to claim 1, characterized in that: The generating of the structured status analysis report comprises the following steps: After verifying the protocol header and signature, decrypt the data and map the Modbus status code to the business status description; Extract core indicators and verify units and types, calculate deviation rates by comparing configured thresholds, determine data quality based on data tag values, and integrate results to generate status analysis reports.

5. The dynamic monitoring platform of the pollution source treatment system according to claim 1, characterized in that: The precise positioning of risks and triggering of control strategy matching refers to dividing warnings into three levels according to exceeding standards, parameter abnormalities and status abnormalities, comparing dynamic thresholds with logical association conditions, grading by severity and matching preset control strategies.

6. The dynamic monitoring platform of the pollution source treatment system according to claim 5, characterized in that: The generating of the anti-control operation log refers to generating calibration, cleaning and mode switching instructions according to the warning level, double checking the parameter range and CRC value, asynchronously sending instructions and managing timeout retries, and linking external devices to perform physical actions.

7. The dynamic monitoring platform of the pollution source treatment system according to claim 1, characterized in that: Generating the root cause tracing report includes the following steps: Create work orders based on the reverse control operation log and associate them with the equipment topology, and start the electronic maintenance process through the QR code; Collect calibration records and third-party test data to calculate matching degree. When the standards are not met, retrieve historical data to identify abnormal trends and generate root cause tracing reports.

8. The dynamic monitoring platform of the pollution source treatment system according to claim 2, characterized in that: The three-level verification includes frame structure verification, data type analysis and logical integrity verification.

9. The dynamic monitoring platform of the pollution source treatment system according to claim 3, characterized in that: The determination of data validity includes the wastewater analyzer checking the data marking register value and the data quality label, and the flue gas analyzer checking the system status code and triggering a logic warning in combination with the communication parameters.

10. The dynamic monitoring platform of the pollution source treatment system according to claim 9, characterized in that: The comparison dynamic threshold includes quantifying the core indicator deviation rate and matching the compliance range according to the device type.

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