DCS card isolation terminal with intelligent monitoring and adaptive algorithm

Abstract

The application relates to the technical field of industrial automation control equipment, and discloses a DCS card piece isolation wiring terminal with intelligent monitoring and self-adaptive algorithm, which comprises a DCS card piece side wiring layer, an electromechanical isolation execution layer, an intelligent acquisition control layer, an on-site equipment wiring layer and a public power supply communication module. By acquiring environmental temperature and humidity and operation time variables, a self-adaptive insulation determination threshold value is compensated to generate, a time series data set is constructed to perform a one-dimensional linear regression fitting, insulation deterioration rate data is generated, preset parameter output micro-voltage pulse signals are output according to the rate, differential operation is performed on the total aliasing signal data collected, disturbance components are removed and process signal data is reconstructed, and when insulation resistance data is less than the lower limit of a threshold value, an instruction is sent to cut off the electrical connection. The application realizes lossless online inspection of a line and dynamic adjustment of a threshold value, avoids false alarms caused by a fixed lower limit under complex working conditions, and improves the reliability of evaluation and protection.

Description

Technical Field

[0001] This invention relates to the field of industrial automation control equipment technology, specifically to a DCS card isolation terminal block with intelligent monitoring and adaptive algorithms. Background Technology

[0002] DCS card isolation terminals are standard connection devices in industrial automation control systems. They are mainly connected in series between the DCS system cards in the control room and the field measuring instruments or actuators. The core function of this device is to provide reliable electrical isolation and surge protection while maintaining the electrical signal connection and transmission between the two sides. It prevents abnormal signals such as overvoltages that may occur in the field from entering the control room cards, thereby ensuring the safe operation of the control system hardware.

[0003] In existing industrial control sites, some isolation terminals integrate basic insulation monitoring modules. Under normal circumstances, technicians will pre-input a fixed lower limit value of insulation resistance into the microprocessor inside the terminal as a warning judgment benchmark. When the terminal detects that the insulation resistance of the signal measurement circuit is reduced due to external factors and the actual resistance value falls below the pre-set fixed lower limit value, the terminal will output an alarm signal to the outside or trigger a hardware cut-off action to prevent potential grounding faults from causing system shutdown.

[0004] However, existing isolation terminals have technical defects in terms of poor accuracy in insulation condition assessment during long-term operation. The actual operating conditions of industrial cabinets are complex. The resistance of cable insulation materials decreases as the ambient temperature rises. In addition, surface moisture adhesion in high humidity environments and dust accumulation during long-term operation will generate additional leakage current, causing the insulation resistance to decay naturally. Existing insulation monitoring solutions usually use fixed lower warning limits and cannot dynamically adjust the insulation judgment benchmark according to the real-time ambient temperature and humidity fluctuations of the cabinet and the cumulative operation time of the equipment. This single judgment mechanism makes it easy for the terminals to trigger warnings due to normal fluctuations in resistance when facing non-real short-circuit fault conditions such as high temperature, high humidity or natural aging, resulting in false alarms and reducing the reliability of daily insulation condition monitoring. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a DCS card isolation terminal block with intelligent monitoring and adaptive algorithms. This solves the problem that existing isolation terminals use a single, fixed lower limit for insulation warning, which cannot be dynamically adjusted based on real-world operating conditions such as temperature fluctuations, high humidity, and long-term equipment aging. This leads to frequent false alarms and inaccurate insulation status assessments.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a DCS card isolation terminal with intelligent monitoring and adaptive algorithm, wherein the DCS card isolation terminal with intelligent monitoring and adaptive algorithm is connected in series between the signal terminal of the external DCS system and the cable of the local instrument, and the DCS card isolation terminal with intelligent monitoring and adaptive algorithm is configured with program logic to execute the following control steps: The ambient temperature and humidity data of the space where the DCS card isolation terminal with intelligent monitoring and adaptive algorithm is located are obtained, and the compensation calculation is performed in combination with the initial input basic insulation threshold parameters to generate an adaptive insulation judgment threshold. Historical insulation resistance data are extracted according to a preset sampling period to construct a time series dataset. A univariate linear regression fitting calculation is performed on the time series dataset to generate insulation degradation rate data and initial state reference data. Based on the determination result of the insulation degradation rate data, the first preset parameter or the second preset parameter is retrieved, and a micro voltage pulse signal is output to the internal signal measurement circuit according to the retrieved first preset parameter or the second preset parameter. The electrical signal characteristics in the signal measurement loop are collected, and total aliasing signal data is generated based on the electrical signal characteristics. Differential operation is performed on the total aliasing signal data to separate the disturbance component data generated by the micro voltage pulse signal from the total aliasing signal data, process signal component data is extracted, and the process signal data reconstructed from the process signal component data is output to the external DCS system. Calculate the current insulation resistance data. When the insulation resistance data is less than the lower limit of the adaptive insulation judgment threshold, issue a trip control command to cut off the internal electrical connection path.

[0007] Preferably, the step of performing compensation calculations based on the initial input basic insulation threshold parameters to generate an adaptive insulation judgment threshold includes: Receive channel type data sent by the external DCS system, parse the channel type data and match the corresponding set value, and retrieve the basic insulation threshold parameter; Retrieve a preset temperature compensation data table, use the ambient temperature variable data as the input index to perform matching calculations, and generate a temperature correction coefficient. Retrieve a preset humidity compensation data table, use the environmental humidity variable data as the input index to perform matching calculations, and generate a humidity correction coefficient; The cumulative operation time variable is obtained, and the dust aging attenuation coefficient is calculated by combining the preset aging conversion logic. The aging conversion logic is as follows: multiple time intervals are pre-divided and corresponding fixed attenuation coefficient values ​​are assigned. The time interval to which the cumulative operation time variable belongs is determined, and the corresponding fixed attenuation coefficient value is extracted as the dust aging attenuation coefficient. The basic insulation threshold parameter, the temperature correction coefficient, the humidity correction coefficient, and the dust accumulation aging attenuation coefficient are extracted and multiplied to generate the adaptive insulation judgment threshold.

[0008] Preferably, the step of extracting historical insulation resistance data according to a preset sampling period and constructing a time series dataset includes: Obtain the timestamp data corresponding to the historical insulation resistance data; A sliding time window with preset capacity parameters is established, and the matched historical insulation resistance data and the timestamp data are combined into data pairs, and the data pairs are stored in the sliding time window to construct the time series dataset. When the number of data pairs in the time series dataset reaches the preset capacity parameter, the sliding time window is controlled to update the data pairs in the time series dataset according to the first-in-first-out logic rule.

[0009] Preferably, after the step of performing univariate linear regression fitting calculation to generate insulation degradation rate data, the method further includes: The insulation degradation rate data is numerically compared with zero; When the insulation degradation rate data is greater than or equal to zero, the insulation state is determined to be stable, an insulation stability status identifier is generated, and the insulation stability status identifier is written into the pre-allocated status register flag bit; When the insulation degradation rate data is less than zero, the insulation state is determined to be in a continuous decline stage, and an insulation vulnerability warning signal is generated. The lower limit of the adaptive insulation judgment threshold is used as the expected data of the fitted insulation resistance value and substituted into the operation logic determined by the univariate linear regression fitting calculation. The insulation degradation rate data and the initial state reference data are combined to perform inverse calculation to generate the remaining time margin data for reaching the lower limit of the adaptive insulation judgment threshold. The insulation vulnerability warning signal and the remaining time margin data are written into the status register flag bit.

[0010] Preferably, the step of outputting a micro-voltage pulse signal to the signal measurement circuit according to the retrieved first preset parameter or second preset parameter includes: Read the identification data stored in the flag bits of the status register; When the status register flag bit stores the insulation stability status identifier, according to the pre-configured time-sharing peak-shifting scheduling logic, the grouping and rotation timing allocation of multiple parallel-running signal measurement circuits is performed, and a regular inspection command is sent according to the allocated timing result, and the micro voltage pulse signal is generated according to the first preset parameters. When the status register flag bit stores the insulation vulnerability warning signal, a dynamic protection inspection command is sent to generate the micro voltage pulse signal according to the second preset parameters. The protection voltage amplitude data and protection pulse width data included in the second preset parameters are respectively smaller than the standard voltage amplitude data and standard pulse width data included in the first preset parameters.

[0011] Preferably, the step of performing differential operations on the total aliasing signal data to separate the disturbance component data generated by the micro-voltage pulse signal from the total aliasing signal data includes: In the separation and cancellation model of the total aliasing signal data and the first preset parameter or the second preset parameter input signal used to output the micro voltage pulse signal, the total aliasing signal data is composed of the superposition of the disturbance component data and the process signal component data. Within the signal separation and cancellation model, a corresponding virtual disturbance reference signal is generated in the digital domain according to the first preset parameter or the second preset parameter; The control signal separation and cancellation model performs a differential operation by synchronously subtracting the total aliased signal data from the virtual disturbance reference signal in the time domain, eliminating the disturbance component data, and reconstructing the separated process signal component data to generate the process signal data.

[0012] Preferably, before issuing the trip control command, the method further includes: The adaptive insulation judgment threshold is multiplied by the early warning judgment coefficient to generate a mild early warning threshold data. The adaptive insulation judgment threshold is multiplied by the fault judgment coefficient to generate a severe fault threshold data. The severe fault threshold data is the set lower limit of the adaptive insulation judgment threshold. The insulation resistance data is compared with the mild warning threshold data and the severe fault threshold data, respectively. When the insulation resistance data is less than the mild warning threshold data and greater than or equal to the severe fault threshold data, the continuous frame number filter counter is started to perform the first accumulation counting operation; When the first accumulated count value of the continuous frame number filter counter reaches the first preset continuous frame number parameter, pre-maintenance work order application data is generated, and the local three-color status indicator light is driven to display a yellow warning status. When the insulation resistance data recovers to a level greater than or equal to the mild warning threshold data, the first accumulated count value of the continuous frame number filter counter is cleared.

[0013] Preferably, the step of issuing a trip control command to disconnect the internal electrical connection path includes: When the insulation resistance data is less than the severe fault threshold data, the continuous frame number filter counter is started to perform the second accumulation counting operation. When the second accumulated count value of the continuous frame number filter counter reaches the second preset continuous frame number parameter, a trip control command is issued to trigger the electromagnetic trip coil, driving the local three-color status indicator to display a red fault status. The current insulation resistance data, ambient temperature variable data, ambient humidity variable data, and isolation disconnect switch operation status data are captured, and combined with millisecond-level timestamps to package and generate SOE event record data, which is then uploaded to the external DCS system. The electromagnetic trip coil drives the isolating switch to perform a disconnection action, cutting off the electrical connection path; after disconnection, the mechanical anti-misoperation locking mechanism is triggered to physically lock the closing circuit and cut off the closing electrical control signal; When the insulation resistance data recovers to a level greater than or equal to the severe fault threshold data, the second accumulated count value of the continuous frame number filter counter is cleared.

[0014] Preferably, after the electrical control signal for cutting off the closing is cut off, the method further includes: Keep the anti-misoperation padlock hole physically open to allow access to external maintenance padlocks; Maintain the internal cable connection status, connect to the signal measurement circuit through the external test interface, and receive the line insulation resistance retest operation performed by the external testing instrument.

[0015] A DCS card isolation terminal block with intelligent monitoring and adaptive algorithm, comprising the hardware structure of the DCS card isolation terminal block with intelligent monitoring and adaptive algorithm, specifically including: DCS card side wiring layer, used to interface with the signal terminals of external DCS systems; The local equipment wiring layer is used to connect cables to local instruments and is equipped with an external test interface; The electromechanical isolation execution layer is electrically connected between the DCS card side wiring layer and the local equipment wiring layer, and has built-in isolation disconnect switch, electromagnetic trip coil, passive position feedback contact, surge absorption circuit, mechanical anti-misoperation locking mechanism and anti-misoperation padlock hole; The public power supply communication module integrates the power supply circuit and the RS485 bus communication circuit. The intelligent acquisition and control layer integrates a microprocessor, a programmable micro-high voltage insulation sampling source, a leakage current sampling differential amplifier circuit, a temperature and humidity acquisition module, and a local three-color status indicator light. The microprocessor has a built-in internal storage unit.

[0016] This invention provides a DCS card isolation terminal block with intelligent monitoring and adaptive algorithms. It has the following advantages: 1. This invention combines ambient temperature variable data, ambient humidity variable data, and dust aging attenuation coefficient based on cumulative commissioning time variable to dynamically compensate and calculate the basic insulation threshold parameters to generate an adaptive insulation judgment threshold. This achieves adaptive adjustment of the insulation status judgment benchmark under different cabinet operating conditions, avoiding false alarms caused by using a fixed warning lower limit in high humidity or long-term aging environments, thereby ensuring the accuracy of the insulation status assessment results of the isolation terminal and the reliability of status monitoring.

[0017] 2. This invention generates insulation degradation rate data by constructing a time series dataset and performing univariate linear regression fitting calculation. When the insulation condition is in a continuous decline stage, a second preset parameter with smaller voltage amplitude and pulse width is retrieved. The signal separation and cancellation model is used to remove disturbance component data to reconstruct process signal data. This enables non-destructive inspection of degraded lines without interrupting the continuous receiving action of the external DCS system. It can provide remaining time margin data through inverse calculation and ensure continuous transmission of process signals.

[0018] 3. This invention sets mild warning threshold data and severe fault threshold data, and combines them with a continuous frame number filter counter to perform accumulation and clearing operations respectively. It also uses an electromagnetic trip coil to drive the isolating disconnect switch to cut off the electrical connection path and trigger the mechanical anti-misoperation locking mechanism to physically lock the closing circuit. This achieves graded response to the line deterioration process and isolation of fault nodes, effectively filtering out the risk of malfunction caused by transient interference, and eliminating potential safety hazards caused by improper closing before external maintenance from a hardware perspective. Attached Figure Description

[0019] Figure 1 This is a block diagram illustrating the internal hardware electrical and signal processing principles of the present invention; Figure 2 This is a flowchart of the adaptive insulation determination threshold generation and degradation rate calculation of the present invention. Figure 3 This is a flowchart illustrating the principle and execution process of the adaptive non-destructive inspection and signal stripping algorithm of the present invention. Figure 4 This is a flowchart of the intelligent hierarchical linkage, filtering anti-interference and fault physical isolation control of the present invention. Detailed Implementation

[0020] The technical solutions in 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] Example: Please see the appendix Figure 1 - Appendix Figure 4 This invention provides a DCS card isolation terminal with intelligent monitoring and adaptive algorithm, which is connected in series between the signal terminal of the external DCS system and the cable of the local instrument.

[0022] The DCS card isolation terminal block with intelligent monitoring and adaptive algorithms includes: DCS card side wiring layer; Electromechanical isolation execution layer; Intelligent data acquisition and control layer; Local equipment wiring layer; Public power supply communication module.

[0023] The DCS card-side wiring layer is located on the top end face of the DCS card isolation terminal with intelligent monitoring and adaptive algorithms. The DCS card-side wiring layer includes an anti-loosening spring clamping mechanism and is used to connect to the signal terminals of external DCS systems.

[0024] The electromechanical isolation actuator layer is located below the DCS card side wiring layer. The electromechanical isolation actuator layer has a built-in isolation disconnect switch, electromagnetic trip coil, passive position feedback contact and surge absorption circuit. The electromechanical isolation actuator layer is electrically connected between the DCS card side wiring layer and the local equipment wiring layer.

[0025] The intelligent acquisition and control layer is located below the electromechanical isolation execution layer. The intelligent acquisition and control layer integrates a microprocessor, a programmable micro high voltage insulation sampling source, a leakage current sampling differential amplifier circuit, and a temperature and humidity acquisition module. The microprocessor also has a built-in internal storage unit.

[0026] The local device wiring layer is located below the intelligent acquisition and control layer. The local device wiring layer and the DCS card side wiring layer form a physical partition. The local device wiring layer is equipped with an external test interface and is used to connect the cables of local instruments.

[0027] The public power supply communication module is electrically connected to the intelligent acquisition and control layer. The public power supply communication module integrates the power supply circuit and the RS485 bus communication circuit.

[0028] After the DCS card with intelligent monitoring and adaptive algorithms performs a power-on startup operation at the isolation terminal, the common power supply communication module provides the operating voltage to the intelligent acquisition and control layer.

[0029] The microprocessor in the intelligent acquisition and control layer performs initialization operations. The microprocessor acquires the ambient temperature and humidity data in the space where the DCS card isolation terminal with intelligent monitoring and adaptive algorithm is located through the temperature and humidity acquisition module.

[0030] The microprocessor combines the initial input basic insulation threshold parameters, ambient temperature variable data, and ambient humidity variable data to perform compensation calculations and generate an adaptive insulation judgment threshold.

[0031] The microprocessor extracts historical insulation resistance data according to the sampling period preset in the microprocessor's internal storage unit, and constructs a time series dataset in the microprocessor's internal storage unit.

[0032] The microprocessor performs a univariate linear regression fitting calculation on the time series dataset, calculates and outputs insulation degradation rate data.

[0033] When the insulation degradation rate data is greater than or equal to zero, the microprocessor determines that the insulation state is stable. The programmable micro high voltage insulation sampling source retrieves the first preset parameters pre-configured in the internal storage unit of the microprocessor and outputs a micro voltage pulse signal to the signal measurement circuit composed of the DCS card side wiring layer and the local equipment wiring layer according to the first preset parameters.

[0034] When the insulation degradation rate data is less than zero, the microprocessor determines that the insulation state is in a continuous decline stage. The microprocessor adjusts the output state of the programmable micro high voltage insulation sampling source, retrieves the second preset parameter pre-configured in the microprocessor's internal storage unit, and outputs a micro voltage pulse signal according to the second preset parameter. The voltage amplitude and pulse width of the second preset parameter are both less than the first preset parameter.

[0035] During the period when the programmable micro-high voltage insulation sampling source outputs a micro-voltage pulse signal, the leakage current sampling differential amplifier circuit collects the electrical signal characteristics in the signal measurement circuit in real time, and generates total aliasing signal data based on the electrical signal characteristics.

[0036] The microprocessor performs differential operations on the total aliasing signal data, separates the disturbance component data generated by the micro voltage pulse signal from the total aliasing signal data, reconstructs the process signal data, and outputs the process signal data to the DCS card side wiring layer.

[0037] The microprocessor calculates the current insulation resistance data and compares the insulation resistance data with the adaptive insulation judgment threshold.

[0038] When the insulation resistance data is less than the lower limit of the adaptive insulation judgment threshold, the microprocessor sends a trip control command to the electromechanical isolation execution layer.

[0039] After receiving the trip control command, the electromechanical isolation execution layer triggers the electromagnetic trip coil.

[0040] The isolating switch performs an opening action under the drive of the electromagnetic trip coil, cutting off the electrical connection path between the DCS card side wiring layer and the local equipment wiring layer. After the isolating switch opens, it locks the closing circuit.

[0041] With the isolating disconnect switch open, external testing instruments can be connected to the signal measurement circuit through the external test interface of the local equipment wiring layer to perform line insulation resistance retesting.

[0042] Based on the aforementioned DCS card isolation terminal with intelligent monitoring and adaptive algorithm, this invention also provides a specific implementation method for generating an adaptive insulation determination threshold.

[0043] The microprocessor within the intelligent acquisition and control layer receives channel type data from the external DCS system via the RS485 bus communication circuit integrated within the public power supply communication module.

[0044] The channel type data includes analog input identifiers, analog output identifiers, digital input identifiers, and digital output identifiers.

[0045] The microprocessor parses the channel type data, matches the corresponding set value in the microprocessor's internal storage unit, and retrieves the basic insulation threshold parameter.

[0046] The temperature and humidity acquisition module built into the intelligent acquisition and control layer performs sampling operations according to the set sampling period.

[0047] The temperature and humidity acquisition module collects ambient temperature and humidity data within the space where the DCS card with intelligent monitoring and adaptive algorithms are located.

[0048] The temperature and humidity acquisition module transmits ambient temperature and humidity data to the microprocessor.

[0049] The microprocessor retrieves a pre-set temperature compensation data table from its internal storage unit, uses the ambient temperature variable data as input index to perform matching calculations, and generates a temperature correction coefficient.

[0050] The temperature correction factor is used to compensate for the decrease in resistance of cable insulation materials caused by an increase in ambient temperature.

[0051] The microprocessor retrieves a preset humidity compensation data table from its internal storage unit, uses the ambient humidity variable data as input index to perform matching calculations, and generates a humidity correction coefficient.

[0052] The humidity correction factor is used to offset the increase in leakage current caused by water vapor adhesion on surfaces in high-humidity environments.

[0053] The microprocessor reads data from its built-in internal timer to obtain the cumulative commissioning time variable of the DCS card's isolated terminal block with intelligent monitoring and adaptive algorithms.

[0054] The microprocessor calculates and generates the dust accumulation aging attenuation coefficient based on the cumulative operation time variable and the aging calculation logic preset in the microprocessor's internal storage unit. The aging calculation logic is as follows: multiple time intervals are pre-divided in the microprocessor's internal storage unit, and a corresponding fixed attenuation coefficient value is assigned to each time interval. The microprocessor determines the time interval to which the cumulative operation time variable belongs and extracts the corresponding fixed attenuation coefficient value as the dust accumulation aging attenuation coefficient.

[0055] The microprocessor extracts the basic insulation threshold parameters, temperature correction coefficient, humidity correction coefficient, and dust accumulation aging attenuation coefficient, performs multiplication operations, and generates an adaptive insulation judgment threshold.

[0056] The formula used by the microprocessor to calculate the adaptive insulation determination threshold is as follows:

[0057] In the formula, Indicates the adaptive insulation determination threshold. Indicates the basic insulation threshold parameter. This represents the temperature correction factor. This represents the humidity correction factor. This represents the dust accumulation and aging attenuation coefficient.

[0058] The microprocessor writes the generated adaptive insulation determination threshold into its internal memory.

[0059] In subsequent state assessment operations, the microprocessor calls the adaptive insulation judgment threshold as the real-time insulation state judgment benchmark value.

[0060] Based on the aforementioned DCS card isolation terminal with intelligent monitoring and adaptive algorithm, this invention also provides a specific implementation method for calculating insulation degradation rate data.

[0061] The microprocessor sequentially saves the insulation resistance data calculated in each sampling period to its internal storage unit as historical insulation resistance data. The microprocessor extracts the historical insulation resistance data according to the sampling period preset in its internal storage unit.

[0062] The microprocessor reads data from its built-in internal timer to obtain the timestamp data corresponding to the historical insulation resistance values.

[0063] The microprocessor establishes a sliding time window with preset capacity parameters in its internal memory unit.

[0064] The microprocessor combines the matched historical insulation resistance data with the timestamp data into a data pair and stores the data pair in a sliding time window.

[0065] The microprocessor constructs a time series dataset within a sliding time window.

[0066] When the number of data pairs in the time series dataset reaches the preset capacity parameter, the sliding time window updates the data pairs in the time series dataset according to the first-in-first-out logic rule.

[0067] The microprocessor retrieves the least squares regression function preset in the microprocessor's internal memory.

[0068] The microprocessor takes the time series dataset as input parameters and performs a univariate linear regression fitting calculation using the least squares regression function.

[0069] The microprocessor generates insulation degradation rate data and initial state reference data by fitting a univariate linear regression.

[0070] The calculation formula used by the microprocessor to perform univariate linear regression fitting is as follows:

[0071] In the formula, This represents the expected insulation resistance value calculated using univariate linear regression. Represents timestamp data, This represents the data on insulation degradation rate. This represents the initial state reference data.

[0072] The microprocessor extracts numerical values ​​of the insulation degradation rate data.

[0073] The microprocessor compares the insulation degradation rate data with a zero value.

[0074] When the insulation degradation rate data is greater than or equal to zero, the microprocessor determines that the insulation state of the isolation terminals of the DCS card with intelligent monitoring and adaptive algorithm is stable.

[0075] The microprocessor's internal memory has pre-allocated status register flag bits. The microprocessor generates an insulation stability status flag and writes the insulation stability status flag into the status register flag bits.

[0076] The intelligent acquisition and control layer integrates a local three-color status indicator light, and the microprocessor drives the local three-color status indicator light to display a green normal state.

[0077] When the insulation degradation rate data is less than zero, the microprocessor determines that the insulation status of the isolation terminals of the DCS card with intelligent monitoring and adaptive algorithm is in a continuous decline phase.

[0078] The microprocessor generates an insulation vulnerability warning signal based on the determination that the insulation condition is in a continuous decline phase.

[0079] The microprocessor retrieves the adaptive insulation determination threshold stored in the microprocessor's internal memory.

[0080] The microprocessor uses the adaptive insulation judgment threshold as the expected data of the fitted insulation resistance value and substitutes it into the calculation formula. It then performs inverse calculation by combining the insulation degradation rate data and the initial state reference data to generate the remaining time margin data for reaching the fault threshold.

[0081] The microprocessor writes the insulation vulnerability warning signal and the remaining time margin data into the status register flag bit.

[0082] When the microprocessor performs subsequent inspection operations, it reads the status register flags.

[0083] Based on the read insulation vulnerability warning signal, the microprocessor triggers parameter adjustment operations on the programmable micro-high voltage insulation sampling source.

[0084] Based on the aforementioned DCS card isolation terminal with intelligent monitoring and adaptive algorithm, this invention also provides a specific implementation method for adaptive non-destructive inspection and signal stripping based on deterioration status.

[0085] The microprocessor reads the identification data stored in the flag bits of the status register.

[0086] When the status register flag contains an insulation stability status indicator, the microprocessor retrieves the pre-configured time-sharing peak-shaving scheduling logic from its internal memory. Based on the time-sharing peak-shaving scheduling logic, the microprocessor performs grouping and rotation timing allocation for multiple parallel-running signal measurement circuits, generates routine inspection instructions based on the allocated timing results, and sends the routine inspection instructions to the programmable micro high-voltage insulation sampling source.

[0087] After receiving a routine inspection command, the programmable micro high-voltage insulation sampling source retrieves the first preset parameters pre-configured in the microprocessor's internal storage unit.

[0088] The programmable micro-high voltage insulation sampling source generates micro-voltage pulse signals according to the first preset parameters.

[0089] The first preset parameters include standard voltage amplitude data and standard pulse width data.

[0090] The programmable micro-high voltage insulation sampling source will output the micro-voltage pulse signal generated according to the first preset parameters to the signal measurement circuit.

[0091] When the status register flag contains an insulation vulnerability warning signal, the microprocessor generates a dynamic protection inspection command and sends the command to the programmable micro high voltage insulation sampling source.

[0092] After receiving the dynamic protection inspection command, the programmable micro high voltage insulation sampling source retrieves the second preset parameter pre-configured in the internal storage unit of the microprocessor.

[0093] The programmable micro-high voltage insulation sampling source generates micro-voltage pulse signals according to the second preset parameters.

[0094] The second preset parameter includes protection voltage amplitude data and protection pulse width data.

[0095] The value of the protection voltage amplitude data is less than the value of the standard voltage amplitude data, and the value of the protection pulse width data is less than the value of the standard pulse width data.

[0096] The programmable micro-high voltage insulation sampling source will output the micro-voltage pulse signal generated according to the second preset parameters to the signal measurement circuit.

[0097] During the time period during which the programmable micro-high voltage insulation sampling source outputs a micro-voltage pulse signal to the signal measurement circuit, the leakage current sampling differential amplifier circuit acquires the electrical signal characteristics in the signal measurement circuit in real time.

[0098] The leakage current sampling differential amplifier circuit generates total aliasing signal data based on the characteristics of the acquired electrical signal.

[0099] The total aliasing signal data is composed of the disturbance component data generated by the injection of micro-voltage pulse signal and the process signal component data superimposed.

[0100] The leakage current sampling differential amplifier circuit transmits the total aliasing signal data to the microprocessor.

[0101] The microprocessor retrieves the signal separation and cancellation model preset in the microprocessor's internal memory unit.

[0102] The microprocessor separates and cancels the total aliasing signal data with the first or second preset parameter input signal used by the current output micro-voltage pulse signal in the model.

[0103] Within the signal separation and cancellation model, the microprocessor generates a corresponding virtual disturbance reference signal in the digital domain based on either a first preset parameter or a second preset parameter.

[0104] The signal separation and cancellation model performs a differential operation by synchronously subtracting the total aliased signal data from the virtual disturbance reference signal in the time domain.

[0105] The microprocessor uses differential operations to remove disturbance components from the total aliased signal data and reconstructs the separated process signal components to generate process signal data.

[0106] The microprocessor uses the following formulas to perform differential operations and generate process signal data:

[0107] In the formula, This represents the process signal data generated by the reconstructed data. Indicates total aliasing signal data. This represents the perturbation component data.

[0108] The microprocessor outputs the reconstructed process signal data to the DCS card side wiring layer.

[0109] The DCS card side wiring layer transmits process signal data to the signal terminal of the external DCS system, enabling the external DCS system to continuously receive process signal data.

[0110] Based on the aforementioned DCS card isolation terminal with intelligent monitoring and adaptive algorithms, this invention also provides specific implementation methods for intelligent hierarchical linkage and physical fault isolation.

[0111] The microprocessor calculates and generates the current insulation resistance data based on the characteristics of the electrical signal acquired by the leakage current sampling differential amplifier circuit.

[0112] The microprocessor retrieves the adaptive insulation determination threshold stored in the microprocessor's internal memory.

[0113] The microprocessor's internal storage unit is pre-configured with early warning judgment coefficients and fault judgment coefficients.

[0114] The value of the warning determination coefficient is greater than the value of the fault determination coefficient.

[0115] The microprocessor multiplies the adaptive insulation judgment threshold with the early warning judgment coefficient to generate mild early warning threshold data.

[0116] The microprocessor multiplies the adaptive insulation determination threshold with the fault determination coefficient to generate severe fault threshold data.

[0117] The microprocessor compares the insulation resistance data with the mild warning threshold data and the severe fault threshold data, respectively.

[0118] The microprocessor's internal storage unit is pre-allocated with a continuous frame count filter counter and pre-configured with a first preset continuous frame count parameter and a second preset continuous frame count parameter.

[0119] When the insulation resistance data is less than the mild warning threshold data and the insulation resistance data is greater than or equal to the severe fault threshold data, the microprocessor starts the continuous frame number filter counter to perform the first accumulation count operation.

[0120] When the insulation resistance data recovers to a level greater than or equal to the mild warning threshold, the microprocessor performs a zeroing operation on the continuous frame number filter counter.

[0121] When the first accumulated count value of the continuous frame count filter counter reaches the first preset continuous frame count parameter, the microprocessor determines that the signal measurement circuit has experienced slight insulation degradation.

[0122] The microprocessor generates pre-maintenance work order application data based on the determination of mild insulation degradation.

[0123] The microprocessor sends the pre-maintenance work order application data to the external DCS system through the RS485 bus communication circuit integrated in the public power supply communication module.

[0124] The intelligent acquisition and control layer also integrates a local three-color status indicator light, which is driven by a microprocessor to display a yellow warning status.

[0125] When the insulation resistance data is less than the severe fault threshold data, the microprocessor starts the continuous frame number filter counter to perform the second accumulation count operation.

[0126] When the second accumulated count value of the continuous frame count filter counter reaches the second preset continuous frame count parameter, the microprocessor determines that a serious grounding fault has occurred in the signal measurement circuit.

[0127] The microprocessor sends a trip control command to the electromechanical isolation execution layer, and the microprocessor drives the local three-color status indicator to display a red fault status.

[0128] The microprocessor captures current insulation resistance data, ambient temperature variable data, ambient humidity variable data, and the operating status data of the isolating switch, and combines this with millisecond-level timestamps generated by the microprocessor's built-in internal timer to package and generate SOE event log data. The microprocessor then uploads the SOE event log data to the external DCS system via the RS485 bus communication circuit integrated in the public power supply communication module. After receiving the trip control command, the electromechanical isolation execution layer triggers the electromagnetic trip coil.

[0129] The isolating disconnector performs the disconnection action under the drive of the electromagnetic trip coil.

[0130] The isolating disconnect switch cuts off the electrical connection between the DCS card side wiring layer and the local equipment wiring layer, achieving single-point fault isolation.

[0131] The electromechanical isolation execution layer is equipped with a mechanical anti-misoperation locking mechanism.

[0132] After the isolating switch is disconnected, the mechanical anti-misoperation locking mechanism is triggered accordingly, physically locking the closing circuit and cutting off the closing electrical control signal of the isolating switch.

[0133] The electromechanical isolation actuator layer is also equipped with a padlock hole to prevent misoperation.

[0134] With the isolating switch open, the anti-misoperation padlock hole is physically open and is used to connect an external maintenance padlock.

[0135] With the isolating disconnect switch open, external testing instruments can be connected to the signal measurement circuit through the external test interface of the local equipment wiring layer.

[0136] While maintaining the cable connection status within the wiring layer on the DCS card side, the external testing instrument performs a retest of the line insulation resistance.

[0137] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A DCS card isolation terminal with intelligent monitoring and adaptive algorithm, wherein the DCS card isolation terminal with intelligent monitoring and adaptive algorithm is connected in series between the signal terminal of the external DCS system and the cable of the local instrument, characterized in that, The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm is configured with program logic to perform the following control steps: The ambient temperature and humidity data of the space where the DCS card isolation terminal with intelligent monitoring and adaptive algorithm is located are obtained, and the compensation calculation is performed in combination with the initial input basic insulation threshold parameters to generate an adaptive insulation judgment threshold. Historical insulation resistance data are extracted according to a preset sampling period to construct a time series dataset. A univariate linear regression fitting calculation is performed on the time series dataset to generate insulation degradation rate data and initial state reference data. Based on the determination result of the insulation degradation rate data, the first preset parameter or the second preset parameter is retrieved, and a micro voltage pulse signal is output to the internal signal measurement circuit according to the retrieved first preset parameter or the second preset parameter. The electrical signal characteristics in the signal measurement loop are collected, and total aliasing signal data is generated based on the electrical signal characteristics. Differential operation is performed on the total aliasing signal data to separate the disturbance component data generated by the micro voltage pulse signal from the total aliasing signal data, process signal component data is extracted, and the process signal data reconstructed from the process signal component data is output to the external DCS system. Calculate the current insulation resistance data. When the insulation resistance data is less than the lower limit of the adaptive insulation judgment threshold, issue a trip control command to cut off the internal electrical connection path.

2. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 1, characterized in that, The step of performing compensation calculations based on the initial input basic insulation threshold parameters to generate an adaptive insulation judgment threshold includes: Receive channel type data sent by the external DCS system, parse the channel type data and match the corresponding set value, and retrieve the basic insulation threshold parameter; Retrieve a preset temperature compensation data table, use the ambient temperature variable data as the input index to perform matching calculations, and generate a temperature correction coefficient. Retrieve a preset humidity compensation data table, use the environmental humidity variable data as the input index to perform matching calculations, and generate a humidity correction coefficient; The cumulative operation time variable is obtained, and the dust aging attenuation coefficient is calculated by combining the preset aging conversion logic. The aging conversion logic is as follows: multiple time intervals are pre-divided and corresponding fixed attenuation coefficient values ​​are assigned. The time interval to which the cumulative operation time variable belongs is determined, and the corresponding fixed attenuation coefficient value is extracted as the dust aging attenuation coefficient. The basic insulation threshold parameter, the temperature correction coefficient, the humidity correction coefficient, and the dust accumulation aging attenuation coefficient are extracted and multiplied to generate the adaptive insulation judgment threshold.

3. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 2, characterized in that, The step of extracting historical insulation resistance data according to a preset sampling period and constructing a time series dataset includes: Obtain the timestamp data corresponding to the historical insulation resistance data; A sliding time window with preset capacity parameters is established, and the matched historical insulation resistance data and the timestamp data are combined into data pairs, and the data pairs are stored in the sliding time window to construct the time series dataset. When the number of data pairs in the time series dataset reaches the preset capacity parameter, the sliding time window is controlled to update the data pairs in the time series dataset according to the first-in-first-out logic rule.

4. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 3, characterized in that, After the step of performing univariate linear regression fitting calculation to generate insulation degradation rate data, the method further includes: The insulation degradation rate data is numerically compared with zero; When the insulation degradation rate data is greater than or equal to zero, the insulation state is determined to be stable, an insulation stability status identifier is generated, and the insulation stability status identifier is written into the pre-allocated status register flag bit; When the insulation degradation rate data is less than zero, the insulation state is determined to be in a continuous decline stage, and an insulation vulnerability warning signal is generated. The lower limit of the adaptive insulation judgment threshold is used as the expected data of the fitted insulation resistance value and substituted into the operation logic determined by the univariate linear regression fitting calculation. The insulation degradation rate data and the initial state reference data are combined to perform inverse calculation to generate the remaining time margin data for reaching the lower limit of the adaptive insulation judgment threshold. The insulation vulnerability warning signal and the remaining time margin data are written into the status register flag bit.

5. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 4, characterized in that, The step of outputting a micro-voltage pulse signal to the signal measurement circuit according to the retrieved first preset parameter or second preset parameter includes: Read the identification data stored in the flag bits of the status register; When the status register flag bit stores the insulation stability status identifier, according to the pre-configured time-sharing peak-shifting scheduling logic, the grouping and rotation timing allocation of multiple parallel-running signal measurement circuits is performed, and a regular inspection command is sent according to the allocated timing result, and the micro voltage pulse signal is generated according to the first preset parameters. When the status register flag bit stores the insulation vulnerability warning signal, a dynamic protection inspection command is sent to generate the micro voltage pulse signal according to the second preset parameters. The protection voltage amplitude data and protection pulse width data included in the second preset parameters are respectively smaller than the standard voltage amplitude data and standard pulse width data included in the first preset parameters.

6. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 5, characterized in that, The step of performing differential operations on the total aliasing signal data to separate the disturbance component data generated by the micro-voltage pulse signal from the total aliasing signal data includes: In the separation and cancellation model of the total aliasing signal data and the first preset parameter or the second preset parameter input signal used to output the micro voltage pulse signal, the total aliasing signal data is composed of the superposition of the disturbance component data and the process signal component data. Within the signal separation and cancellation model, a corresponding virtual disturbance reference signal is generated in the digital domain according to the first preset parameter or the second preset parameter; The control signal separation and cancellation model performs a differential operation by synchronously subtracting the total aliased signal data from the virtual disturbance reference signal in the time domain, eliminating the disturbance component data, and reconstructing the separated process signal component data to generate the process signal data.

7. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 6, characterized in that, Before issuing the trip control command, the following is also included: The adaptive insulation judgment threshold is multiplied by the early warning judgment coefficient to generate a mild early warning threshold data. The adaptive insulation judgment threshold is multiplied by the fault judgment coefficient to generate a severe fault threshold data. The severe fault threshold data is the set lower limit of the adaptive insulation judgment threshold. The insulation resistance data is compared with the mild warning threshold data and the severe fault threshold data, respectively. When the insulation resistance data is less than the mild warning threshold data and greater than or equal to the severe fault threshold data, the continuous frame number filter counter is started to perform the first accumulation counting operation; When the first accumulated count value of the continuous frame number filter counter reaches the first preset continuous frame number parameter, pre-maintenance work order application data is generated, and the local three-color status indicator light is driven to display a yellow warning status. When the insulation resistance data recovers to a level greater than or equal to the mild warning threshold data, the first accumulated count value of the continuous frame number filter counter is cleared.

8. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 7, characterized in that, The step of issuing a trip control command to disconnect the internal electrical connection path includes: When the insulation resistance data is less than the severe fault threshold data, the continuous frame number filter counter is started to perform the second accumulation counting operation. When the second accumulated count value of the continuous frame number filter counter reaches the second preset continuous frame number parameter, a trip control command is issued to trigger the electromagnetic trip coil, driving the local three-color status indicator to display a red fault status. The current insulation resistance data, ambient temperature variable data, ambient humidity variable data, and isolation disconnect switch operation status data are captured, and combined with millisecond-level timestamps to package and generate SOE event record data, which is then uploaded to the external DCS system. The electromagnetic trip coil drives the isolating switch to perform a disconnection action, cutting off the electrical connection path; after disconnection, the mechanical anti-misoperation locking mechanism is triggered to physically lock the closing circuit and cut off the closing electrical control signal; When the insulation resistance data recovers to a level greater than or equal to the severe fault threshold data, the second accumulated count value of the continuous frame number filter counter is cleared.

9. The DCS card isolation terminal block with intelligent monitoring and adaptive algorithm according to claim 8, characterized in that, After the electrical control signal for cutting off the closing circuit is cut off, the following is also included: Keep the anti-misoperation padlock hole physically open to allow access to external maintenance padlocks; Maintain the internal cable connection status, connect to the signal measurement circuit through the external test interface, and receive the line insulation resistance retest operation performed by the external testing instrument.

10. A DCS card isolation terminal block with intelligent monitoring and adaptive algorithm, characterized in that, The hardware structure of the DCS card isolation terminal block with intelligent monitoring and adaptive algorithm as described in any one of claims 1 to 9 specifically includes: DCS card side wiring layer, used to interface with the signal terminals of external DCS systems; The local equipment wiring layer is used to connect cables to local instruments and is equipped with an external test interface; The electromechanical isolation execution layer is electrically connected between the DCS card side wiring layer and the local equipment wiring layer, and has built-in isolation disconnect switch, electromagnetic trip coil, passive position feedback contact, surge absorption circuit, mechanical anti-misoperation locking mechanism and anti-misoperation padlock hole; The public power supply communication module integrates the power supply circuit and the RS485 bus communication circuit. The intelligent acquisition and control layer integrates a microprocessor, a programmable micro-high voltage insulation sampling source, a leakage current sampling differential amplifier circuit, a temperature and humidity acquisition module, and a local three-color status indicator light. The microprocessor has a built-in internal storage unit.

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