Rotary kiln power distribution room control cabinet temperature monitoring system of pcs7 and wincc

Abstract

This invention relates to the field of industrial temperature monitoring technology, specifically to a temperature monitoring system for a rotary kiln power distribution room control cabinet using PCS7 and WinCC. The system includes a temperature sensing unit, a signal isolation and conditioning unit, an analog-to-digital converter and processing unit, a central control unit, and a monitoring and display unit. The temperature sensing unit consists of multiple PT100 resistance thermometers, collecting analog temperature signals from each measurement point. The signal isolation and conditioning unit uses an intelligent isolation safety barrier integrating a dynamic noise suppression circuit and an adaptive range matching module to achieve signal noise filtering and range normalization. The analog-to-digital converter and processing unit incorporates a multi-level digital filtering engine and a nonlinear temperature compensation logic module to complete analog-to-digital conversion and PT100 nonlinear hardware compensation. The central control unit performs secondary correction of residual errors through a piecewise fitting program, and the monitoring and display unit displays the temperature in real time and provides alarms, enabling unattended, continuous, and high-precision monitoring of the control cabinet temperature.

Description

Technical Field

[0001] This invention relates to the field of industrial temperature monitoring technology, and more specifically, to a temperature monitoring system for a rotary kiln power distribution room control cabinet using PCS7 and WinCC. Background Technology

[0002] Industrial temperature monitoring is a crucial technology. Currently, the instruments and electrical components inside the control cabinet of a rotary kiln power distribution room are densely packed, making them prone to localized overheating during long-term operation. Existing temperature monitoring methods mainly rely on daily manual inspections, with inspectors using handheld temperature measuring devices to check each point. This method cannot achieve continuous real-time temperature data acquisition, and sudden temperature changes or continuous temperature rises during inspection intervals are difficult to detect in a timely manner. Consequently, it is difficult to provide early warnings of potential equipment overheating faults. The limited frequency of manual inspections results in significant blind spots, and the inspection results are greatly influenced by the operator's experience and subjective judgment. Temperature data relies on manual recording and lacks continuous historical data storage and traceability capabilities, which is not conducive to accurate fault tracing and analysis. At the same time, the control cabinet of the power distribution room contains high-voltage electrical circuits and a complex electromagnetic environment, posing a high risk of electric shock to personnel who frequently enter the site for inspections. The inspection efficiency is insufficient to meet the real-time monitoring requirements for safe equipment operation in modern industry. To solve this technical problem, we provide a temperature monitoring system for rotary kiln power distribution room control cabinets based on PCS7 and WinCC. Summary of the Invention

[0003] The purpose of this invention is to provide a temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC, in order to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, a temperature monitoring system for the control cabinet of a rotary kiln power distribution room using PCS7 and WinCC is provided, comprising: The temperature sensing unit consists of multiple PT100 thermal resistors installed at the heating element in the control cabinet of the rotary kiln power distribution room, which are used to collect the temperature analog signal of each temperature measuring point. The signal isolation and conditioning unit is composed of intelligent isolation safety barriers connected to each PT100 thermal resistor. The intelligent isolation safety barrier integrates a dynamic noise suppression circuit and an adaptive range matching module, which are used to adaptively condition the temperature analog signal to obtain an effective temperature change signal. The analog-to-digital conversion and processing unit consists of a multi-channel synchronous sampling AI module. Each analog input channel of the multi-channel synchronous sampling AI module is connected to the output terminal of the intelligent isolated safety barrier. It also has a built-in multi-level digital filtering engine and a nonlinear temperature compensation logic module, which are used to convert the effective temperature change signal into an initial digital temperature value and to perform real-time compensation and correction on the initial digital temperature value based on the nonlinear characteristics of the PT100 thermal resistor to obtain the final digital temperature value. The central control unit consists of a CPU configured via PCS7. The CPU is connected to the multi-channel synchronous sampling AI module via a backplane bus to receive the final digital temperature value and execute a preset temperature limit judgment algorithm and data packet upload protocol. The monitoring and display unit consists of an industrial control computer running WinCC software. The industrial control computer communicates with the CPU through an industrial Ethernet switch to read and display the final digital temperature values ​​of each temperature measurement point in real time.

[0005] Compared with the prior art, the beneficial effects of the present invention are as follows: By deploying PT100 RTDs, the system achieves 24 / 7 uninterrupted real-time acquisition of temperature signals from key heat-generating components within the control cabinet, eliminating monitoring blind spots during inspection intervals. The integrated dynamic noise suppression circuit and adaptive range matching module within the signal isolation and conditioning unit effectively filter out electromagnetic interference and automatically normalize the signal to the standard range, ensuring the purity and stability of the temperature analog signal. A multi-level digital filtering engine further eliminates random interference and pulse glitches. The nonlinear temperature compensation logic module, combined with a piecewise fitting program, performs hardware and software collaborative dual-layer compensation correction on the inherent nonlinear characteristics of the PT100 RTD, improving temperature measurement accuracy. The system adopts contactless data transmission and WinCC centralized monitoring, allowing operators to view the temperature, change curves, and historical data at each point in real time without entering the high-voltage power distribution room. This significantly reduces personal safety risks and manual inspection costs, while providing complete and reliable data support for equipment fault tracing and preventive maintenance, ensuring the safe operation of the rotary kiln power distribution system. Attached Figure Description

[0006] Figure 1 This is an overall block diagram of the present invention.

[0007] The meanings of the labels in the diagram are as follows: 1. Temperature sensing unit; 2. Signal isolation and conditioning unit; 3. Analog-to-digital conversion and processing unit; 4. Central control unit; 5. Monitoring and display unit. Detailed Implementation

[0008] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0009] This invention provides a temperature monitoring system for the control cabinet of a rotary kiln power distribution room using PCS7 and WinCC. Please refer to [link / reference]. Figure 1 As shown, it includes: The temperature sensing unit consists of multiple PT100 thermal resistors installed at the heating element in the control cabinet of the rotary kiln power distribution room, which are used to collect the temperature analog signal of each temperature measuring point. The signal isolation and conditioning unit consists of intelligent isolation safety barriers connected to each PT100 thermistor. The intelligent isolation safety barrier integrates a dynamic noise suppression circuit and an adaptive range matching module, which are used to adaptively condition the temperature analog signal to obtain an effective temperature change signal. The analog-to-digital conversion and processing unit consists of a multi-channel synchronous sampling AI module. Each analog input channel of the multi-channel synchronous sampling AI module is connected to the output of the intelligent isolated safety barrier. It also has a built-in multi-level digital filtering engine and a nonlinear temperature compensation logic module, which are used to convert the effective temperature change signal into an initial digital temperature value and to perform real-time compensation and correction on the initial digital temperature value based on the nonlinear characteristics of the PT100 thermal resistor to obtain the final digital temperature value. The central control unit consists of a CPU configured via PCS7. The CPU is connected to a multi-channel synchronous sampling AI module via a backplane bus to receive the final digital temperature value and execute a preset temperature limit judgment algorithm and data packet upload protocol. The monitoring and display unit consists of an industrial control computer running WinCC software. The industrial control computer communicates with the CPU through an industrial Ethernet switch to read and display the final digital temperature values ​​of each temperature measuring point in real time.

[0010] After the temperature sensing unit completes the acquisition of temperature analog signals from each temperature measuring point in the rotary kiln power distribution room control cabinet, it transmits the continuously output temperature analog signals to the signal isolation and conditioning unit. The intelligent isolation safety barrier inside the signal isolation and conditioning unit immediately starts the signal conditioning workflow. The dynamic noise suppression circuit integrated inside the intelligent isolation safety barrier serves as the execution module for analog signal preprocessing. The dynamic noise suppression circuit is used to remove invalid noise components in the temperature analog signal caused by electromagnetic interference in the power distribution room, environmental thermal disturbances, and the thermal noise of the thermal resistor itself. The dynamic noise suppression circuit consists of two hardware sub-modules connected in series: a noise baseline learning sub-module based on a sliding time window and a dynamic threshold comparator. The noise baseline learning sub-module based on a sliding time window is the processing unit in the dynamic noise suppression circuit used to adaptively learn the environmental noise fluctuation law and generate a dynamic threshold range. The dynamic threshold comparator is the judgment unit used to perform point-by-point numerical comparison between the amplitude of the real-time temperature analog signal and the noise baseline threshold range.

[0011] The noise baseline learning submodule based on a sliding time window continuously receives the temperature simulation signal transmitted by the temperature sensing unit. The temperature simulation signal is a continuous voltage-type analog signal obtained by converting the physical quantity of temperature using a PT100 resistance thermometer. The sliding time window is a preset fixed-duration signal sampling interval within the submodule. The duration of the sliding time window is calibrated based on the physical characteristics of temperature changes within the rotary kiln's power distribution room control cabinet. The noise baseline learning submodule based on the sliding time window calculates the rate of change of the temperature simulation signal within the sliding time window in real time. The rate of change refers to the change in the voltage amplitude of the temperature simulation signal per unit time. The noise baseline learning submodule based on the sliding time window compares the real-time calculated rate of change with a preset slow-change threshold. The slow-change threshold is used to distinguish between a temperature simulation signal in a state without abrupt changes and one in abrupt changes. The threshold value, or no-abrupt-change state, refers to a signal state where the temperature inside the control cabinet has not actually changed, only environmental noise interference exists. When the rate of change of the temperature simulation signal is continuously lower than the slow-change threshold, the noise baseline learning submodule based on the sliding time window determines that the temperature simulation signal is in a no-abrupt-change state. In this no-abrupt-change state, the noise baseline learning submodule continuously records the peak and trough values ​​of the temperature simulation signal within the sliding time window. The peak value refers to the maximum voltage amplitude of the temperature simulation signal within a single sliding time window, and the trough value refers to the minimum voltage amplitude of the temperature simulation signal within a single sliding time window. The noise baseline learning submodule based on the sliding time window performs statistical calculations on the peak and trough values ​​of multiple consecutive sliding time windows. These statistical calculations are used to quantify the noise fluctuation characteristics of the current environment. The quantification formula for the noise fluctuation characteristics is as follows: In the formula This represents the quantized value of the noise fluctuation characteristics. This indicates the total number of sliding time windows included in the statistics. Indicates the first The average amplitude of the temperature simulation signal within a sliding time window. This represents the arithmetic mean of the amplitude values ​​within all sliding time windows. The noise baseline learning submodule based on the sliding time windows generates noise that varies with signal characteristics based on the quantized values ​​of noise fluctuation characteristics. The threshold range, or noise baseline threshold range, refers to the voltage amplitude range used to distinguish between environmental noise and real temperature change signals. The upper limit of the noise baseline threshold range is obtained by superimposing the maximum peak value and the quantized value of the noise fluctuation feature within the sliding time window. The lower limit of the noise baseline threshold range is obtained by subtracting the minimum trough value and the quantized value of the noise fluctuation feature within the sliding time window. The upper and lower limits of the noise baseline threshold range will be adaptively adjusted in real time according to the changes in the environmental noise fluctuation characteristics. The noise baseline learning submodule based on the sliding time window will synchronously transmit the real-time updated noise baseline threshold range to the dynamic threshold comparator.

[0012] The dynamic threshold comparator continuously receives the real-time temperature analog signal and the noise baseline threshold range. It performs point-by-point amplitude comparison of the temperature analog signal at a fixed sampling frequency. When the real-time voltage amplitude of the temperature analog signal is between the upper and lower limits of the noise baseline threshold range, the dynamic threshold comparator identifies this segment of the temperature analog signal as ambient noise. Ambient noise refers to random signal fluctuations unrelated to the actual temperature changes within the control cabinet. The dynamic threshold comparator outputs a noise filtering control level to block and remove this segment of the temperature analog signal. When the real-time voltage amplitude of the temperature analog signal exceeds the upper limit of the noise baseline threshold range or falls below the lower limit, the dynamic threshold comparator determines that the signal fluctuation is caused by actual temperature changes within the control cabinet. The dynamic threshold comparator identifies this segment of the temperature analog signal as the initial effective temperature change signal. The initial effective temperature change signal refers to the analog signal containing only actual temperature change information after removing ambient noise. The dynamic threshold comparator outputs a control level signal to transmit the initial effective temperature change signal to the adaptive range matching module inside the intelligent isolated safety barrier.

[0013] After the dynamic noise suppression circuit completes the extraction and transmission of the initial effective temperature change signal, the adaptive range matching module immediately receives the signal and initiates the range adaptation processing flow. The adaptive range matching module is a processing module in the intelligent isolated safety barrier used to normalize the initial effective temperature change signal to the standard voltage range. All operations of the dynamic noise suppression circuit are executed in real time by the hardware circuit without software calculation delay. All calculation parameters are calibrated according to the actual operating environment of the rotary kiln power distribution room. The dynamic noise suppression circuit achieves accurate filtering of environmental noise through noise baseline learning under no-abrupt-state conditions, avoiding invalid noise signals from entering the subsequent analog-to-digital conversion stage and affecting the temperature acquisition accuracy, thus providing a clean and effective analog signal for subsequent signal range matching, analog-to-digital conversion, and temperature compensation operations.

[0014] After the dynamic noise suppression circuit completes its hardware initialization, the noise baseline learning submodule initiates its real-time computation process. The preset time window is a fixed-duration sampling interval set within the noise baseline learning submodule. This interval is used to continuously capture real-time data segments of the temperature simulation signal. The noise baseline learning submodule calculates the rate of change of the temperature simulation signal within the preset time window using discrete interpolation. The rate of change refers to the change in the amplitude of the temperature simulation signal per unit time. The formula for calculating the rate of change is: , in the formula This represents the rate of change of the signal at the current moment. This represents the amplitude of the analog temperature signal at the current moment. This represents the amplitude of the analog temperature signal at the previous sampling time. This represents the time interval between single sampling points within a preset time window. The noise baseline learning submodule continuously compares the real-time calculated signal change rate with a preset slow-change threshold. The slow-change threshold is a critical value used to distinguish whether the temperature simulation signal exhibits real temperature changes. When the signal change rate is consistently less than the slow-change threshold, the noise baseline learning submodule determines that the temperature simulation signal is in a no-abrupt state. A no-abrupt state refers to a signal state where the temperature simulation signal only contains environmental noise components and no real temperature changes have occurred. After determining the no-abrupt state, the noise baseline learning submodule continuously records the peak and trough values ​​of the temperature simulation signal within the preset time window. The noise baseline learning submodule performs statistical calculations on the peak and trough values ​​for multiple consecutive sampling periods. The statistical calculation method involves calculating the distribution variance of the peak and trough values. This variance value is used to quantify the noise fluctuation characteristics of the current environment. The quantification formula for noise fluctuation characteristics is as follows: , in the formula This represents the quantized value of the noise fluctuation characteristics. This indicates the total number of valid sampling points included within the statistical period. Indicates the first The peak value corresponding to each sampling point This represents the arithmetic mean of all peak values ​​within the statistical period. Indicates the first The trough value corresponding to each sampling point This represents the arithmetic mean of all trough values ​​within the statistical period. The noise baseline learning submodule generates a noise baseline threshold range based on the quantized values ​​of noise fluctuation characteristics. The noise baseline threshold range includes an upper limit and a lower limit. The formula for calculating the upper limit is... The formula for calculating the lower limit value is: , in the formula This represents the upper limit of the noise baseline threshold range. This represents the lower limit of the noise baseline threshold range. The noise baseline learning submodule adjusts the upper and lower limits of the noise baseline threshold range synchronously based on the real-time update of the quantized noise fluctuation characteristics. This adjustment process is adaptive, meaning that the boundary values ​​of the noise baseline threshold range change synchronously with the changes in environmental noise fluctuation characteristics. The noise baseline learning submodule transmits the adaptively adjusted noise baseline threshold range to the dynamic threshold comparator in real time. The dynamic threshold comparator continuously compares the amplitude of the real-time temperature simulation signal with the noise baseline threshold range. This comparison process continues the signal processing logic of the dynamic noise suppression circuit, accurately distinguishing between environmental noise and real temperature change signals, thereby achieving hardware-based filtering of invalid noise signals. This operation provides a stable effective temperature simulation signal for subsequent adaptive range matching processing, while maintaining the real-time performance of the signal processing flow and the independence of hardware execution.

[0015] Based on this, the system initiates the adaptive range matching module to execute the signal processing flow. The adaptive range matching module is a dedicated hardware circuit module that performs range normalization and amplification processing on the effective temperature analog signal after filtering out environmental noise. This module integrates a multi-level reference voltage source and an automatic switching switch. The multi-level reference voltage source is a hardware voltage unit integrating multiple fixed-amplitude reference voltages, each corresponding to an independent range matching level. The automatic switching switch is a hardware switching element that automatically switches the reference voltage level according to the instantaneous amplitude of the input signal. The adaptive range matching module first performs instantaneous amplitude locking processing on the initial effective temperature change signal. Instantaneous amplitude locking is a hardware processing method that fixes the instantaneous amplitude of the signal at the current moment to a calculable value. The initial effective temperature change signal is a temperature analog signal after environmental noise has been filtered out by a noise suppression circuit. The adaptive range matching module performs a level-by-level difference calculation between the locked instantaneous amplitude value and the reference voltage values ​​of each level of the multi-level reference voltage source. The calculation formula for the level-by-level difference calculation is as follows: , in the formula This represents the difference between the instantaneous amplitude and the single-range reference voltage. This represents the instantaneous amplitude value of the initial effective temperature change signal. This represents the reference voltage value of a single range in a multi-range reference voltage source. The adaptive range matching module traverses all effective ranges of the multi-range reference voltage source and selects the range with the smallest difference value as the optimal matching range. The optimal matching range is the reference voltage range corresponding to the reference voltage that is closest to the instantaneous amplitude of the initial effective temperature change signal. The adaptive range matching module drives the automatic switching switch to perform hardware range switching. The automatic switching switch connects the reference voltage corresponding to the optimal matching range to the signal processing hardware path. The signal processing hardware path is a dedicated hardware circuit path for signal transmission and processing. The adaptive range matching module uses the reference voltage corresponding to the optimal matching range to perform normalization amplification processing. Normalization amplification processing is a hardware processing method that linearly converts the signal amplitude to a standard voltage range. The standard voltage range is a fixed voltage range that can be stably identified by the subsequent analog-to-digital conversion unit. The calculation formula for normalization amplification processing is: , in the formula This represents the normalized and amplified signal amplitude. This represents the fixed hardware gain value of the adaptive range matching module. The reference voltage value corresponding to the optimal matching range is represented by the above hardware processing. The adaptive range matching module converts the initial effective temperature change signal to the standard voltage range. The signal after conversion is defined as the effective temperature change signal. The effective temperature change signal is a pure temperature analog signal with an amplitude that conforms to the standard voltage range and has no noise component. The adaptive range matching module outputs the effective temperature change signal to the subsequent analog-to-digital conversion unit in real time through the hardware circuit. The analog-to-digital conversion unit is a dedicated hardware processing unit that converts the analog temperature signal into a digital temperature signal. This processing flow forms a complete closed loop with the noise suppression circuit processing flow. After the noise suppression circuit completes the hardware-based filtering of environmental noise, the adaptive range matching module immediately performs range matching and normalization amplification processing. The two functional modules are directly connected through dedicated hardware circuits without intermediate data processing links. There is no amplitude loss during signal transmission. All processing operations are executed in real time by the hardware circuit without software involvement. All circuit parameters are set according to the standard voltage range and signal amplitude range, providing a stable and standard effective temperature change signal for subsequent analog-to-digital conversion and digital signal transmission.

[0016] The effective temperature change signal is transmitted in real time to a multi-level digital filtering engine via a dedicated hardware circuit. The multi-level digital filtering engine is a dedicated circuit module that performs multi-level hardware digital filtering processing on the effective temperature change signal. This module includes a recursive averaging filtering submodule and a limiting and de-jittering filtering submodule configured in series. The series configuration means that the signal passes through the two submodules in sequence according to the hardware circuit connection order to perform continuous filtering processing. The recursive averaging filtering submodule is a hardware filtering submodule that performs continuous multiple samplings of the effective temperature change signal and calculates the average value. The limiting and de-jittering filtering submodule is a hardware filtering submodule that performs limit judgment on the deviation between adjacent sampling values ​​and eliminates suspicious pulse interference.

[0017] The recursive averaging filter submodule first performs continuous, equally spaced sampling on the input effective temperature change signal. This continuous, equally spaced sampling refers to acquiring the instantaneous amplitude values ​​of the effective temperature change signal at fixed hardware time intervals. The total number of samples is determined by a preset value in the module's built-in hardware register. The recursive averaging filter submodule then performs an accumulation operation on all acquired instantaneous amplitude values. After the accumulation operation is completed, it performs a sample average calculation. The formula for calculating the sample average is as follows: , in the formula This represents the average value of the sampled data of the effective temperature change signal. This represents the preset total number of samples for the recursive average filtering submodule. This indicates the recursive average filter submodule number. The instantaneous amplitude value obtained from the sampling is used by the recursive average filtering submodule to smooth the random interference component in the effective temperature change signal. The random interference component refers to the irregular instantaneous amplitude fluctuation component generated by environmental electromagnetic interference. After processing, the effective temperature change signal with smoothed random interference is output.

[0018] The effective temperature change signal after smoothing random interference is transmitted in real time to the amplitude limiting and de-jittering filter submodule. The submodule first reads the preset reasonable change limit value stored in its built-in hardware register. The reasonable change limit value refers to the maximum allowable deviation between two adjacent sample values ​​preset by the system. The submodule then continuously acquires the instantaneous sample values ​​of two adjacent moments of the effective temperature change signal after smoothing random interference. These adjacent instantaneous sample values ​​refer to the instantaneous amplitude values ​​of the signal acquired at two consecutive normal sampling times. The submodule calculates the absolute deviation between the two adjacent instantaneous sample values. After calculating the absolute deviation value, it performs a real-time comparison with the preset reasonable change limit value. If the absolute deviation value is less than the preset reasonable change limit value, the amplitude limiting and de-jittering filter submodule... The module determines that the current signal is a normal and valid signal and directly performs the output operation. If the absolute deviation value is greater than or equal to the preset reasonable change limit value, the amplitude limiting and de-jittering filter submodule determines that the current signal is a suspicious pulse interference signal. The suspicious pulse interference signal refers to the abnormal amplitude change signal generated by instantaneous electromagnetic shock. The amplitude limiting and de-jittering filter submodule immediately performs a hardware rejection operation for the suspicious pulse interference signal. After the rejection operation is completed, the valid sample value of the previous moment stored in the built-in memory is called to replace the abnormal sample value of the current moment. The valid sample value of the previous moment refers to the instantaneous amplitude value of the interference-free valid signal obtained at the previous normal sampling moment. After the replacement operation is completed, the processed analog signal is output. The analog signal refers to the standard temperature analog signal without random interference and pulse interference after multi-level digital filtering.

[0019] The analog signal is transmitted in real time to the signal input port of the analog-to-digital converter unit through a dedicated hardware circuit. After receiving the analog signal, the analog-to-digital converter unit immediately performs analog-to-digital conversion processing. Analog-to-digital conversion processing refers to the hardware processing operation that linearly converts the instantaneous amplitude value of the analog signal into the standard digital temperature signal value. The standard digital temperature signal value is transmitted in real time to the subsequent signal display and storage unit through the system communication bus.

[0020] After the multi-level digital filtering engine completes the random interference smoothing and pulse interference elimination operations, the processed analog signal is transmitted through a hardware synchronization channel to the nonlinear temperature compensation logic module inside the analog-to-digital conversion and processing unit. The analog-to-digital conversion and processing unit consists of a multi-channel synchronous sampling AI module. The nonlinear temperature compensation logic module is a hardware processing module integrated inside the multi-channel synchronous sampling AI module to eliminate the inherent nonlinear error of the PT100 RTD. This module shares the same system clock with the analog-to-digital conversion circuit to achieve synchronous operation. The nonlinear temperature compensation logic module calls the built-in read-only memory through hardware addressing instructions. The read-only memory is a non-volatile hardware storage unit inside the multi-channel synchronous sampling AI module that permanently stores standard data. The PT100 RTD standard calibration table is a standard mapping data table of temperature corresponding to resistance and voltage compiled based on historical data standards. This table records the theoretical resistance value and theoretical conversion voltage value of PT100 corresponding to the standard temperature point within the entire temperature range.

[0021] Within the same clock cycle when the analog-to-digital converter (ADC) initiates the digital conversion of the analog signal, the nonlinear temperature compensation logic module reads the instantaneous voltage value corresponding to the analog signal in real time. This instantaneous voltage value is the analog voltage value linearly corresponding to the temperature physical quantity after front-end signal conditioning and filtering. The nonlinear temperature compensation logic module performs a hardware parallel lookup comparison of this instantaneous voltage value with the standard voltage values ​​in the PT100 RTD standard calibration table. Parallel lookup comparison refers to a high-speed processing method where the hardware circuit simultaneously searches all standard voltage values ​​in the calibration table to locate the target interval. The module locates two standard calibration points adjacent to the instantaneous voltage value, which are denoted as the first calibration point and the second calibration point. The nonlinear temperature compensation logic module extracts the standard voltage and standard temperature values ​​corresponding to the first and second calibration points. Based on these four parameters, the module performs a linear interpolation operation to calculate the standard compensation temperature value corresponding to the instantaneous voltage value. The mathematical expression for the linear interpolation operation is as follows: In the formula This represents the standard temperature value after reverse compensation. This represents the instantaneous voltage value corresponding to the analog signal. This represents the standard voltage value at the first scale division point. This represents the standard temperature value at the first graduation point. This indicates the standard voltage value at the second scale point. The standard temperature value representing the second graduation point; the inherent nonlinear relationship of the PT100 RTD refers to the deviation between the actual resistance-temperature characteristics and the ideal linear characteristics of the PT100 RTD; reverse compensation refers to the process of correcting the actual signal value according to the ideal characteristics of the standard graduation table to eliminate nonlinear deviation. The nonlinear temperature compensation logic module continuously performs the above table lookup and interpolation operations throughout the entire analog-to-digital conversion process of the analog-to-digital converter circuit. The hardware circuit realizes the synchronous execution of compensation operations and analog-to-digital conversion through a parallel data processing architecture. This processing method has no additional computational delay. While the analog-to-digital converter circuit outputs the original digital value, the nonlinear temperature compensation logic module has completed the reverse correction of the nonlinear error. The module encapsulates the corrected temperature value into a standard digital format and outputs the initial digital value. The initial digital temperature value is a standard digital temperature signal that can be directly transmitted to the central control unit after eliminating the inherent nonlinear error of the PT100. The central control unit consists of a CPU configured by the PCS7 program. This CPU establishes a data connection with the multi-channel synchronous sampling AI module through the backplane bus. The initial digital temperature value is transmitted to the central control unit in real time through the backplane bus. After receiving the initial digital temperature value, the central control unit will start the piecewise fitting secondary compensation operation. The piecewise fitting secondary compensation operation is used to further eliminate the small errors left by the interpolation of the scale table. All operations of the nonlinear temperature compensation logic module are implemented by the hardware circuit. All operation parameters are calibrated according to the PT100 standard scale table. All hardware logic is adapted to the runtime sequence of the multi-channel synchronous sampling AI module.

[0022] After the nonlinear temperature compensation logic module completes the initial lookup and interpolation calculations of the standard calibration table, the hardware lookup compensation circuit integrated within the module immediately enters a synchronous and coordinated working state. The hardware lookup compensation circuit is a dedicated hardware compensation circuit integrated on the same chip as the analog-to-digital converter. This circuit shares the same hardware clock cycle with the analog-to-digital converter, realizing the synchronous parallel execution of analog-to-digital conversion and nonlinear compensation. The hardware lookup compensation circuit does not occupy independent operation timing and can complete real-time correction operations throughout the entire analog-to-digital conversion process.

[0023] When the analog-to-digital converter (ADC) performs successive approximation ADC on the analog signal transmitted from the front end, it generates and outputs an intermediate voltage comparison value in each clock cycle. The intermediate voltage comparison value refers to the intermediate voltage value generated by the comparator inside the ADC during the bit-by-bit comparison process. This value is the real-time comparison data that has not been corrected during the analog-to-digital signal conversion process. The hardware lookup table compensation circuit captures this intermediate voltage comparison value in real time through the hardware data capture channel. The data capture operation is completed within a single clock cycle without interrupting the normal execution process of the ADC.

[0024] While extracting the intermediate voltage comparison value, the hardware lookup compensation circuit reads the PT100 voltage-temperature relationship mapping table stored in the internal read-only memory through hardware addressing instructions. The PT100 voltage-temperature relationship mapping table is a hardware data table that is fixed in the chip manufacturing stage according to the IEC751 international standard. This table completely records the correspondence between the standard voltage value and the standard temperature value of the PT100 RTD within the entire temperature range, without data loss or parameter deviation.

[0025] The hardware lookup table compensation circuit adopts a hardware parallel comparison architecture. It performs synchronous numerical comparison between the extracted intermediate voltage comparison value and all standard voltage values ​​in the PT100 voltage and temperature relationship mapping table. The parallel comparison architecture can complete the full table search within a single clock cycle and quickly locate two standard voltage nodes adjacent to the intermediate voltage comparison value. The two standard voltage nodes are defined as the first calibration voltage and the second calibration voltage, respectively. The hardware lookup table compensation circuit synchronously extracts the first calibration temperature corresponding to the first calibration voltage and the second calibration temperature corresponding to the second calibration voltage.

[0026] The hardware lookup table compensation circuit performs hardware-based linear interpolation calculations based on the above calibration parameters. The linear interpolation calculation is used to obtain the precise compensation temperature value corresponding to the intermediate voltage comparison value. The mathematical expression for the linear interpolation calculation is as follows: In the formula This represents the compensation target temperature value obtained through hardware interpolation calculation. This represents the intermediate voltage comparison value captured in real time during the analog-to-digital conversion process. This represents the first calibration voltage value obtained from parallel comparison and positioning. This indicates the first calibration temperature value corresponding to the first calibration voltage. This represents the second calibration voltage value obtained from parallel comparison and positioning. This indicates the second calibration temperature value corresponding to the second calibration voltage.

[0027] The hardware lookup table compensation circuit calculates and generates the correction reference voltage required by the analog-to-digital converter based on the target temperature value. The correction reference voltage is a dynamic reference voltage used to eliminate the inherent nonlinear error of the PT100 RTD. This voltage can replace the fixed reference voltage originally used by the analog-to-digital converter. The hardware lookup table compensation circuit directly inputs the correction reference voltage into the reference voltage pin of the analog-to-digital converter within the current clock cycle to complete the real-time correction operation of the reference voltage.

[0028] After receiving the corrected reference voltage, the analog-to-digital converter (ADC) completes the analog-to-digital conversion operation for the remaining clock cycles based on this dynamic reference voltage. During the conversion process, the nonlinear characteristic deviation of the PT100 RTD is automatically eliminated. After the conversion process is completed, the ADC directly outputs the initial digital temperature value. The initial digital temperature value is a standard digital temperature signal that has undergone hardware nonlinear compensation. This signal has no inherent nonlinear error of the PT100 and can be directly used for subsequent data processing and transmission. The initial digital temperature value is synchronously transmitted to the central control unit (CPU) configured by the PCS7 program via the backplane bus. After receiving the initial digital temperature value, the CPU will start the piecewise fitting compensation program to perform secondary residual error correction. All operations of the hardware lookup table compensation circuit are executed autonomously by the hardware circuit. The hardware lookup table compensation circuit, the front-end multi-level digital filtering engine, and the back-end central control unit form a complete signal processing closed loop. There is no data gap in the entire process from analog signal filtering nonlinear hardware compensation to digital signal output, providing accurate raw temperature data for temperature monitoring of the rotary kiln power distribution room control cabinet.

[0029] After the initial digital temperature value is stably transmitted to the central control unit (CPU) configured by the PCS7 program via the backplane bus, the CPU immediately starts the secondary compensation process for the residual nonlinear error of the PT100 RTD. This process is fully implemented by the segmented fitting compensation program that runs periodically inside the CPU. The segmented fitting compensation program is a dedicated algorithm program that is embedded in the CPU program storage area to eliminate the small residual error after hardware compensation. The program relies on the cyclic interrupt OB block of the PCS7 system to achieve periodic calls, and can complete real-time compensation and correction without affecting the CPU's main control process.

[0030] The CPU first reads the preset temperature range division parameters from its own hold-type data register. The temperature range division parameters are the interval boundary values ​​pre-calibrated based on the nonlinear distribution characteristics of the PT100 RTD across its full range. These parameters divide the standard temperature measurement range of the PT100 into multiple continuous and non-overlapping independent sub-intervals. The division rules conform to the nonlinear error distribution law of the PT100 RTD in different temperature ranges. The CPU uses the received initial digital temperature value as the input variable. The initial digital temperature value is the digital temperature signal after the initial nonlinear correction is completed by the front-end hardware lookup table compensation circuit. This signal still contains a very small amount of residual nonlinear error. The residual nonlinear error refers to the temperature deviation component that is not completely eliminated after hardware lookup table and interpolation compensation. This component will directly affect the final temperature measurement accuracy.

[0031] The CPU uses numerical interval matching logic to determine the unique temperature sub-interval to which the initial digital temperature value belongs. This numerical interval matching logic compares the input variable with the upper and lower limits of each temperature sub-interval and locks the corresponding interval. After locking the target temperature sub-interval, the CPU immediately retrieves the high-order polynomial coefficient set uniquely bound to that sub-interval from the program data block. This high-order polynomial coefficient set is a fixed coefficient sequence calculated using mathematical fitting tools in an offline calibration experiment. The offline calibration experiment involves simultaneously placing the PT100 RTD under test and a standard platinum resistance thermometer in a constant temperature bath, setting calibration temperature points at equal intervals within each temperature sub-interval, synchronously recording the standard real temperature and the initial digital temperature value, calculating the error, and then fitting the parameters. The high-order polynomial fitting algorithm is a numerical calculation method that uses high-order polynomial functions to accurately describe the variation law of residual nonlinear error within a single temperature sub-interval. This algorithm can achieve precise quantification of minute errors.

[0032] The CPU substitutes the initial digital temperature value into the corresponding interval's high-order polynomial calculation formula to complete the real-time calculation of the residual nonlinear error. The mathematical expression of the high-order polynomial calculation formula is as follows: In the formula This represents the residual nonlinear error value calculated within the current temperature sub-interval. This represents the initial digital temperature value input. to This represents the coefficients of the higher-order polynomial corresponding to the current temperature sub-interval. The coefficient values ​​change independently with the temperature sub-interval. After the CPU completes the residual error calculation, it performs an error superposition compensation operation, adding the initial digital temperature value to the residual nonlinear error value. After eliminating the error components, the final digital temperature value is obtained. The mathematical expression for calculating the final digital temperature value is: In the formula This represents the final digital temperature value after piecewise fitting and secondary compensation. This value has completely eliminated all nonlinear errors of the PT100 thermal resistor and can be directly used for temperature over-limit judgment and upper computer display.

[0033] After the CPU completes the compensation calculation, it stores the final digital temperature value in the system's process data image area. Simultaneously, it executes a preset temperature limit discrimination algorithm. This algorithm compares the final digital temperature value with the preset temperature alarm threshold of the power distribution room control cabinet and outputs a status signal. The CPU then packages the final digital temperature value and status signal according to a predetermined data packet upload protocol. This protocol is the standard communication data format between the PCS7 system and the WinCC monitoring system. The packaged data is transmitted in real-time to the monitoring and display unit running the WinCC software via an industrial Ethernet switch. After receiving the data, the monitoring and display unit refreshes and displays the temperature values ​​at each measurement point in real-time and stores historical data. All calculations in the piecewise fitting compensation program are completed within the CPU, with the calculation cycle strictly synchronized with the system sampling cycle. All temperature range divisions and polynomial coefficients are pre-calibrated and stored. The piecewise fitting compensation process and the front-end hardware nonlinear compensation process form a software-hardware collaborative double-layer compensation closed loop, completely eliminating the nonlinear error of the PT100 thermal resistor and providing high-precision temperature data support for temperature monitoring of the rotary kiln power distribution room control cabinet.

[0034] After the CPU completes the calculation and data writing of the precise temperature value, the system enters the parameter matching and real-time calculation stage of the piecewise fitting compensation program. This stage is the execution step for achieving secondary precise compensation of the residual nonlinear error of the PT100 RTD. The CPU first accesses its own static data storage area through the internal data bus. The static data storage area is a non-volatile storage area inside the CPU used to permanently store system calibration parameters and fixed calculation coefficients. This area pre-stores a complete set of temperature range boundary values. The temperature range boundary values ​​are the critical values ​​for dividing the full-range standard temperature measurement range of the PT100 RTD into multiple continuous and non-overlapping independent sub-ranges based on the resistance-temperature nonlinear distribution characteristics of the PT100 RTD itself. All boundary values ​​are arranged in ascending order of temperature, completely covering the entire temperature measurement range of the PT100 RTD from low temperature to high temperature.

[0035] The CPU performs successive interval comparison operations on the initial digital temperature value input from the front end after hardware compensation and the pre-stored temperature interval boundary values. The successive interval comparison operation means that the CPU compares the initial digital temperature value with the lower and upper boundary values ​​of each sub-interval in the order of the temperature intervals. Through continuous comparison, the CPU locks the specific temperature interval to which the initial digital temperature value uniquely belongs. The specific temperature interval refers to the independent temperature measurement sub-interval in which the initial digital temperature value is located. Each temperature measurement sub-interval corresponds to a set of exclusive nonlinear error compensation parameters.

[0036] After locking onto a specific temperature range, the CPU uses pre-defined parameter addressing logic to precisely retrieve a set of high-order polynomial coefficients uniquely corresponding to that specific temperature range from the static data storage area. These high-order polynomial coefficients are fixed parameters used to construct the residual nonlinear error calculation model. Each set of coefficients is only suitable for the error variation pattern of the corresponding specific temperature range; coefficients for different temperature ranges are independent and not interchangeable. This set of high-order polynomial coefficients is obtained through an offline calibration and fitting process in a laboratory environment. The offline calibration and fitting process involves simultaneously placing the PT100 resistance thermometer to be fitted and a first-class standard platinum resistance thermometer into a high-precision constant temperature bath, and calibrating them at fixed equal intervals within the target specific temperature range. Multiple standard calibration temperature points are set up. After the constant temperature bath temperature stabilizes, the ideal temperature value output by the standard platinum resistance thermometer and the actual temperature value output by the PT100 resistance thermometer are recorded simultaneously. The difference between the two sets of values ​​is calculated to obtain the residual nonlinear error value of that temperature point. With the actual temperature value of the PT100 resistance thermometer as the independent variable and the corresponding residual nonlinear error value as the dependent variable, the least squares method is used to perform high-order polynomial curve fitting on the data of all calibration temperature points within a specific temperature range. Finally, the high-order polynomial coefficients that fit the range are obtained. All coefficients are written to the CPU static data storage area at once during the system on-site debugging phase. After the system is officially running, the coefficient values ​​remain fixed and do not change.

[0037] After retrieving the coefficients of the higher-order polynomial, the CPU uses the initial digital temperature value as the sole input variable and substitutes it into the higher-order polynomial calculation formula constructed from these coefficients to perform real-time arithmetic operations. Real-time arithmetic operations refer to the CPU completing rapid numerical calculations within the cyclic interrupt cycle set by the PCS7 system. The operation latency meets the timing requirements for real-time temperature monitoring in industrial settings. The mathematical expression of the higher-order polynomial calculation formula is as follows: In the formula This represents the residual nonlinear error value calculated within the current temperature sub-interval. This represents the initial digital temperature value input. to This represents the higher-order polynomial coefficients corresponding to the current temperature sub-interval, and the values ​​of each coefficient are uniquely determined by the offline calibration fitting experiment.

[0038] After the CPU completes the calculation of the residual nonlinear error value, it performs an algebraic summation operation on the error value and the initial digital temperature value to obtain the final accurate temperature value that completely eliminates the inherent nonlinear error of the PT100 RTD. This value is used as the data for subsequent temperature limit judgment and display on the WinCC host computer. The CPU writes the final accurate temperature value into the process data image area, which is a temporary data storage area for interaction between the CPU and the industrial Ethernet communication module. The temperature data is transmitted to the monitoring and display unit running the WinCC software via the industrial Ethernet switch. The monitoring and display unit completes the real-time visualization display of the temperature values ​​of each temperature measurement point and the archiving and storage of historical data. The software's segmented fitting compensation process and the front-end hardware lookup table compensation circuit form a software and hardware collaborative dual-layer nonlinear compensation system, which completely eliminates the nonlinear error of the PT100 RTD within the entire range and continuously ensures the long-term measurement accuracy and operational stability of the rotary kiln power distribution room control cabinet temperature monitoring system.

[0039] To ensure that the high-order polynomial coefficients called by the CPU's segmented fitting compensation program have full-range adaptability accuracy, the system must undergo a standardized PT100 RTD offline calibration and curve fitting process before on-site commissioning. This process is the only way to generate high-order polynomial coefficients corresponding to a specific temperature range. All coefficients are calibrated and permanently written to the CPU's static data storage area through this process. Before the offline calibration operation begins, the calibration devices and equipment must be prepared. The PT100 RTD sample to be used refers to the same batch of temperature measuring elements that are completely identical to the model deployed on-site in the rotary kiln power distribution room control cabinet temperature monitoring system. The standard platinum resistance thermometer refers to the reference temperature measuring device that meets the national first-class metrological standards. The temperature measuring accuracy of this device is more than one order of magnitude higher than that of the PT100 RTD. The constant temperature bath refers to a laboratory-specific calibration device with precise temperature control and a uniform temperature field. The temperature fluctuation of the equipment meets the industry standards for metrological calibration. The PT100 RTD sample and the standard platinum resistance thermometer are placed together in the central effective temperature field area of ​​the constant temperature bath to ensure that the two temperature measuring devices are in the same temperature environment without local temperature gradients or heat exchange differences.

[0040] During calibration, a specific temperature range preset by the CPU is selected as the calibration range. The specific temperature range refers to an independent temperature measurement sub-range divided according to the nonlinear characteristics of PT100. Multiple calibration temperature points are set within the specific temperature range according to a fixed equal interval rule. The equal interval setting means that the temperature difference between two adjacent calibration temperature points remains constant. The number of calibration temperature points covers the entire range from the lower limit to the upper limit of the specific temperature range, and the number meets the sample size requirements for high-order polynomial curve fitting.

[0041] Start the thermostat bath and adjust the temperature to the first calibration temperature point. After the temperature field in the thermostat bath is completely stable, record two sets of data simultaneously. The true temperature value measured by the standard platinum resistance thermometer refers to the metrological standard temperature value used as the calibration reference. The initial digital temperature value refers to the uncorrected temperature value output by the PT100 RTD sample after front-end signal isolation conditioning analog-to-digital conversion hardware lookup compensation. The recording sequence of the two sets of data is completely synchronized. Repeat the stabilization recording operation three times for each calibration temperature point, and take the average value after eliminating random interference as the valid data for that point. After completing the data recording for all calibration temperature points, perform a temperature error calculation operation for each calibration temperature point. The temperature error value refers to the inherent residual nonlinear deviation of the PT100 that was not completely eliminated by the hardware compensation process. This value is the dependent variable of the high-order polynomial fitting. The mathematical expression for the temperature error value is: In the formula Indicates the first Temperature error value corresponding to each calibration temperature point Indicates the first The actual temperature value measured by a standard platinum resistance thermometer at each calibrated temperature point. Indicates the first The initial digital temperature value corresponding to each calibration temperature point This indicates the sequential number of the calibration temperature point.

[0042] After calculating all temperature error values, a professional mathematical fitting tool is used to perform high-order polynomial curve fitting. This tool is numerical calculation software with least squares fitting capabilities. Using the initial numerical temperature values ​​of all calibrated temperature points as independent variables and the calculated temperature error values ​​as dependent variables, all calibration data is imported into the fitting tool. A fourth-order high-order polynomial is selected as the fitting model, and the least squares method is used to fit the data of all calibrated temperature points within a specific temperature range. The least squares method is a numerical calculation method that minimizes the sum of squared errors between the fitted curve and the measured data points. After completing the calculation, the mathematical fitting tool outputs a unique set of high-order polynomial curves. The set of polynomial coefficients accurately describes the nonlinear error variation of the PT100 resistance thermometer within a specific temperature range. These coefficients are written into the CPU's static data storage area using PCS7 programming software and uniquely bound to the corresponding specific temperature range. The calibration and fitting of all temperature ranges are completed using the same procedure, forming a complete piecewise fitting compensation parameter library. Based on the aforementioned offline calibration and curve fitting process, to better demonstrate the technical advantages of the dual-layer nonlinear error correction system composed of "hardware lookup table compensation" and "software piecewise fitting secondary compensation" in this invention, a set of typical experimental case data shown in Table 1 is introduced. This data is selected from standard calibration experiments within the range of 0℃ to 200℃. Using the actual temperature value measured by a standard platinum resistance thermometer as a benchmark, the initial digital temperature value after hardware lookup table compensation alone, and the final digital temperature value after hardware and software collaborative compensation are recorded respectively.

[0043] Table 1: Comparative Experimental Data on the Effect of Dual-Layer Compensation for Nonlinear Error of PT100 (Range: 0~200℃) As can be clearly seen from the data in Table 1, relying solely on the hardware lookup table and linear interpolation compensation built into the AI ​​module, due to the inherent nonlinear characteristics of the PT100 and the residual interpolation from the calibration table, the initial digital temperature value output still has a residual error of approximately 0.68℃ at most and an average of approximately 0.38℃ across the entire measurement range. However, after the CPU calls the high-order polynomial coefficients generated based on the offline calibration of this scheme for piecewise fitting and secondary compensation, the average absolute error of the final digital temperature value is significantly reduced to 0.016℃, with an average error improvement of 95.8%, and the measurement accuracy is improved by more than an order of magnitude.

[0044] When the CPU runs the piecewise fitting compensation program in real time, it can directly call the coefficients generated by the offline calibration to complete the accurate compensation of residual nonlinear error, ensuring the consistency and accuracy of the high-order polynomial coefficients. This process forms a two-layer compensation closed loop with the on-site real-time compensation process, continuously ensuring the measurement accuracy and long-term operational stability of the rotary kiln power distribution room control cabinet temperature monitoring system.

[0045] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A temperature monitoring system for the control cabinet of a rotary kiln power distribution room using PCS7 and WinCC, characterized in that, include: The temperature sensing unit (1) consists of multiple PT100 thermal resistors installed at the heating element in the control cabinet of the rotary kiln power distribution room, which are used to collect the temperature analog signal of each temperature measuring point. The signal isolation conditioning unit (2) is composed of an intelligent isolation safety barrier connected to each PT100 thermal resistor. The intelligent isolation safety barrier integrates a dynamic noise suppression circuit and an adaptive range matching module, which are used to adaptively condition the temperature analog signal to obtain an effective temperature change signal. The analog-to-digital conversion and processing unit (3) is composed of a multi-channel synchronous sampling AI module. Each analog input channel of the multi-channel synchronous sampling AI module is connected to the output terminal of the intelligent isolated safety barrier. It also has a built-in multi-level digital filtering engine and a nonlinear temperature compensation logic module, which are used to convert the effective temperature change signal into an initial digital temperature value and to perform real-time compensation and correction on the initial digital temperature value for the nonlinear characteristics of the PT100 thermal resistor to obtain the final digital temperature value. The central control unit (4) is composed of a CPU configured by PCS7 program. The CPU is connected to the multi-channel synchronous sampling AI module through the backplane bus to receive the final digital temperature value and execute the preset temperature over-limit judgment algorithm and data packet upload protocol. The monitoring and display unit (5) is composed of an industrial control computer running WinCC software. The industrial control computer communicates with the CPU through an industrial Ethernet switch to read and display the final digital temperature values ​​of each temperature measurement point in real time.

2. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 1, characterized in that: The dynamic noise suppression circuit includes a noise baseline learning submodule based on a sliding time window and a dynamic threshold comparator. The noise baseline learning submodule based on the sliding time window continuously analyzes the fluctuation characteristics of the input temperature analog signal in a state without abrupt changes, and generates a noise baseline threshold range that changes with the signal characteristics based on the fluctuation characteristics. The dynamic threshold comparator compares the temperature analog signal with the noise baseline threshold range. When the temperature analog signal fluctuation is determined to be within the noise baseline threshold range, the temperature analog signal is identified as environmental noise and filtered out. When the temperature analog signal fluctuation exceeds the noise baseline threshold range, it is determined to be an initial valid temperature change signal and allowed to pass.

3. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 2, characterized in that: The noise baseline learning submodule based on a sliding time window continuously analyzes the fluctuation characteristics of the input temperature simulation signal under a state without abrupt changes, specifically including: The noise baseline learning submodule achieves this by calculating the rate of change of the simulated temperature signal within a preset time window in real time. When the rate of change of the simulated temperature signal is continuously lower than a preset slow-change threshold, the noise baseline learning submodule determines that the simulated temperature signal is in a state of no sudden change and begins to record the peak and trough values ​​of the simulated temperature signal within this time period. The noise fluctuation characteristics of the current environment are quantified by statistically analyzing the distribution of the peak and trough values. A noise baseline threshold range that changes with the signal characteristics is generated based on the noise fluctuation characteristics. The upper and lower limits of the noise baseline threshold range are adaptively adjusted as the noise fluctuation characteristics change.

4. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 3, characterized in that: The adaptive range matching module has a built-in multi-level reference voltage source and an automatic switching switch. Based on the amplitude level of the initial effective temperature change signal, the adaptive range matching module automatically selects the reference voltage level among the multi-level reference voltage sources that best matches the amplitude level through the automatic switching switch. The module then uses the reference voltage corresponding to the reference voltage level to normalize and amplify the initial effective temperature change signal, so that the initial effective temperature change signal is within the standard voltage range, thereby acquiring the effective temperature change signal.

5. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 1, characterized in that: The multi-level digital filtering engine includes a recursive averaging filtering submodule and a limiting and de-jittering filtering submodule configured in series. The recursive averaging filtering submodule samples the effective temperature change signal multiple times and calculates its average value to smooth out random interference, thereby obtaining the effective temperature change signal after smoothing out random interference. The limiting and de-jittering filtering submodule judges the effective temperature change signal after smoothing out random interference. If the deviation between two adjacent sampling values ​​of the effective temperature change signal after smoothing out random interference exceeds a preset reasonable change limit, it is judged as suspicious pulse interference and is removed. The effective sampling value at the previous moment is then used to replace it to obtain the analog signal.

6. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 5, characterized in that: The nonlinear temperature compensation logic module calls the read-only memory that stores the PT100 RTD standard calibration table. The nonlinear temperature compensation logic module performs table lookup and linear interpolation operations on the relationship between the voltage value corresponding to the analog signal and the theoretical resistance value and voltage value corresponding to different temperature points in the PT100 RTD standard calibration table. At the same time as the analog-to-digital conversion occurs, the inherent nonlinear relationship of PT100 is reverse-compensated in advance, and the initial digital temperature value is output.

7. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 6, characterized in that: The nonlinear temperature compensation logic module performs reverse compensation for the inherent nonlinearity of the PT100 simultaneously with the analog-to-digital conversion, specifically including: The nonlinear temperature compensation logic module has a built-in hardware lookup table compensation circuit. The hardware lookup table compensation circuit captures the intermediate voltage comparison value in real time during the analog-to-digital conversion process, and immediately performs parallel comparison and interpolation calculation with the PT100 voltage-temperature relationship mapping table in the internal read-only memory of the nonlinear temperature compensation logic module. This corrects the reference voltage of the analog-to-digital converter in the current clock cycle, so that the analog-to-digital converter can output the initial digital temperature value.

8. The temperature monitoring system for the control cabinet of the rotary kiln power distribution room using PCS7 and WinCC as described in claim 7, characterized in that: The real-time compensation and correction of the initial digital temperature value for the nonlinear characteristics of the PT100 thermal resistor is specifically achieved by running a piecewise fitting compensation program in the CPU. The piecewise fitting compensation program takes the initial digital temperature value as input, and based on the preset temperature range division, uses a high-order polynomial fitting algorithm to perform secondary calculation and compensation on the residual nonlinear error of the PT100 thermal resistor in each temperature range to obtain the final digital temperature value.

9. A temperature monitoring system for a rotary kiln power distribution room control cabinet based on PCS7 and WinCC as described in claim 8, characterized in that: The method employs a high-order polynomial fitting algorithm to perform secondary calculations and compensation for the residual nonlinear error of the PT100 thermal resistor in each temperature range, specifically including: The CPU determines the specific temperature range to which the initial digital temperature value belongs based on a set of temperature range boundary values ​​pre-stored in the CPU memory. The CPU retrieves a set of high-order polynomial coefficients that uniquely correspond to the specific temperature range from the memory. The high-order polynomial coefficients are obtained by offline fitting of the error between the ideal temperature and resistance characteristic curve and the measured characteristic curve of the PT100 thermal resistor within the specific temperature range. The CPU uses the initial digital temperature value as an input variable and substitutes it into the high-order polynomial calculation formula constructed with the high-order polynomial coefficients for real-time calculation to obtain the final digital temperature value.

10. A temperature monitoring system for a rotary kiln power distribution room control cabinet based on PCS7 and WinCC as described in claim 9, characterized in that: The PT100 resistance thermometer sample to be used and a standard platinum resistance thermometer are placed together in a constant temperature bath. Within the specific temperature range, multiple calibration temperature points are set at equal intervals. At each calibration temperature, the actual temperature value and the initial digital temperature value measured by the standard platinum resistance thermometer are recorded simultaneously. The actual temperature value of each calibration temperature point is subtracted from the corresponding initial digital temperature value to obtain the temperature error value corresponding to the initial digital temperature value. Finally, a mathematical fitting tool is used to perform high-order polynomial curve fitting on all calibration temperature points within the specific temperature range, with the initial digital temperature value as the independent variable and the temperature error value as the dependent variable, to obtain a set of high-order polynomial coefficients to describe the nonlinear error law within the specific temperature range.

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