An electric heat tracing band output power intelligent control method and system

Abstract

The application discloses an electric tracing band output power intelligent control method and system, and belongs to the technical field of industrial electric tracing control. The application monitors the micro insulation deterioration of the PTC material by collecting the driving voltage and current signals of the electric tracing band in real time, calculating the high-frequency distortion rate (DHF) in the steady-state heating stage THD h , High-frequency Total Harmonic Distortion ) to monitor the micro insulation deterioration of the PTC material; after forced power-off and power restoration in the active disturbance detection stage, the driving current is collected, the Prony algorithm is adopted to extract the maximum decay time constant τ max , and then the local equivalent convective heat transfer coefficient is inverted h local . According to the comparison results of the h local and THD h with the safety threshold, it is decided whether to switch from the conventional PID control mode to the anti-coking control mode. In the anti-coking mode, the safety duty ratio is calculated based on the extreme adiabatic assumption and is output in the form of a low-duty-ratio pulse, so as to guide the local heat accumulation to diffuse axially.

Description

Technical Field

[0001] This invention relates to the field of industrial electric heat tracing control technology, specifically to an intelligent control method and system for the output power of electric heat tracing cables used in long-distance pipelines for transporting high-viscosity fluids such as heavy oil and asphalt, which is particularly suitable for preventing material cracking and coking caused by local fluid stagnation. Background Technology

[0002] In the petrochemical, storage, and terminal industries, the long-distance pipeline transportation of high-viscosity non-Newtonian fluids such as heavy oil and asphalt is highly dependent on electric heat tracing systems. These fluids are extremely sensitive to temperature: excessively low temperatures can cause the viscosity to increase exponentially or even cause the pipes to freeze; while excessively high local temperatures, once exceeding the pyrolysis temperature threshold (usually 250℃~300℃), will cause the colloids and asphalt inside the fluid to undergo a thermal condensation reaction, forming a hard coke layer on the inner side of the pipe wall, ultimately leading to complete pipeline blockage and scrapping.

[0003] Currently, electric heating tape is commonly used for insulation on the outer walls of pipelines in industrial settings. Under normal steady-state flow conditions, the fluid inside the pipe carries away heat through forced convection, resulting in a relatively uniform temperature field within the pipeline. However, in actual production, due to factors such as pump and valve start-up and shutdown, sudden changes in pipe diameter, or localized filter blockage, long pipelines are prone to developing "dead zones" where fluid flow velocity sharply decreases or even stagnates completely. In these areas, the convective heat transfer coefficient of the fluid approaches zero, and the heat dissipation pathway is cut off. If the electric heating tape continues to output conventional heating power at this point, heat will continue to accumulate in this small localized space, causing a sharp increase in local temperature and irreversible coking of the material.

[0004] The closest existing solution is the Chinese invention patent with application number CN202510652997.7 and authorization announcement number CN120178763B, entitled "A Method, Device, and System for Controlling the Operation of an Electric Heating Cable System". This technology collects the temperature of the electric heating cable, the temperature of the heated body, and the ambient temperature using multi-point temperature sensors to construct a temperature sequence, calculate the heat compensation imbalance and compensation response lag, generate a temperature compensation factor, and adjust the proportional parameters of the PID controller accordingly. This method alleviates the control lag caused by sudden changes in ambient temperature to some extent, but it still has the following drawbacks:

[0005] (1) Continuous power output mode cannot solve adiabatic hot spots: Simply modifying the PID parameters is essentially still continuous heating. In the near-adiabatic state where the local fluid is stagnant, dominated by the integral effect of heat conservation, any small continuous power input will eventually lead to continuous heat accumulation, and the temperature rise chain cannot be cut off from the physical level. (2) Lack of underlying physical mechanism: This scheme remains at the level of statistical fitting of temperature data, and fails to reverse the physical driving force of temperature rise (such as the change of local equivalent convective heat transfer coefficient), and does not have the ability to preventive intervention.

[0006] Therefore, there is an urgent need for an intelligent power control method and system for electric heating tape that can preventively intervene before materials coke. Summary of the Invention

[0007] 1. Technical problem to be solved:

[0008] This invention aims to provide a novel intelligent control method and system for the output power of electric heating cables to solve the technical problem of material cracking and coking caused by the continuous power output mode in the existing technology. This invention breaks the existing continuous adjustment mode by dynamic parameter inversion and time sequence reconstruction across physical domains and introduces an anti-coking control mode based on physical boundary constraints, thereby preventing material cracking and coking and ensuring the long-term smooth operation of long-distance pipelines.

[0009] 2. Technical Solution:

[0010] To solve the above problems, the present invention adopts the following technical solution.

[0011] A method for intelligent control of the output power of an electric heating cable includes the following steps:

[0012] Step S1: Real-time acquisition of the driving voltage u(t) and driving current I(t) of the electric heating tape;

[0013] Step S2: Determine whether the preset active disturbance detection period t has been reached at the current time. probe ;

[0014] If the target is not reached, the system will enter steady-state continuous heating mode and execute steps S3 to S4.

[0015] If the target has been reached, then enter the active disturbance detection mode and execute steps S5 to S6.

[0016] Step S3: Extract the fundamental frequency f0 of the power grid based on the driving voltage u(t), and calculate the effective value I of the driving current I(t) using the period 1 / f0 corresponding to the fundamental frequency f0 as the sliding window length. rms The effective voltage values ​​u(t) and driving voltage u(t) rms (t); Perform a Fast Fourier Transform (FFT) on the driving current I(t) to obtain the fundamental amplitude M0, and after filtering out the fundamental component using a digital notch filter, perform a FFT on the remaining 11th to 40th high-frequency harmonic signals to obtain the amplitudes M of each harmonic. n (n=11,12,…39,40), and then calculate the high-frequency distortion rate (THD). h Meanwhile, based on the effective value of the current I rms (t) and the effective value of voltage u rms (t), calculate the current estimated resistance value R. currentAnd based on the resistance-temperature nonlinear mapping table RT, the current estimated temperature T is obtained by linear interpolation. current ;

[0017] Step S4: Based on the high frequency distortion rate (THD) h Make intelligent decisions: If the high frequency distortion rate (THD) h Less than the preset high-frequency total harmonic distortion (THD) benchmark base If the condition is met, the normal PID control mode is maintained and the corresponding duty cycle command is output, i.e., step S9 is executed; otherwise, the anti-coking control mode is switched to, i.e., step S8 is executed.

[0018] Step S5: Forcefully shut off the relay, restore power supply after a preset very short time, collect the drive current I(t) and drive voltage u(t) after power supply is restored, and calculate the effective value of the current I using the period 1 / f0 corresponding to the fundamental frequency f0 as the sliding window length. rms (t) and the effective value of voltage u rms (t), using the Prony algorithm to calculate the effective value of the current I. rms (t) Perform dimensionality reduction analysis on the multi-exponential decay model and extract the maximum decay time constant τ. max Meanwhile, based on the effective value of the current I rms (t) and the effective value of voltage u rms (t), calculate the current estimated resistance value R. current And based on the resistance-temperature nonlinear mapping table RT, the current estimated temperature T is obtained by linear interpolation. current ;

[0019] Step S6: According to the law of conservation of energy, use the formula Calculate the local equivalent convective heat transfer coefficient h of the current pipeline with the worst heat dissipation. local C v For the local equivalent heat capacity, S is the equivalent heat transfer surface area, and λ is the dimensionless correction coefficient; then proceed to step S7.

[0020] Step S7: Based on the local equivalent convective heat transfer coefficient h local Make intelligent decisions: if the local equivalent convective heat transfer coefficient h local Greater than the safe convection heat transfer coefficient h safe If the condition is met, the normal PID control mode is maintained and the corresponding duty cycle command is output, i.e., step S9 is executed; otherwise, the anti-coking control mode is switched to, i.e., step S8 is executed.

[0021] Step S8: First, output an alarm signal. Then, based on the extreme adiabatic assumption, that is, assuming that the local equivalent convective heat transfer coefficient is zero, calculate the maximum safe energy that can be injected according to the first law of thermodynamics. and corresponding safe power Then the safe duty cycle can be calculated. And perform clamping processing on the safe duty cycle with a preset upper limit value; wherein, T coke T is the preset material pyrolysis temperature. margin As a preset engineering safety margin, R0 is the nominal cold resistance of the electric heating tape, Δt safe The control cycle under the anti-coking control mode;

[0022] Step S9: Combine the duty cycle and corresponding conventional PID control period t generated in step S4 using the conventional PID control mode. normal Alternatively, the safe duty cycle generated by the anti-coking control mode in step S7 can be mapped to a switching timing command, which drives the relay to perform on / off actions through opto-isolation, thereby controlling the output power of the electric heating tape; then return to step S1 for a loop.

[0023] An intelligent control system for the output power of an electric heating cable, comprising:

[0024] The main power circuit consists of an AC power grid, a front-end overcurrent and overvoltage protection unit, a relay, and an electric heating tape laid on the pipeline, connected in series.

[0025] Electrical signal acquisition unit: includes a current transformer connected to the live wire of the main circuit and a voltage transformer connected in parallel to both ends of the electric heating tape, which are used to acquire the driving current and driving voltage in real time, respectively.

[0026] Signal conditioning and analog-to-digital conversion unit: connected to the output terminals of the current transformer and voltage transformer, used for DC biasing, filtering, amplification and analog-to-digital conversion of analog signals;

[0027] Controller: The controller integrates a phase-locked loop module, a digital notch filter module, a fast Fourier transform module, a Prony algorithm module, a thermodynamic parameter inversion module, an intelligent decision-making module, a PID control module, and an anti-coking control module; the controller receives the digital signal after analog-to-digital conversion, executes the steps of the above method, and outputs switching timing instructions;

[0028] Opto-isolated drive unit: Receives the switching timing instructions from the controller and drives the relay to perform on / off actions.

[0029] 3. Beneficial effects:

[0030] Compared with the prior art, the technical solution provided by this invention has the following advantages:

[0031] (1) This invention uses a dual-parameter joint judgment, namely the local equivalent convective heat transfer coefficient and high frequency distortion rate calculated by the lumped parameter method, to identify the fluid stagnation state and the abnormal state of PTC material. It can trigger an early warning before the temperature reaches the danger threshold and switch to the anti-coking control mode, thus realizing the transformation from passive response to active prevention.

[0032] (2) After the anti-coking control mode is triggered, the present invention calculates the safe duty cycle based on the extreme adiabatic assumption and outputs it in a low duty cycle pulse mode to provide heat relaxation time for potential overheated areas, guide local heat accumulation to diffuse along the pipeline axis, avoid the continuous accumulation of heat causing the material temperature to exceed the cracking temperature, thereby ensuring material safety and long-term pipeline operation.

[0033] It should be noted that the structures not described in this invention are not related to the design points and improvement directions of this invention, and are the same as or can be implemented using existing technologies, so they will not be elaborated here. Attached Figure Description

[0034] Figure 1 This is a block diagram of the overall architecture of the intelligent control system for the output power of the electric heating cable of the present invention;

[0035] Figure 2 This is a flowchart of the steady-state continuous heating and active disturbance detection process of the intelligent control method for the output power of the electric heating cable of the present invention.

[0036] Figure 3 This is a flowchart of the intelligent decision-making and control mode switching of the intelligent control method for the output power of the electric heating cable of the present invention;

[0037] Figure 4 This is a flowchart of the Prony algorithm calculation process in this invention;

[0038] Figure 5 This is a comparison chart of current waveforms under normal conditions and under conditions with "dead water zone";

[0039] Figure 6 The current spectrum diagrams are shown for normal conditions (a) and conditions with "dead water zone" (b).

[0040] Figure 7 The transient current decay curve during active disturbance detection;

[0041] Figure 8 A schematic diagram of PWM timing instructions in anti-coking control mode.

[0042] Explanation of symbols in the diagram:

[0043] C v Local equivalent heat transfer; S, equivalent heat transfer surface area; λ, dimensionless correction factor; h safeSafe convective heat transfer coefficient; THD h High-frequency distortion rate; T coke The preset material pyrolysis temperature; T margin 1. Preset engineering safety margin; R0, nominal cold resistance of the electric heating tape; RT, resistance-temperature nonlinear mapping table; T target 1. Heating to target temperature; t probe Active disturbance detection period; I(t), driving current; u(t), driving voltage; f0, fundamental frequency of the power grid; M0, fundamental amplitude of the driving current; M n The amplitude of the nth harmonic of the driving current; I rms (t), RMS current value; u rms (t), effective voltage value; R current Current estimated resistance value; T current、 Current estimated temperature; τ max The maximum decay time constant; h local Local equivalent convective heat transfer coefficient; THD base High-frequency total harmonic distortion (THD) benchmark; P safe Safe power; D safe Safety duty cycle; ΔT; temperature difference between target temperature and current temperature; D normal The normal duty cycle output by the PID algorithm; Δt normal PID algorithm control cycle; Δt safe Control cycle under anti-coking control mode; I rms (t), RMS current value; u rms (t), effective voltage value; P nominal Theoretical benchmark output power. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] In this invention, the driving current I(t) is the instantaneous current value of the electric heating tape acquired in real time; the driving voltage u(t) is the instantaneous voltage value of the electric heating tape acquired in real time.

[0046] Example 1: System Architecture

[0047] like Figure 1 As shown, the novel intelligent control system for the output power of the electric heating cable provided by this invention consists of an AC power grid, a front-end protection circuit (double-pole circuit breaker, varistor), a power execution module (relay), an electric heating cable, a controller (signal conditioning circuit, AD conversion, intelligent control algorithm, opto-isolation drive), a current transformer, a voltage transformer, and other components.

[0048] In an industrial three-phase 380V AC power supply system, after passing through a reverse current and overvoltage protection unit, a relay is connected in series with the live wire. The relay output is connected to an electric heating cable laid on the pipeline. A current transformer is connected to the live wire of the main power circuit to collect the drive current flowing through the electric heating cable in a non-contact manner; a voltage transformer is connected in parallel across the electric heating cable to collect the drive voltage. The weak analog signal output by the transformer is converted into a digital signal by an AD converter after passing through a signal conditioning circuit (DC bias, low-pass filtering, and amplification), and then input to the intelligent control algorithm. The calculation result of the intelligent control algorithm is mapped to a switching timing command, which controls the on / off state of the relay through an opto-isolated drive module, thereby adjusting the output power of the electric heating cable.

[0049] The controller integrates the following functional modules: a phase-locked loop (PLL) for extracting the fundamental frequency of the power grid; a digital notch filter for filtering out the fundamental energy; a fast Fourier transform (FFT) module for spectrum analysis; a Prony algorithm module for dimensionality reduction analysis of the multi-exponential decay model; a thermodynamic parameter inversion module for calculating the local equivalent convective heat transfer coefficient; and an intelligent decision-making module based on the local equivalent convective heat transfer coefficient h. local and high frequency distortion rate (THD) h Determine whether to switch modes; the PID control module is used for conventional heating control; the anti-coking control module is used for calculating the safe duty cycle under extreme adiabatic assumptions.

[0050] Example 2: Intelligent Control Principles and Theoretical Derivation

[0051] This invention periodically switches between two operating modes: "steady-state continuous heating" and "active disturbance detection".

[0052] (1) Construction of state observer

[0053] During the steady-state continuous heating phase, the controller extracts the real-time grid fundamental frequency f0 based on the driving voltage u(t) through a phase-locked loop and performs dual-channel frequency domain analysis on the driving current I(t). The first channel extracts the fundamental amplitude M0 of the driving current through a single-frequency discrete Fourier transform; the second channel filters out the fundamental energy through a digital notch filter, retaining the characteristic energy of the 11th to 40th harmonics, and calculates the high-frequency distortion rate (THD) through a fast Fourier transform. h :

[0054]

[0055] Where M n Let m be the amplitude of the nth harmonic of the driving current, k be the harmonic initiation number (11 in this embodiment), and m be the harmonic termination number (40 in this embodiment). High-frequency distortion rate (THD) h Used to quantify the microscopic insulation degradation state of PTC materials.

[0056] During the steady-state continuous heating phase, the effective value I of the driving current I(t) is calculated using the period 1 / f0 corresponding to the fundamental frequency f0 as the sliding window length. rms The effective voltage values ​​u(t) and driving voltage u(t) rms (t). Meanwhile, based on the effective value of the current I... rms (t) and the effective value of voltage u rms (t), calculate the current estimated resistance value R. current :

[0057]

[0058] Obtain the current estimated resistance value R current Then, based on the resistance-temperature nonlinear mapping table RT, the currently estimated temperature T is obtained by linear interpolation. current .

[0059] During the active disturbance detection phase, the controller forces the relay to shut off for 3-8 seconds, then restores power. The controller uses the actual period 1 / f0 of the phase-locked loop output as a sliding window to calculate the effective value I of the drive current I(t). rms The effective voltage values ​​u(t) and driving voltage u(t) rms Similarly, the current resistance estimate R can be obtained based on formula (2). current And further obtain the currently estimated temperature T current .

[0060] Furthermore, according to the superposition principle, the effective value of the current I rms (t) represents the linear superposition of the transient responses of countless local pipe segments along the line, mathematically expressed as a multi-exponential decay model:

[0061]

[0062] Where I s (t) is the steady-state current, τ k For the k-th decay time constant, A k denoted as amplitude, and N is the number of decay exponents.

[0063] In AD sampling, assume the sampling frequency is f. AD B represents the effective value of the current I obtained within a period of 1 / f0. rms The number of points in (t) yields the pure current decay sequence I. decay (t) is:

[0064]

[0065] The system invokes the Prony algorithm to perform dimensionality reduction analysis on the multi-exponential decay model, and extracts the maximum decay time constant τ.max This allows us to pinpoint the blind spot with the worst heat dissipation conditions in the entire pipeline.

[0066] (2) Inverse calculation of thermodynamic parameters

[0067] According to the law of conservation of energy, the rate of change of local temperature satisfies:

[0068]

[0069] Where C v P represents local equivalent thermal melting. in Where is the input power, h is the convective heat transfer coefficient, S is the equivalent heat transfer surface area, and T is the heating temperature. env The ambient temperature.

[0070] Simplify to the standard form of a first-order inertial element:

[0071]

[0072] With the standard differential equation of a first-order system (Where y(t) is the temperature response and e(t) is the input excitation) By comparison, we can obtain:

[0073]

[0074] The maximum decay time constant τ extracted by Prony max Substitute and inversely derive the local equivalent convective heat transfer coefficient h. local :

[0075]

[0076] in λ This is a dimensionless correction factor, determined based on engineering experience, used for engineering correction of the locally equivalent convective heat transfer coefficient derived by the lumped parameter method. Those skilled in the art can directly determine this value within the above range based on the pipeline diameter, insulation thickness, and actual heat transfer conditions. λ The specific value; λ =1.0 represents the benchmark value for matching the theoretical model with engineering practice.

[0077] Its typical engineering value range is 0.6~1.5: When dealing with large-diameter heavy oil pipelines and laying ultra-thick insulation cotton (pipeline diameter ≥ DN200 and insulation layer thickness ≥ 100mm), radial heat conduction is significantly sluggish. λ Take 1.0≤ λ ≤1.5; For pipelines with smaller diameters or thinner insulation layers (pipe diameter <DN200 or insulation layer thickness <100mm), heat is easily lost. λ Take 0.6≤ λ <1.0.

[0078] By constructing a state observer and calculating thermodynamic parameters, this invention eliminates the need for external temperature sensors and can monitor the convection state of fluids inside pipelines and estimate the temperature of electric tracing cables based on electrical parameters.

[0079] (3) Intelligent decision-making

[0080] The controller monitors the high frequency distortion rate (THD). h and the local equivalent convective heat transfer coefficient h local Set the safe convection heat transfer coefficient h. safe and the high-frequency total harmonic distortion benchmark (THD) base The decision-making logic is as follows.

[0081] For the steady-state continuous heating stage:

[0082] If THD h <THD base If the fluid flow is determined to be smooth, maintain the normal PID control mode; otherwise, switch to the anti-coking control mode and trigger an early warning.

[0083] For the active perturbation detection phase:

[0084] If h local h safe If the condition is met, the normal PID control mode will be maintained; otherwise, the anti-coking control mode will be switched to and an early warning will be triggered.

[0085] (4) Calculation of safe duty cycle for anti-coking control mode

[0086] When switching to anti-coking control mode, to avoid blindly increasing power as is common with traditional PID controllers, the controller performs thermodynamic modeling based on extreme adiabatic conditions. This ensures that the locally high-viscosity fluid does not exceed the preset material pyrolysis temperature T. coke During the control period Δt safe Maximum safe energy Q allowed to be injected safe and the corresponding safe power P safe for:

[0087]

[0088] Where T current The current estimated temperature (obtained by interpolation via the resistance-temperature nonlinear mapping table RT), T margin This is the preset engineering safety margin (recommended 20℃).

[0089] Furthermore, based on the effective value of the grid voltage u rms (t) Calculate the safe duty cycle D under anti-coking conditions, given the nominal cold resistance R0 of the electric heating tape. safe :

[0090]

[0091] Where P nominal This is the theoretical reference output power.

[0092] To prevent the calculated duty cycle value from being excessively high under extreme low-pressure conditions, a safe duty cycle D is specified. safe Apply a software clamp (e.g., limit it to no more than 15%). The controller's internal PWM timer maps the clamped duty cycle to the control cycle Δt in the anti-coking control mode. safe The switching timing instructions (typically 240 seconds) are used to drive the relay via opto-isolation. During the long zero-power off period, the accumulated heat diffuses axially along the tube wall, while the PTC material cools and contracts, releasing the electric field stress.

[0093] Example 3: Online Implementation of the Prony Algorithm

[0094] Long-distance electric heating cables are essentially typical distributed parameter systems. According to the principle of linear superposition, the total transient current detected at the control end perfectly matches the linear combination form of multiple exponential decays in the mathematical model. The Prony algorithm is specifically designed for transient exponential damping and frequency estimation of discrete time series. It is an effective tool for transforming nonlinear parameter estimation into solving constant-coefficient linear prediction difference equations and complex roots of univariate polynomials.

[0095] In practical deployments, the system's main control chip employs an industrial-grade processor (such as a DSP with a 200MHz clock speed) equipped with a floating-point arithmetic unit, which can directly call the matrix inversion and singular value decomposition APIs of the underlying DSP mathematical function library (such as CMSIS-DSP). In a typical engineering configuration with 256 sampling points and a fitting order of 3, the hardware execution time for a single full-order Prony feature analysis is typically less than 50ms, far less than the pipeline thermodynamic evolution cycle of several minutes or even hours, fully meeting the system's high real-time online computing requirements during active disturbance detection.

[0096] like Figure 4 As shown, the specific calculation process of the Prony algorithm is as follows: based on the effective value of the current I... rms (t) Extract the pure decay sequence; establish an autoregressive model and construct the Toeplitz data matrix; calculate the linear prediction coefficients using the least squares method; solve the characteristic polynomial equation to obtain the complex poles; perform logarithmic operations on the poles to calculate the corresponding time constants, and select the largest value as the largest decay time constant τ. max .

[0097] Example 4: Simulation Case

[0098] To further verify the technical advantages of the present invention, the following comparison results of conventional PID control and the present solution in dealing with the "stagnant water" working condition are presented in combination with simulation data.

[0099] (1) Basic working conditions and model parameter settings

[0100] The basic operating conditions and system parameters for the heavy oil transmission pipeline are set as shown in Table 1.

[0101] Table 1 Operating Conditions and Control System Parameters

[0102]

[0103] The corresponding data for the resistance-temperature nonlinear mapping table RT of the PTC material in the electric tracing cable are shown in Table 2.

[0104] Table 2 Resistance-Temperature Nonlinear Mapping Table RT

[0105]

[0106] (2) Defects of conventional PID control schemes

[0107] Conventional PID control systems rely on real-time feedback from external temperature sensors. However, in practical engineering applications of long-distance heavy oil pipelines, limited hardware procurement costs and complex on-site installation processes necessitate the use of a limited number of temperature sensors with large intervals and sparse distribution along the pipeline. This inevitably results in a spatial monitoring blind zone of tens or even hundreds of meters between two temperature measurement nodes. If a pump or valve malfunctions, causing heavy oil to stagnate, and the stagnation zone happens to occur within this blind zone, the PID controller will continue to blindly output continuous power based on the normal readings from the remote sensor. The temperature in the stagnation zone will rapidly rise and exceed the 250°C cracking threshold, leading to irreversible high-temperature agglomeration of the heavy oil and ultimately clogging the pipeline.

[0108] (3) Simulation of the intelligent control scheme of the present invention

[0109] Example 1:

[0110] During the steady-state heating phase, such as Figure 5 As shown, when a "dead water zone" occurs, the current waveform exhibits obvious glitches and distortion (the curve marked "coking" in the figure). The spectrum is obtained using a digital notch filter and Fast Fourier Transform. Figure 6The high-frequency distortion rate was calculated as follows: 2.42% under normal pipeline conditions, rising to 8.34% after the "dead water zone" appeared, exceeding the 5% high-frequency total harmonic distortion rate benchmark. Simultaneously, the system obtained an effective current value of 1.41A and an effective voltage value of 140.62V, estimating the current resistance at 99.73Ω. Based on linear interpolation using the resistance-temperature nonlinear mapping table RT (Table 2), the temperature was determined to have climbed to 179.46℃. At this point, the system issued an alarm signal and immediately switched to anti-coking control mode.

[0111] Example 2:

[0112] Assuming that at the end of the steady-state heating phase, the heavy oil in the pipeline experiences only a slight, insignificant stagnation, resulting in a calculated high-frequency distortion rate lower than the high-frequency total harmonic distortion rate benchmark, thus not triggering the anti-coking control mode. Once the active disturbance detection cycle of 600 seconds is reached, the active disturbance detection phase begins, such as... Figure 7 As shown, the stagnation of heavy oil worsens, leading to a "dead water zone." Because heat cannot be dissipated in this zone, the transient start-up current exhibits a hysteretic decay characteristic. The controller, based on the Prony algorithm, extracts a maximum time constant of 290.42 and calculates the local equivalent convective heat transfer coefficient: 204.93 W / (m²) under normal conditions. 2 ·K), the "dead water zone" dropped to 10.33 W / (m³). 2 ·K), below the safety threshold of 20 W / (m 2 ·K). Simultaneously, the system obtains an effective current value of 1.41A and an effective voltage value of 140.62V, therefore the current estimated resistance is 99.73Ω. Based on linear interpolation using the resistance-temperature nonlinear mapping table RT (Table 2), the temperature has climbed to 179.46℃. Because h local =10.33<20, the system determines that there is a risk of coking, issues an alarm signal and immediately switches to anti-coking control mode.

[0113] In Examples 1 and 2 above, when the system switches to the anti-coking control mode, the system will calculate the safe energy based on the extreme adiabatic assumption and the pyrolysis temperature of 250°C. The theoretical adiabatic duty cycle is 79.87%, exceeding the upper limit of 15%, therefore the final execution duty cycle is locked at 15%. The anti-coking PWM cycle is three times the conventional PID control cycle, and the output switching timing instructions are as follows: Figure 8 As shown, during the long zero-power shutdown period, the accumulated heat can slowly diffuse axially into the pipeline, and the core temperature of the blind zone is effectively locked below the pyrolysis temperature, preventing material pyrolysis and denaturation.

[0114] Example 5: Control Flow

[0115] The complete process of the intelligent control method for the output power of the electric heating cable of the present invention is as follows: Figure 2 and Figure 3 As shown, the specific steps include:

[0116] Step 1: The controller senses the driving voltage u(t) and driving current I(t) of the electric heating cable in real time through current transformers and voltage transformers, and performs calculations after signal conditioning and AD conversion.

[0117] Step 2: Determine if the current timing has reached the active disturbance detection period t. probe If the target is not reached, proceed to step 3; if the target is reached, proceed to step 6. On the first run, proceed directly to step 6 to perform the initial probe.

[0118] Step 3 (Steady-state continuous heating): Calculate the effective value of the current I rms (t), effective voltage value u rms (t), Current estimated resistance value R current Look up the resistance-temperature nonlinear mapping table RT and interpolate the value to the currently estimated temperature T. current The fundamental amplitude M0 of the driving current is extracted by FFT, and the nth harmonic amplitude M of the driving current is obtained by digital notch filter and FFT. n Calculate the high-frequency distortion rate (THD) according to formula (1). h .

[0119] Step 4 (Intelligent Decision-Making Process): For the steady-state continuous heating stage, if THD h <THD base If the condition is met, proceed to step 8 (normal PID mode); otherwise, output an alarm and proceed to step 5 (anti-coking mode).

[0120] Step 5 (Anti-coking control mode): Calculate the safe power P according to formula (10). safe Calculate the safe duty cycle D according to formula (11). safe Then clamp and map the switching timing of the control cycle under the anti-coking control mode, and proceed to step 9.

[0121] Step 6 (Active Disturbance Detection): After forcibly turning off the relay for 6 seconds, restore power supply, collect the drive current I(t) and drive voltage u(t) after power supply is restored, and calculate the effective value of the current I. rms (t), effective voltage value u rms (t), Current estimated resistance value R current Look up the resistance-temperature nonlinear mapping table RT and interpolate the value to the currently estimated temperature T. current The Prony algorithm is used to calculate the effective value of the current I. rms (t) Perform dimensionality reduction analysis on the multi-exponential decay model and extract the maximum decay time constant τ. max The local equivalent convective heat transfer coefficient h is calculated according to equation (8). local .

[0122] Step 7 (Intelligent Decision-Making Process): For the active disturbance detection stage, if h local h safe If the condition is met, proceed to step 8 (normal PID mode); otherwise, output an alarm and proceed to step 5 (anti-coking control mode).

[0123] Step 8 (Conventional PID control mode): Calculate ΔT=T target -T current Substituting the difference ΔT into the PID algorithm, we obtain the normal duty cycle D output by the PID algorithm. normal This is mapped to the PID algorithm control period Δt. normal The switching timing.

[0124] Step 9: The switching timing command drives the relay via opto-isolation to control the output power of the heating tape, and then returns to Step 1 in a loop.

[0125] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art can make various improvements and modifications without departing from the spirit and principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for intelligent control of the output power of an electric heating tape, applied to the heating control of pipelines carrying high-viscosity non-Newtonian fluids such as heavy oil and asphalt, characterized in that... Includes the following steps: Step S1: Real-time acquisition of the driving voltage u(t) and driving current I(t) of the electric heating tape; Step S2: Determine whether the preset active disturbance detection period t has been reached at the current time. probe ; If the target is not reached, the system will enter steady-state continuous heating mode and execute steps S3 to S4. If the target has been reached, then enter the active disturbance detection mode and execute steps S5 to S6. Step S3: Extract the fundamental frequency f0 of the power grid based on the driving voltage u(t), and calculate the effective value I of the driving current I(t) using the period 1 / f0 corresponding to the fundamental frequency f0 as the sliding window length. rms The effective voltage values ​​u(t) and driving voltage u(t) rms (t); Perform a Fast Fourier Transform (FFT) on the driving current I(t) to obtain the fundamental amplitude M0, and after filtering out the fundamental component using a digital notch filter, perform a FFT on the remaining 11th to 40th high-frequency harmonic signals to obtain the amplitudes M of each harmonic. n (n=11,12,…39,40), and then calculate the high-frequency distortion rate (THD). h Meanwhile, based on the effective value of the current I rms (t) and the effective value of voltage u rms (t), calculate the current estimated resistance value R. current And based on the resistance-temperature nonlinear mapping table RT, the current estimated temperature T is obtained by linear interpolation. current ; Step S4: Based on the high frequency distortion rate (THD) h Make intelligent decisions: If the high frequency distortion rate (THD) h Less than the preset high-frequency total harmonic distortion (THD) benchmark base If the condition is met, the normal PID control mode is maintained and the corresponding duty cycle command is output, i.e., step S9 is executed; otherwise, the anti-coking control mode is switched to, i.e., step S8 is executed. Step S5: Forcefully shut off the relay, restore power supply after a preset very short time, collect the drive current I(t) and drive voltage u(t) after power supply is restored, and calculate the effective value of the current I using the period 1 / f0 corresponding to the fundamental frequency f0 as the sliding window length. rms (t) and the effective value of voltage u rms (t), using the Prony algorithm to calculate the effective value of the current I. rms (t) Perform dimensionality reduction analysis on the multi-exponential decay model and extract the maximum decay time constant τ. max Meanwhile, based on the effective value of the current I rms (t) and the effective value of voltage u rms (t), calculate the current estimated resistance value R. current And based on the resistance-temperature nonlinear mapping table RT, the current estimated temperature T is obtained by linear interpolation. current ; Step S6: According to the law of conservation of energy, use the formula Calculate the local equivalent convective heat transfer coefficient h of the current pipeline with the worst heat dissipation. local C v For the local equivalent heat capacity, S is the equivalent heat transfer surface area, and λ is the dimensionless correction coefficient; then proceed to step S7. Step S7: Based on the local equivalent convective heat transfer coefficient h local Make intelligent decisions: if the local equivalent convective heat transfer coefficient h local Greater than the safe convection heat transfer coefficient h safe If the condition is met, the normal PID control mode is maintained and the corresponding duty cycle command is output, i.e., step S9 is executed; otherwise, the anti-coking control mode is switched to, i.e., step S8 is executed. Step S8: First, output an alarm signal. Then, based on the extreme adiabatic assumption, that is, assuming that the local equivalent convective heat transfer coefficient is zero, calculate the maximum safe energy that can be injected according to the first law of thermodynamics. and the corresponding safe power Then the safe duty cycle can be calculated. And the safe duty cycle D safe Perform clamping processing with a preset upper limit value; where T coke T is the preset material pyrolysis temperature. margin As a preset engineering safety margin, R0 is the nominal cold resistance of the electric heating tape, Δt safe The control cycle under the anti-coking control mode; Step S9: Combine the duty cycle and corresponding conventional PID control period t generated in step S4 using the conventional PID control mode. normal Or the safe duty cycle D generated by the anti-coking control mode in step S7. safe and the corresponding control period Δt safe The sequence is mapped to a switching timing instruction, which drives the relay to perform on / off actions through opto-isolation, thereby controlling the output power of the electric heating tape; then the process returns to step S1 and loops.

2. The intelligent control method for the output power of the electric heating tape according to claim 1, characterized in that, The specific implementation of the Prony algorithm in the active perturbation detection mode includes: Based on the collected RMS current value I rms (t) Extract the pure decay sequence after removing the steady-state component, establish an autoregressive model and construct the Toeplitz data matrix, solve for the linear prediction coefficients using the least squares method, then solve the characteristic polynomial equation to obtain the complex poles, take the logarithm of the poles to calculate the corresponding time constants, and select the largest value as the largest decay time constant τ. max .

3. The intelligent control method for the output power of the electric heating tape according to claim 1, characterized in that, The dimensionless correction coefficient λ The value range is 0.6 to 1.5; for pipelines with a diameter ≥ DN200 and an insulation layer thickness ≥ 100mm, λ Take 1.0≤ λ ≤1.5; for pipelines with a diameter <DN200 or an insulation layer thickness <100mm, λ Take 0.6≤ λ <1.

0.

4. The intelligent control method for the output power of the electric heating tape according to claim 1, characterized in that, In the aforementioned anti-coking control mode, the safe duty cycle D safe The upper limit clamping value is 15%~20%.

5. The intelligent control method for the output power of the electric heating tape according to claim 1, characterized in that, The active disturbance detection period t probe The time is 300 to 600 seconds, the extremely short time of the forced shutdown is 3 to 8 seconds, and the acquisition time of the driving current I(t) is 10 to 60 seconds.

6. The intelligent control method for the output power of the electric heating tape according to claim 1, characterized in that, In the anti-coking control mode, steps S5 and S6 are re-executed during each power-on pulse to dynamically update the local equivalent convective heat transfer coefficient h. local When the condition for maintaining the normal PID control mode in step S7 is met, the anti-coking control mode is automatically exited and the normal PID control mode is restored.

7. An intelligent control system for the output power of an electric heating cable, used to implement the method according to any one of claims 1 to 6, characterized in that, include: The main power circuit consists of an AC power grid, a front-end overcurrent and overvoltage protection unit, a relay, and an electric heating tape laid on the pipeline, connected in series. Electrical signal acquisition unit: includes a current transformer connected to the live wire of the main circuit and a voltage transformer connected in parallel to both ends of the electric heating tape, which are used to acquire the driving current and driving voltage in real time, respectively. Signal conditioning and analog-to-digital conversion unit: connected to the output terminals of the current transformer and voltage transformer, used for DC biasing, filtering, amplification and analog-to-digital conversion of analog signals; Controller: The controller integrates a phase-locked loop module, a digital notch filter module, a fast Fourier transform module, a Prony algorithm module, a thermodynamic parameter inversion module, an intelligent decision-making module, a PID control module, and an anti-coking control module; the controller receives the digital signal after analog-to-digital conversion, executes the steps of the method described in any one of claims 1 to 6, and outputs switching timing instructions; Opto-isolated drive unit: Receives the switching timing instructions from the controller and drives the relay to perform on / off actions.

8. The intelligent control system for the output power of the electric heating tape according to claim 7, characterized in that, The controller is an industrial-grade DSP processor with a floating-point arithmetic unit, with a main frequency of not less than 200MHz, and has a CMSIS-DSP mathematical function library embedded in it to accelerate matrix operations. The controller also contains the corresponding data of the resistance-temperature nonlinear mapping table RT of the electric heating tape, which is used to estimate the resistance value R based on the real-time calculated current resistance value. current The estimated temperature T is obtained through one-dimensional interpolation. current .

9. The intelligent control system for the output power of the electric heating tape according to claim 7, characterized in that, The anti-coking control module is configured to: when the intelligent decision module determines that the system is entering the anti-coking control mode, forcibly switch the control cycle to the control cycle Δt of the anti-coking control mode. safe This period is at least the conventional PID control period t. normal It is 3 times the maximum, and the output duty cycle is clamped to no more than the preset upper limit.

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