Heat tracing control system based on LoRa and 4G wireless technology

Abstract

The invention belongs to the technical field of industrial temperature maintenance, and particularly relates to a heat tracing control system based on LoRa and 4G wireless technology, the heat tracing control system is composed of an integrated control system and an intelligent management system, and the integrated control system is mainly used for real-time execution control: by means of a high-precision sensor and a wireless communication architecture, PID dynamic adjustment of temperature of each heat tracing pipeline is realized; the zero-crossing detection circuit is matched with the zero-crossing trigger type solid-state relay to realize zero-crossing trigger power control and is used for suppressing harmonic waves of a power system; the intelligent management system is mainly used for analyzing global data, insighting energy consumption and carrying out risk early warning at the same time; the state is visualized, and multi-dimensional parameter monitoring and fault positioning are carried out; and configuring a remote strategy to realize mode switching. By means of the closed-loop PID algorithm and the stepless voltage regulation technology of the power regulation device, + / -1 DEG C precise temperature control is achieved, meanwhile, data are transmitted in real time through wireless communication, the heating requirement and power output are dynamically matched, and a multi-collaborative intelligent heat management network is constructed.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial temperature maintenance, and in particular relates to a heat tracing control system based on LoRa and 4G wireless technologies. Background Art

[0002] Heat tracing control is an industrial temperature maintenance technology that actively heats pipelines, storage tanks, and other equipment to compensate for heat loss, ensuring stable operation of internal media (such as water, oil, and chemical fluids) within a specific temperature range. Its primary purpose is to prevent solidification (such as crude oil antifreeze), crystallization, or increased viscosity of the medium, thereby ensuring process continuity. Typical applications include anti-condensation of oil pipelines, thermal insulation of pharmaceutical water, and constant temperature operation of chemical reactors.

[0003] Problems with existing technologies: 1. Energy waste and low temperature control accuracy Disadvantages of traditional heat tracing control: The heating cables often run at full power all day, resulting in serious energy waste; temperature control relies on mechanical thermostats with an accuracy of only ±5°C, which are prone to overshoot or delayed response; 2. Insufficient Safety and Power Grid Pollution Disadvantages of traditional heat tracing control: Phase power modulation generates high-order harmonics (THD>30%), which interfere with the power grid; 3. Short communication distance and poor networking flexibility Disadvantages of traditional heat tracing control: Reliance on wired / short-range wireless technologies such as RS485 and ZigBee, limited coverage (usually less than 100m), requiring extensive wiring; expansion is difficult, and adding new nodes requires re-planning of wiring, which is costly. Summary of the Invention

[0004] The purpose of this invention is to provide a heating control system based on LoRa and 4G wireless technology, which can achieve ±1°C precise temperature control with the help of a closed-loop PID algorithm and stepless voltage regulation technology of a power regulating device. At the same time, it uses wireless communication to transmit data in real time, dynamically match heating demand and power output, and build a multi-coordinated intelligent thermal management network.

[0005] The technical solutions adopted by the present invention are as follows: The heat tracing control method based on LoRa and 4G wireless technology, including the PID dynamic adjustment method, has the following specific steps: Data collection and preprocessing; Cloud-based PID calculation and decision-making: After data is transmitted to the intelligent management system cloud platform, the platform calculates the target power in real time; Instruction issuance and power execution: control instructions are issued to the target heating base station, which analyzes the instructions, dynamically adjusts the PWM duty cycle, controls the heating belt power, and implements zero-crossing conduction to achieve harmonic suppression; Closed-loop calibration and safety protection.

[0006] In the data collection and preprocessing, an industrial-grade digital temperature sensor is used to collect and process the data through SPI / I 2 The C interface is connected to the MCU main control chip in the heating base station, and temperature data is collected every 10-30 seconds; An RC low-pass filter is used to suppress high-frequency noise, and a sliding average filter and a Kalman filter are used to eliminate environmental transient interference; The MCU main control chip sends the filtered temperature data to the intelligent management system.

[0007] The temperature data is sent to the intelligent management system in three forms: Method 1: The MCU main control chip packages the filtered temperature data into LoRa frames and sends them to the gateway LoRa through spread spectrum modulation. The gateway LoRa then sends the data information to the intelligent management system. Method 2: The MCU main control chip sends the filtered temperature data to the built-in IoT card of the heating base station, and the gateway uploads the data to the intelligent management system through the 4G module; Method 3: The MCU main control chip packages the filtered temperature data into a data packet through the built-in Bluetooth module of the heating base station and sends it to the smart device equipped with the heating intelligent control APP.

[0008] The step of the platform calculating the target power in real time includes: Quickly respond to the deviation between the measured temperature and the set value, and increase the P weight when the temperature difference reaches the limit value; Accumulate historical deviations to eliminate steady-state errors caused by pipeline material differences; Predict temperature change trends, suppress overshoot, and combine current sensor data to dynamically constrain the PID output range.

[0009] The step of the heating base station parsing instruction includes: After the MCU main control chip in the heating base station analyzes the instruction, it drives the solid-state relay to conduct when the AC power crosses zero; The zero-crossing detection circuit generates a trigger pulse, and the PWM dynamically adjusts the duty cycle to accurately control the power of the heating cable.

[0010] The step of achieving harmonic suppression by zero-crossing conduction includes zero-crossing point detection and instruction generation: The grid voltage signal is input into the comparator through the voltage divider circuit, and a 5V TTL pulse signal is output when the AC voltage passes through zero. The MCU main control chip has a built-in PLL algorithm that samples the grid frequency in real time and dynamically adjusts the zero-crossing trigger timing to compensate for grid fluctuations. The zero-crossing pulse triggers the GPIO external interrupt. After the MCU main control chip in the heating base station receives the pulse, it immediately generates a zero-crossing trigger type solid-state relay trigger instruction in the interrupt service program.

[0011] Furthermore, it also includes dynamic power adjustment and harmonic suppression: The solid-state relay is turned on at the detected zero-crossing point to synchronize the current waveform with the voltage phase, avoiding the 3rd / 5th / 7th harmonics caused by the step current; Set the number of solid-state relay conduction cycles according to the PID calculation results; The MCU main control chip analyzes the current waveform, calculates the total harmonic distortion rate, and automatically reduces the maximum PWM duty cycle when it exceeds the limit.

[0012] Furthermore, it also includes cloud-based collaborative optimization: The system deploys an LSTM model on the cloud to analyze historical THD data and predict the harmonic risk level in the next 24 hours; If the predicted THD is greater than 5%, a PWM duty cycle limit adjustment instruction is automatically generated and sent to all heating base station nodes; When the cloud detects multi-node harmonic anomalies, it automatically triggers the grid quality inspection process and pushes an operation and maintenance work order.

[0013] The heating control system based on LoRa and 4G wireless technology uses a heating control method based on LoRa and 4G wireless technology, including: Integrated control system: The PID temperature of each heating pipeline is dynamically adjusted through high-precision sensors and wireless communication architecture; Through the zero detection circuit and the zero-crossing triggered solid-state relay, the zero-crossing triggered power control is used to suppress the power system harmonics; Executes rapid power-off due to overload / short circuit, and has an alarm function for situations that affect system stability; Intelligent management system: Used to analyze global data, gain insights into energy consumption and provide risk warnings; Visualize status, implement multi-dimensional parameter monitoring and fault location; Configure remote policies to implement mode switching; The integrated control system relies on the hardware layer to perform overload cutoff and temperature fine-tuning; the intelligent management system relies on cloud computing power to formulate energy efficiency strategies and analyze the root causes of faults; the integrated control system and the intelligent management system form a closed data flow loop, combining safety and energy efficiency linkage.

[0014] An electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the heating control method based on LoRa and 4G wireless technologies.

[0015] The technical effects achieved by the present invention are: This invention uses a high-precision temperature sensor measurement module and PID algorithm to monitor equipment temperature in real time and dynamically adjust output power. The temperature control accuracy can reach ±1°C. Compared with other thermostats, it can save 10%-30% of electricity consumption throughout the year, achieving significant cost reduction and efficiency improvement results. In addition, the use of LoRa self-organizing network / 4G / Bluetooth communication reduces wiring and reduces maintenance costs by 70%.

[0016] The present invention has multiple safety protections, monitors voltage and current in real time and automatically cuts off overload / short circuit, has over-temperature alarm for power regulating device, self-diagnosis of sensor fault and temperature sensor measurement design, supports temperature deviation alarm, and ensures safe and stable operation of the system.

[0017] The present invention adopts zero-crossing control of the power regulating device to avoid harmonics in the power system and improve the stability of the power grid and the reliability of the system.

[0018] The present invention is used in conjunction with host computer software, and the equipment can be freely switched between three modes: constant temperature / industrial temperature control / power limitation according to actual needs, with the characteristics of multi-mode flexible control.

[0019] The solution of the present invention uses wireless communication to transmit data in real time, dynamically matches heating demand with power output, and through AI diagnosis and local visual monitoring, timely obtains power consumption anomalies, leakage or temperature control failure warnings, and builds a multi-coordinated intelligent thermal management network.

[0020] The present invention uses a distributed expansion system to enable the entire communication process to have the characteristics of distributed control and flexible expansion. It supports multi-node distributed control, can expand the number of nodes and control range according to needs, and flexibly adapt to projects of different scales. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 1 is a schematic diagram of communication connections of a heating base station provided by an embodiment of the present invention; Figure 2 4 is a system diagram of a heat tracing control system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose and advantages of the present invention more clearly understood, the present invention is described in detail below with reference to the following examples. It should be understood that the following text is only used to describe one or several specific embodiments of the present invention and does not strictly limit the scope of protection specifically claimed in the present invention.

[0023] like Figure 1 As shown, the heat tracing control system based on LoRa and 4G wireless technology includes a heat tracing control system, which is composed of an integrated control system and an intelligent management system; The integrated control system is designed for rapid edge execution, focusing on real-time response and relying on the hardware layer to perform overload shutdown and temperature fine-tuning. The intelligent management system is designed for cloud-based intelligent decision-making, focusing on long-term optimization and relying on cloud computing power for energy efficiency strategy development and root cause analysis. The integrated control system and intelligent management system form a closed data flow loop, and simultaneously achieve both safety and energy efficiency linkage.

[0024] The integrated control system adopts dynamic temperature control system, multiple protection system, power grid stabilization system and interactive management system.

[0025] (1) Dynamic temperature control system: Through high-precision temperature sensor measurement module and PID algorithm, it monitors the equipment temperature in real time and dynamically adjusts the output power. The temperature control accuracy can reach ±1°C. The core technologies required are as follows: High-precision temperature sensing module: used to collect temperature data collected by temperature sensors arranged at each heating pipeline; Technical Prerequisites: Use an industrial-grade digital temperature sensor (such as the LMT85 or similar devices) with ±0.3°C measurement accuracy. The sensor integrates hardware and software filtering, and uses the MCU to eliminate environmental noise interference. Installation: Directly attach to the surface of the heating cable or key nodes of the pipeline to collect temperature data in real time.

[0026] PID control algorithm: Dynamic tuning mechanism: Proportional term (P): quickly responds to temperature deviations (such as the difference between the set value and the measured value); Integral term (I): accumulates historical deviations to eliminate steady-state errors (such as long-term temperature drift); Differential term (D): predicts temperature change trends and suppresses overshoot; Parameter adaptation: Dynamically adjust PID coefficients according to thermal inertia models (such as pipeline material and environmental heat dissipation coefficient) to adapt to different working conditions.

[0027] Power dynamic adjustment module: Execution unit: controls the solid-state relay or IGBT module through PWM (pulse width modulation) to adjust the power supply voltage (DC12-24V) of the heating pipeline; Energy efficiency optimization: Combined with current detection magnetic sensors (such as the RSCM17100KP101), real-time monitoring of load current can avoid overload and reduce energy consumption.

[0028] Wireless communication architecture: Local transport layer (LoRa): Using the LoRa / 4G version of the heating base station, using modules such as the SX1278 to build a Mesh network, the heating base station nodes connect to the gateway LoRa via wireless communication, with a transmission distance of 3-8km. Finally, the gateway LoRa is used to transmit data to the intelligent management system. Data encryption: End-to-end encryption based on AES-128 prevents tampering. Remote transmission layer (4G): Using LORA / 4G version heating base station, the heating base station node has a built-in IoT card, and the gateway uploads data to the intelligent management system through the 4G module (supporting MQTT protocol) to achieve cross-regional monitoring; Mobile transmission layer (Bluetooth): Using Bluetooth version of the heating base station, the heating base station node is connected to the smart device installed with the heating intelligent control APP through the built-in Bluetooth module. The heating intelligent control APP is the smart device operation terminal of the intelligent management system; Technical prerequisites: The heating base station integrates a power regulation device module, an MCU main control chip, a LoRa or 4G wireless communication module (the Bluetooth version has a built-in Bluetooth module), a temperature sensor interface, a current and voltage acquisition unit, and a high-brightness LCD display module. The entire circuit board adopts an anti-surge and electromagnetic compatibility suppression design to ensure stable operation of the circuit system under harsh working conditions. Among them, the Bluetooth version: has a built-in Bluetooth communication module, and requires a dedicated explosion-proof mobile phone with a built-in APP to scan the device QR code for equipment control and parameter viewing and modification; LORA / 4G version: The shell has an antenna and can be used in conjunction with the host computer for equipment control and parameter viewing and modification. At the same time, it has a built-in Bluetooth chip and also has a stand-alone Bluetooth communication method.

[0029] The specific operation process of output power adjustment is as follows: Step 1: Data collection and preprocessing The temperature sensor collects data every 10-30 seconds, and the data is filtered by the MCU and transmitted through SPI / I 2 C interface sends to the heating base station node; The node packages data (including device ID, temperature value, and timestamp). Method 1: Send it to the gateway LoRa in low-power mode (DR=5), and then transmit it to the intelligent management system. Method 2: The built-in gateway uploads the data to the intelligent management system cloud through the 4G module. Method 3: Transmit it to the built-in APP of a dedicated mobile phone through the built-in Bluetooth communication module.

[0030] Step 2: Cloud PID calculation and decision making After the data is transmitted to the cloud platform, the platform calls the PID algorithm library to calculate the target power in real time; The PID algorithm formula is: , where P is the heat dissipation power, K is the thermal conductivity of the insulation layer, A is the average heat dissipation area of ​​the insulation layer, δ is the average thickness of the insulation layer, and ΔT is the temperature difference between the two sides of the insulation layer; Example: Suppose a section of pipeline needs to maintain a minimum temperature of 10°C to prevent freezing. When the ambient temperature is -10°C, the temperature measurement accuracy of the explosion-proof heating intelligent control base station in this solution reaches 0.1°C, and the temperature control accuracy is less than 1°C. That is, the explosion-proof heating intelligent control base station in this solution can be set to 10°C to prevent the pipeline from freezing. Traditional products have an on-off differential of ±10°C. To ensure the minimum temperature does not fall below 10°C, the temperature setting value should be 10+10=20°C. If this solution and a traditional product are used to insulate the same pipeline, K, A, and δ are the same; Calculate based on the above conditions: The traditional average heating power is: ; The average heating power of this scheme is: ; According to the above formula: ; From this, it can be calculated that under specific circumstances, the energy saving effect of the explosion-proof heating intelligent control base station of this solution can reach 10%-30%, greatly saving the user's electricity consumption.

[0031] Step 3: Command issuance and power execution Taking the above method 1 as an example, the control command is returned to the gateway LoRa, and then broadcast to the target heating base station by LoRa. The heating base station interprets the command, and the PWM dynamically adjusts the duty cycle (for example, from 50% to 70%) to drive the heating pipeline to heat up.

[0032] Step 4: Closed-loop calibration and safety protection Real-time feedback: A new round of temperature data is uploaded to verify the temperature control effect; if the deviation persists >1°C, PID parameter readjustment is automatically triggered; Multiple protections: The current sensor detects short circuit / overcurrent, triggering the air switch to cut off the power; when the temperature exceeds the limit, the platform pushes an APP alarm and activates the backup heating unit.

[0033] According to the content of this solution: through PID dynamic compensation + sensor hardware filtering, the temperature fluctuation is controlled within ±1°C, which can ensure temperature control accuracy; through dynamic power adjustment, ineffective heating is reduced, energy consumption is saved by about 30%, and energy efficiency is improved; through LoRa self-organizing network / 4G / Bluetooth communication, wiring is reduced and maintenance costs are reduced by 70%.

[0034] (2) A multi-layer protection system for real-time monitoring of voltage and current and automatic disconnection of overloads and short circuits. It features over-temperature alarms for power regulators, self-diagnosis of sensor faults, and temperature sensor measurement. It supports temperature deviation alarms to ensure safe and stable system operation. The core technologies required are as follows: Electrical parameter precise monitoring module: Current / voltage detection: Use a magnetic sensor (such as RSCM17100KP101) to collect load current in real time, and use a high-precision ADC (16 bits or more) to measure voltage fluctuations, with a detection accuracy of ±0.5%; Overload / short-circuit protection: When the current exceeds the limit, the solid-state relay (SSR) or IGBT module instantly cuts off the circuit with a response time of <20ms; the integrated resettable fuse (PTC) prevents repeated shocks.

[0035] Over-temperature protection of power regulating device: Temperature monitoring point: Embed a digital temperature sensor (such as DS18B20) in the IGBT / PWM module heat sink to monitor the power device temperature in real time; Hierarchical alarm mechanism: Level 1 warning (>80℃): reduce PWM duty cycle and output power; Level 2 protection (>100℃): force power off and push APP alarm.

[0036] Sensor fault self-diagnosis: Dual-channel calibration: The primary sensor (such as LMT85) and the redundant backup sensor collect data synchronously, and a data difference of >1°C triggers diagnosis; a self-test signal is embedded in the current loop to detect sensor open / short circuit faults; Fault location: Transmit the fault code to the heating base station (such as "ERR101" indicates a temperature sensor failure), and the system platform automatically generates a maintenance work order.

[0037] Temperature deviation dynamic alarm: Intelligent threshold algorithm: Set dynamic alarm thresholds (such as ±2°C floating interval) based on historical temperature curves; sudden change detection (>5°C / min) triggers an emergency state; Multi-level linkage: If the deviation persists for 2 minutes, the backup heating unit will be started and the operation and maintenance personnel will be notified.

[0038] The specific operation process of the system is as follows: Step 1: Real-time monitoring and local decision-making Various types of data are sampled regularly and analyzed for safety after local pre-processing. If it is determined to be safe, the heating base station uploads the data to the intelligent management system. If it is determined to be abnormal, the protection action is executed.

[0039] Step 2: Cloud-based intelligent diagnosis and alarm The heating base station uploads data to the intelligent management system, where the system platform performs the following analyses: temperature trend prediction of the power regulating device (based on the LSTM model) and sensor health assessment (verifying data volatility and correlation). The diagnostic results are pushed to the app and the location of the faulty device is marked (e.g., "Temperature sensor of heating node of pipeline No. 3 is abnormal").

[0040] Step 3: Closed-loop protection and recovery After the fault is eliminated, the system automatically detects the line and gradually restores power supply after confirming safety (PWM increases in steps of 10%). Backup strategy: When the main sensor fails, it switches to the redundant sensor and calibrates the reading deviation.

[0041] According to the content of this plan: the overload cut-off response time is ≤50ms, which is several times faster than traditional thermal relays, greatly improving safety; the sensor fault self-diagnosis accuracy is >95%, the maintenance response time is shortened by 70%, and operation and maintenance are optimized. The system achieves full coverage protection from electrical safety to sensor health through the four-layer closed loop of "sensing-decision-execution-feedback".

[0042] (3) The grid stabilization system uses zero-crossing control of the power regulation device to avoid harmonics in the power system and improve grid stability and system reliability. The core technologies required are as follows: Zero-crossing detection circuit: Technical Prerequisite: Use a high-precision voltage comparator (such as LM393) or an optocoupler isolation device (such as H11AA1) to monitor the AC voltage waveform in real time. When the voltage crosses zero (i.e., the instantaneous value of the voltage is 0V), a pulse signal is generated as a trigger reference. Anti-interference design: Hardware filtering circuit (RC low-pass filtering) combined with software debouncing algorithm to avoid false triggering due to grid noise.

[0043] Zero-crossing trigger solid-state relay (SSR): Execution mechanism: The SSR has a built-in zero voltage switch (ZVS), which only turns on the load circuit when the AC current crosses zero, ensuring that the current waveform is synchronized with the voltage and avoiding harmonics caused by phase mutations. Advantages: Response time ≤ 10ms, no mechanical contacts, and a lifespan of more than 10^7 times, which is superior to traditional electromagnetic relays.

[0044] Adaptive phase synchronization algorithm: Dynamic compensation: The MCU uses the ADC to collect grid frequency (50 / 60Hz) in real time and combines it with phase-locked loop (PLL) technology to dynamically adjust the zero-crossing detection timing to adapt to grid fluctuations. Harmonic suppression: Zero-crossing conduction makes the current waveform close to a sine wave, controlling the total harmonic distortion (THD) to <5% (traditional phase control THD can reach 30%).

[0045] LoRa command coordination mechanism: Low-latency transmission: Using LoRa spread spectrum technology (SF=7, BW=125kHz), the communication delay between the gateway and the node is less than 200ms, ensuring that the power adjustment command is synchronized with the grid cycle; Conflict avoidance: TDMA time division multiple access scheduling sends control instructions in time-sharing to avoid command collisions caused by simultaneous responses from multiple nodes.

[0046] The specific operation process of zero-crossing control is as follows: Step 1: Zero-crossing detection and command generation Zero-crossing pulse generation: The grid voltage signal is input into the comparator through the voltage divider circuit, and a 5V TTL pulse signal is output when the AC voltage crosses the zero point (0V); Phase-locked loop (PLL) compensation: The MCU main control chip has a built-in PLL algorithm that samples the grid frequency in real time (40-70Hz adaptive) and dynamically adjusts the zero-crossing trigger timing to compensate for grid fluctuations. Interrupt response mechanism: The zero-crossing pulse triggers the GPIO external interrupt. After the MCU main control chip in the heating base station receives the pulse, it immediately generates a zero-crossing trigger solid-state relay (SSR) trigger instruction in the interrupt service routine; Example: When the set temperature needs to be increased, the MCU turns on the SSR at the next zero crossing point, so that the heating tape starts at the voltage zero point.

[0047] Step 2: Dynamic power adjustment and harmonic suppression Solid-state relay (SSR) drive: turns on the SSR at the detected zero-crossing point, synchronizing the current waveform with the voltage phase to avoid 3rd / 5th / 7th harmonics caused by step current; Multi-cycle PWM power regulation: The number of SSR conduction cycles is set according to the PID calculation results. For example, in a 50Hz power grid, a 20% duty cycle corresponds to 10 half-waves per second, reducing the high-frequency noise caused by current discontinuity. Harmonic closed-loop suppression: The MCU main control chip analyzes the current waveform, calculates the total harmonic distortion (THD), and automatically reduces the maximum PWM duty cycle when it exceeds the limit.

[0048] Step 3: Cloud Collaborative Optimization Harmonic trend prediction: The system deploys an LSTM model on the cloud to analyze historical THD data and predict the harmonic risk level in the next 24 hours; Dynamic policy issuance: If the predicted THD is greater than 5%, a PWM duty cycle limit adjustment instruction is automatically generated and issued to all heating base station nodes; Fault linkage response: When the cloud detects multi-node harmonic anomalies, it automatically triggers the grid quality inspection process and pushes an operation and maintenance work order.

[0049] According to the content of this plan: reactive power loss is reduced through zero-crossing control, and the comprehensive energy saving rate reaches 18% (compared with phase voltage regulation), which significantly improves energy efficiency; in the pipeline heating system, the grid harmonic interference accidents are reduced by 90%, ensuring stability.

[0050] (IV) Interactive management system: Through the high-brightness LCD screen / APP / host computer, you can observe the real-time temperature, power, alarm and other status on-site or remotely and perform operations such as parameter modification. The specific operation process is as follows: Step 1: Data collection and local display After being processed by the MCU, the data from the temperature sensor and current detection module is sent to the LCD driver via the SPI interface and displayed in the form of dynamic curves / numeric values. When on-site personnel touch to input parameters (such as set temperature values), the LCD generates an operation log and stores it in Flash to prevent loss during power outages.

[0051] Step 2: Remote monitoring and command issuance App / host computer operation: Users log in to the cloud platform and view device status in real time (such as "node 3 power 72%, temperature 45°C"). When modifying parameters, the platform verifies permissions and generates a command packet. Low-latency response: The gateway LoRa processes commands through a priority queue, and critical alarm commands are queued for transmission (delay <500ms).

[0052] Step 3: Multi-terminal status synchronization After the parameters on the LCD screen are modified locally, they are immediately reported to the system cloud, triggering the automatic refresh of the APP / host computer interface; the cloud records all operation flows (including operator IP / time) and supports audit traceability.

[0053] The above-mentioned interaction management technical contents are all existing technologies and will not be described in detail here.

[0054] The intelligent management system adopts a mode switching system, an energy consumption management system, an intelligent early warning system, a multi-dimensional state perception system, and a distribution expansion system.

[0055] (1) The mode switching system is used in conjunction with the host computer software. It can freely switch the equipment between three modes: constant temperature, industrial temperature control, and power limit according to actual needs. The core technologies required are as follows: Upper computer software architecture: Multi-mode strategy engine: Develops a control logic library based on C# / Python, encapsulating three algorithm modules: constant temperature (PID closed loop), industrial temperature control (multi-stage temperature curve), and power limit (threshold priority). Visual configuration interface: supports drag-and-drop setting of temperature curves, power caps, and switching trigger conditions (such as time / event-driven). Data synchronization mechanism: Using MQTT / Modbus TCP protocol, parameter configuration is synchronized in real time between the heating base station and the cloud / local server.

[0056] Edge computing control unit: Dynamic algorithm loading: The controller (such as the STM32F4 series MCU) pre-stores the core code for three modes and switches the running algorithm after receiving instructions from the host computer. For example, the constant temperature mode uses the PID library (proportional coefficient Kp=0.8), and the industrial temperature control mode calls the preset temperature curve table (such as the step temperature increase required by the pharmaceutical process). Local policy cache: stores the last valid instruction and maintains the current mode of operation when communication is interrupted (to prevent loss of control).

[0057] Power dynamic execution module: Multi-mode adapter: Constant temperature mode: PID output PWM duty cycle, accuracy ±1%; Power limit mode: Hard cutoff of excess power (for example, forced reduction of duty cycle to 50% when >2kW); Industrial temperature control mode: Automatic switching of PID parameter groups according to the time axis (for example, increasing the integral term weight in the high temperature section); Zero-crossing trigger protection: SSR zero-crossing switch avoids harmonic generation during mode switching.

[0058] The specific operation process of mode switching operation is as follows: Step 1: Mode configuration and command issuance The user selects a mode (such as "industrial temperature control") on the host computer, sets the temperature curve (0-60 minutes to 90°C), and clicks Send. Taking the previous method 1 as an example, the parameter package is uploaded to the system cloud, encrypted, and pushed to the LoRa gateway in the target area.

[0059] Step 2: Dynamic controller switching The controller parses the instructions and loads the corresponding algorithm: Constant temperature mode: initializes PID parameters (Kp / Ki / Kd); Industrial temperature control mode: reads the preset curve table from Flash and starts the timer for segmented temperature control; Power limit mode: activates the current monitoring interrupt and forces power reduction when the limit is exceeded.

[0060] Status synchronization: Immediately feedback the switching results to the system cloud (such as "mode switching successful").

[0061] Step 3: Execute and close loop calibration The controller outputs PWM signals to drive the heating tape and collects real-time temperature / power at the same time; Abnormal handling: If the industrial temperature control section temperature rise times out, the PID parameters will be automatically readjusted; if the power approaches the threshold, the load will be reduced by 10% in advance (to prevent instantaneous overshoot); After the data is transmitted back, the host computer displays the dynamic curve and alarm status.

[0062] This solution can flexibly adapt to a variety of scenarios, such as constant temperature mode for pharmaceutical storage (±1°C precision temperature control); industrial temperature control to meet the requirements of the stepped thawing process for thermal power plant pipelines; and power limitation for safe operation in explosion-proof areas of chemical plants. Furthermore, remote mode switching via the host computer can reduce on-site commissioning hours by 70%, improving maintenance efficiency.

[0063] (2) The energy consumption management system is internally equipped with an energy consumption data storage and modeling module, an intelligent analysis engine module, a visualization and strategy configuration module, and a dynamic tuning execution module.

[0064] The energy consumption data storage and modeling module is used to build a time series database to store historical energy consumption data and establish a dynamic energy consumption model (such as a power prediction model based on pipeline material and ambient temperature). It also supports data compression storage and fast retrieval, and provides an API interface for the analysis module to call.

[0065] The intelligent analysis engine module can analyze historical data through machine learning algorithms (such as LSTM) to generate baseline energy consumption curves under different operating conditions; it can also compare actual energy consumption with baseline values ​​in real time to identify abnormal scenarios such as overload and ineffective heating (such as sudden current surges exceeding 15A).

[0066] The visualization and policy configuration module is used to provide a Web / APP interface to display real-time energy consumption heat maps, equipment energy efficiency rankings, energy-saving suggestions, etc., and supports custom policies (such as time-sharing temperature control and power limit).

[0067] The dynamic tuning execution module is used to send energy-saving strategies generated in the cloud (such as lowering the pipe insulation temperature by 2°C at night) to the terminal via the 4G / LoRa / Bluetooth link, and dynamically adjust the PID parameters or PWM duty cycle.

[0068] The above-mentioned technical content has the characteristics of energy consumption insight and precise management. It can monitor energy consumption and analyze data in real time, support the formulation of energy-saving strategies, and help reduce operating costs and improve energy efficiency.

[0069] (3) The intelligent early warning system is equipped with a multi-source anomaly detection module, an intelligent analysis and decision-making module, a dynamic hierarchical alarm mechanism, a rapid response and positioning module, and a visual fault tracing system.

[0070] The multi-source anomaly detection module includes an electrical parameter monitoring unit, which uses a high-precision current sensor (such as the RSCM17100KP101) and a voltage detection circuit to collect load current and voltage data in real time, identifying anomalies such as overload (>15A) and short circuits. It also includes an environmental and device status perception unit that monitors overtemperature risks by embedding a digital temperature sensor in the power device heat sink. A three-axis accelerometer is used to detect device vibration anomalies.

[0071] The intelligent analysis and decision-making module includes a multi-dimensional diagnostic engine for data verification and trend prediction. It uses cross-validation between primary and backup sensors (such as the LMT85) to trigger fault diagnosis when the difference exceeds 1°C. It also uses an LSTM model to analyze historical temperature and current curves and predict over-limit risks (such as a temperature trend exceeding 100°C).

[0072] A dynamic, graded alarm mechanism provides differentiated responses based on risk level: Level 1 warning (e.g., temperature > 80°C): automatically reduces power and sends an app notification; Level 2 protection (e.g., short circuit): immediately cuts power and generates a maintenance work order.

[0073] The rapid response and positioning module includes communication alarm distribution. In local response mode, the gateway LoRa broadcasts fault codes to the heating base station or directly sends fault codes to the heating base station with a delay of <200ms. In remote push mode, the 4G gateway sends positioning information (such as "Node 3 overload") to the app / host computer through the MQTT protocol.

[0074] The visual fault tracing system integrates device ID, timestamp, and sensor data through the cloud platform to generate a fault map, and marks abnormal points on the host computer map.

[0075] The above technical content has the characteristics of intelligent alarm and risk warning. The system can automatically analyze operational anomalies, issue alarms in advance, quickly locate problems, and reduce maintenance risks and response time.

[0076] (4) The state multi-dimensional perception system is internally equipped with a multi-dimensional state visualization module and a state synchronization and security module.

[0077] Multi-dimensional state visualization module: through high-brightness LCD screen (500cd / m 2 The device can display current, voltage, temperature curves, and line status on-site (with brightness), and supports touch operation to modify parameters. It can also achieve a "one-screen overview" on the app / host computer, support map positioning of devices, color marking of abnormal lines (red indicates faults), and click to view details.

[0078] State synchronization and security module: Assigns a unique identifier to each device to ensure that data accurately corresponds to physical location and avoid confusion among multiple nodes. When communication is interrupted, the MCU automatically executes the last valid instruction to maintain safe power output and prevent loss of control.

[0079] The above technical content has the characteristics of equipment status and multi-dimensional perception, can comprehensively monitor the equipment operation status, display data such as current, voltage, temperature in real time, and quickly check the status of each line. The above content is all existing technology and will not be elaborated here.

[0080] (5) The distributed expansion system is internally equipped with a dynamic networking communication module, an edge computing control module, and a cloud elastic expansion module.

[0081] The dynamic networking communication module adopts LoRa Mesh self-organizing networking technology, supports automatic registration of new nodes and assignment of unique device IDs, and realizes the star / relay hybrid topology connection of multiple nodes (≥100). It also uses TDMA (Time Division Multiple Access) mechanism to schedule node communication in a time-sharing manner, avoid data collisions, and ensure channel stability during large-scale deployment.

[0082] Edge computing control module: Each heating base station node has a built-in MCU, which locally executes basic control logic such as PID algorithm and overload protection, reducing cloud dependence; it supports policy caching, and when the 4G network is disconnected, it maintains operation according to the last valid instruction to ensure system robustness.

[0083] The cloud elastic expansion module, based on a cloud platform with microservice architecture, dynamically allocates computing resources (such as Kubernetes clusters) through containerization technology to cope with the surge in the number of nodes. It provides a visual configuration interface that supports drag-and-drop addition of new nodes and definition of control rules without modifying the underlying code.

[0084] The process of node expansion is as follows: after the new node is powered on, it sends a network access request to the intelligent management system, and then passes the gateway authentication. If the authentication is passed, an ID is assigned and the configuration is issued. If the authentication is rejected, it is stored locally and waits for retry. The request that passes the authentication is added to the TDMA scheduling queue, and finally the data can be transmitted normally. The above technical content has the characteristics of distributed control and flexible expansion. It supports multi-node distributed control, and the number of nodes and control range can be expanded according to needs, and it can be flexibly adapted to projects of different sizes.

[0085] The foregoing is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications are also within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained herein shall, unless otherwise specified or limited, be implemented in accordance with conventional means in the art.

Claims

1. A heat tracing control method based on LoRa and 4G wireless technology, characterized in that: Including PID dynamic adjustment method, the specific steps are as follows: Step 1: Data collection and preprocessing; Step 2: Cloud PID calculation and decision-making. After the data is transmitted to the intelligent management system cloud platform, the platform calculates the target power in real time. The step of the platform calculating the target power in real time includes: Quickly respond to the deviation between the measured temperature and the set value, and increase the P weight when the temperature difference reaches the limit value; Accumulate historical deviations to eliminate steady-state errors caused by pipeline material differences; Predict temperature change trends, suppress overshoot, combine current sensor data, and dynamically constrain PID output range; Step 3: Instruction issuance and power execution: The control instruction is sent to the target heating base station, which interprets the instruction, dynamically adjusts the PWM duty cycle, controls the heating cable power, and implements zero-crossing conduction to achieve harmonic suppression. The step of the heating base station parsing instruction includes: After the MCU main control chip in the heating base station analyzes the instruction, it drives the solid-state relay to conduct when the AC power crosses zero; The zero-crossing detection circuit generates a trigger pulse, and the PWM dynamically adjusts the duty cycle to accurately control the power of the heating cable; Step 4: Closed-loop calibration and safety protection.

2. The heat tracing control method based on LoRa and 4G wireless technology according to claim 1, characterized in that: In the data collection and preprocessing, an industrial-grade digital temperature sensor is used to collect and process the data through SPI / I 2 The C interface is connected to the MCU main control chip in the heating base station, and temperature data is collected every 10-30 seconds; An RC low-pass filter is used to suppress high-frequency noise, and a sliding average filter and a Kalman filter are used to eliminate environmental transient interference; The MCU main control chip sends the filtered temperature data to the intelligent management system.

3. The heat tracing control method based on LoRa and 4G wireless technology according to claim 2, characterized in that: The temperature data is sent to the intelligent management system through local transmission: The MCU main control chip packages the filtered temperature data into LoRa frames and sends them to the gateway LoRa through spread spectrum modulation. The gateway LoRa then sends the data information to the intelligent management system.

4. The heat tracing control method based on LoRa and 4G wireless technology according to claim 2, characterized in that: The temperature data is sent to the intelligent management system via remote transmission: The MCU main control chip sends the filtered temperature data to the built-in IoT card of the heating base station, and the gateway uploads the data to the intelligent management system through the 4G module.

5. The heat tracing control method based on LoRa and 4G wireless technology according to claim 2, characterized in that: The temperature data is sent to the intelligent management system via mobile transmission: The MCU main control chip packages the filtered temperature data into a data packet through the built-in Bluetooth module of the heating base station and sends it to the smart device equipped with the heating intelligent control APP.

6. The heat tracing control method based on LoRa and 4G wireless technology according to claim 1, characterized in that: The step of achieving harmonic suppression by zero-crossing conduction includes zero-crossing point detection and instruction generation: The grid voltage signal is input into the comparator through the voltage divider circuit, and a 5V TTL pulse signal is output when the AC voltage passes through zero. The MCU main control chip has a built-in PLL algorithm that samples the grid frequency in real time and dynamically adjusts the zero-crossing trigger timing to compensate for grid fluctuations. The zero-crossing pulse triggers the GPIO external interrupt. After the MCU main control chip in the heating base station receives the pulse, it immediately generates a zero-crossing trigger type solid-state relay trigger instruction in the interrupt service program.

7. The heat tracing control method based on LoRa and 4G wireless technology according to claim 6, characterized in that: Also includes dynamic power adjustment and harmonic suppression: The solid-state relay is turned on at the detected zero-crossing point to synchronize the current waveform with the voltage phase, avoiding the 3rd / 5th / 7th harmonics caused by the step current; Set the number of solid-state relay conduction cycles according to the PID calculation results; The MCU main control chip analyzes the current waveform, calculates the total harmonic distortion rate, and automatically reduces the maximum PWM duty cycle when it exceeds the limit.

8. The heat tracing control method based on LoRa and 4G wireless technology according to claim 6, characterized in that: Also includes cloud-based collaborative optimization: The system deploys an LSTM model on the cloud to analyze historical THD data and predict the harmonic risk level in the next 24 hours; If the predicted THD is greater than 5%, a PWM duty cycle limit adjustment instruction is automatically generated and sent to all heating base station nodes; When the cloud detects multi-node harmonic anomalies, it automatically triggers the grid quality inspection process and pushes an operation and maintenance work order.

9. The heating control system based on LoRa and 4G wireless technology is characterized by: The heat tracing control method based on LoRa and 4G wireless technology according to any one of claims 1 to 8 comprises: Integrated control system: The PID temperature of each heating pipeline is dynamically adjusted through high-precision sensors and wireless communication architecture; Through the zero detection circuit and the zero-crossing triggered solid-state relay, the zero-crossing triggered power control is used to suppress the power system harmonics; Executes rapid power-off due to overload / short circuit, and has an alarm function for situations that affect system stability; Intelligent management system: Used to analyze global data, gain insights into energy consumption and provide risk warnings; Visualize status, implement multi-dimensional parameter monitoring and fault location; Configure remote policies to implement mode switching; The integrated control system relies on the hardware layer to perform overload cutoff and temperature fine-tuning; the intelligent management system relies on cloud computing power to formulate energy efficiency strategies and analyze the root causes of faults; the integrated control system and the intelligent management system form a closed data flow loop, combining safety and energy efficiency linkage.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the heating control method based on LoRa and 4G wireless technology according to any one of claims 1 to 8.

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