Control method and system for intelligent control loop of power distribution cabinet

Abstract

The invention belongs to the technical field of power distribution cabinets, and particularly relates to an intelligent control loop control method and system for a power distribution cabinet, and the system comprises a sensor module, a control unit module, a wireless communication module, and a remote monitoring center. The sensor module collects the voltage, current, temperature and smoke concentration of each loop in the power distribution cabinet, the sensor module transmits the collected data to the control unit module for processing and analysis, and the control unit module receives the data transmitted by the sensor module through a network and sends the data to the power distribution cabinet. The control unit module is used for processing and analyzing the data according to a preset algorithm and judging whether the power supply state is abnormal or not, and when the power supply state is abnormal, the control unit module immediately sends emergency alarm information to a remote monitoring center through the wireless communication module, so that quick response and processing are facilitated. According to the invention, a microprocessor is integrated as a core control unit, and a sensor network is combined to realize real-time monitoring and intelligent management of the power supply state of each loop in the power distribution cabinet.

Description

Technical Field

[0001] The present invention belongs to the technical field of power distribution cabinets, and in particular relates to an intelligent control loop control method and system for a power distribution cabinet. Background Art

[0002] The semiconductor electrical power supply and distribution cabinet products currently on the market follow relevant standards (such as GB5266.1-2002 / IEC60204.1-2000, SEMIS2, SEMI S22, etc.) in terms of device selection, assembly, cabinet design, safety interlocking, etc., and realize basic functions such as multi-way distribution of power circuits, leakage protection, and start / stop control circuits in functional design, but most of these products rely on traditional electrical control methods and are not highly intelligent. In particular, in the design of control circuits, there is a lack of flexibility and intelligent monitoring capabilities, making it difficult to achieve real-time monitoring of power supply status, fault warning, and rapid response in emergency situations. In addition, although the existing distribution cabinets are equipped with smoke sensors in terms of smoke alarms and fire and smoke protection, they often have a single post-alarm processing measure and lack the ability to automatically cut off the power supply and link with the remote monitoring system, resulting in untimely response to accidents, which may aggravate losses.

[0003] Therefore, the present invention provides an intelligent control loop control method and system for a distribution cabinet, which can realize real-time monitoring, intelligent control, dynamic load management, rapid response in emergency situations and modular design of the distribution cabinet, thereby improving the intelligence level and safety of the distribution cabinet. Summary of the invention

[0004] The present invention provides an intelligent control loop control method and system for a power distribution cabinet, which are used to solve the technical problems that the control loop of the existing power distribution cabinet lacks flexibility and intelligent monitoring capability, and lacks the ability to automatically cut off power and link with a remote monitoring system.

[0005] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present invention is as follows: an intelligent control loop control system for a distribution cabinet, the loop control system comprising a sensor module, a control unit module, a wireless communication module and a remote monitoring center, the sensor module respectively collects the voltage, current, temperature and smoke concentration of each loop in the distribution cabinet, the sensor module transmits the collected data to the control unit module for processing and analysis, after the control unit module receives the data transmitted by the sensor module network, it processes and analyzes the data according to a preset algorithm to determine whether the power supply status is abnormal, when the power supply status is abnormal, the control unit module will immediately send an emergency alarm message to the remote monitoring center through the wireless communication module to facilitate rapid response and processing.

[0006] A method for controlling an intelligent control loop of a power distribution cabinet comprises the following steps:

[0007] (1) Data collection: The sensor module collects the voltage, current, temperature and smoke concentration of each circuit in the distribution cabinet;

[0008] (2) Transmission analysis: After receiving the data transmitted by the sensor module network, the control unit module processes and analyzes the data according to a preset algorithm, and identifies the power supply status through a comprehensive judgment algorithm. If there is a fault, the overload, short circuit, leakage, overtemperature, and smoke concentration detection algorithm is used to reversely infer its abnormal variables, thereby finding the cause of the fault and determining whether the power supply status is abnormal;

[0009] (3) Quick response: When the power supply status is abnormal, the control unit module will immediately send emergency alarm information to the remote monitoring center through the wireless communication module to facilitate quick response and processing.

[0010] Compared with the prior art, the present invention has the following beneficial effects:

[0011] (1) The present invention integrates a control unit with a microprocessor as the core, combined with a sensor network, to achieve real-time monitoring and intelligent management of the power supply status of each circuit in the distribution cabinet, thereby realizing functions such as multi-way distribution of the power circuit, leakage protection, and start / stop control circuit.

[0012] (2) The present invention optimizes power distribution through intelligent algorithms, realizes dynamic load management, improves energy efficiency, and can quickly cut off power and send alarm information in an emergency, effectively avoiding the expansion of accidents and ensuring the safety of personnel and equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a structural diagram of the intelligent control loop control system of the present invention. DETAILED DESCRIPTION

[0014] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0015] like Figure 1As shown, an intelligent control loop control system of a distribution cabinet, the loop control system includes a sensor module, a control unit module, a wireless communication module and a remote monitoring center, the sensor module respectively collects the voltage, current, temperature and smoke concentration of each loop in the distribution cabinet, the sensor module transmits the collected data to the control unit module for processing and analysis, after the control unit module receives the data transmitted by the sensor module network, it processes and analyzes the data according to a preset algorithm to determine whether the power supply status is abnormal, when the power supply status is abnormal, the control unit module will immediately send an emergency alarm message to the remote monitoring center through the wireless communication module, so as to facilitate rapid response and processing.

[0016] The sensor network consists of multiple different types of sensors, including voltage sensors, current sensors, temperature sensors, and smoke sensors, which are responsible for collecting key parameters such as voltage, current, temperature, and smoke concentration of each circuit in the distribution cabinet. These sensors are connected to the control unit module through wired or wireless means, and transmit the collected data to the control unit module for processing and analysis.

[0017] The control unit module is based on an integrated microprocessor and processes and analyzes data according to preset algorithms, which include overload, short circuit, leakage, overtemperature, smoke concentration detection algorithms and comprehensive judgment algorithms.

[0018] (1) Comprehensive judgment algorithm

[0019] The steps of the comprehensive judgment algorithm are:

[0020] 1) Preprocessing and feature extraction of the data of the sensor module;

[0021] 2) judging the data of the sensor module according to preset thresholds and rules;

[0022] 3) Use logistic regression model to fuse data from multiple sensors;

[0023] 4) Make a final judgment based on the integrated data and take measures.

[0024] After extracting the data feature quantity, the control unit module uses it as a training sample to build a logistic regression model. The specific process is as follows:

[0025] 1) Suppose there are n features [x1,x2,...,x n ]、 Represents the signal characteristics of five variables: overload, short circuit, leakage, overtemperature, and smoke concentration: time domain characteristics, frequency domain characteristics, power characteristics, video characteristics, 1 bias term b and the corresponding weights [ω1,ω2,...,ω n, then the model of logistic regression can be expressed as: In the formula, expSigmoid is the activation function in the logarithmic domain, which is used to convert the output into a probability value; σ is the dot product of the weight vector and the feature vector;

[0026] 2) Set the threshold K. The expSigmoid function maps the output of the operating state feature quantity to the interval [0,1], and can identify whether the power supply state is normal according to different values; if H>K, it is recognized that the power supply state fails and an alarm signal is issued; according to the control loop, the fault alarm index is prompted. At this time, the control unit module will automatically take corresponding measures for processing and repair; if H<K, it is recognized that the power supply state is normal.

[0027] Through the comprehensive judgment algorithm, identify the power supply state. If there is a fault, use the overload, short - circuit, leakage, over - temperature, and smoke concentration detection algorithms to reverse - infer its abnormal variables, so as to find the cause of the fault, such as thermal noise interference, electromagnetic, current interference, or device damage, etc.

[0028] (2) Overload detection algorithm

[0029] Overload means that the current exceeds the rated current of the device, which may cause device damage or fire. The overload detection algorithm is usually based on the current threshold judgment.

[0030] Principle formula: If I>I rated (where I is the actual current, I>I rated is the rated current), then it is judged as overload.

[0031] (3) Short - circuit detection algorithm

[0032] Short - circuit means that two points in the circuit are directly connected, resulting in an excessive current. The short - circuit detection algorithm is usually based on the current mutation and voltage drop to judge.

[0033] Principle formula: If ΔI / Δt>threshold (where ΔI is the current change amount, Δt is the time change amount), and U<U threshold (where U is the actual voltage, U threshold is the voltage threshold), then it is judged as a short - circuit.

[0034] (4) Leakage detection algorithm

[0035] Leakage means that the current leaks through an abnormal path, which may cause electric shock or fire. The leakage detection algorithm is usually based on the residual current judgment.

[0036] Principle formula: Residual current I residual =I in -I out (where I in is the input current, I outis the output current).

[0037] If I residual >I leakage_threshold (where I leakage_threshold is the leakage threshold), it is judged as leakage.

[0038] (5) Overtemperature detection algorithm

[0039] Overtemperature means that the temperature of the equipment exceeds its normal operating range, which may cause equipment damage or fire. Overtemperature detection algorithms are usually based on temperature sensor data.

[0040] Principle formula: If T>T max (Where T is the actual temperature, T max , is the maximum allowable temperature), it is judged as overtemperature.

[0041] (6) Smoke concentration detection algorithm

[0042] Excessive smoke concentration usually means the occurrence of fire. The smoke concentration detection algorithm is based on the smoke sensor data.

[0043] Principle formula: If C>C threshold (where C is the actual smoke concentration, C threshold is the smoke concentration threshold), it is judged that the smoke concentration exceeds the standard.

[0044] The specific algorithm working process: First, the sensor signals of the five variables are collected and the feature vectors [x1, x2, ..., x n ], and then encode the characteristic quantities of the five variables. When the output is judged to be abnormal, the output abnormal number is decoded, and the decoded value and the characteristic quantity of each parameter variable are calculated by the overload, short circuit, leakage, overtemperature, and smoke concentration detection algorithm, so as to identify the specific abnormal variable. The present invention can reduce the unnecessary resources that need to be passed through individual algorithms every time a judgment is made. Each time a single algorithm is used for detection, the processing power consumption is large. The present invention uses the collected data for a one-time comprehensive judgment. Under normal circumstances, the judgment of individual algorithms is not required, which reduces the necessary resources for data processing.

[0045] Through the coordinated work of the sensor network and the control unit, the present invention realizes real-time monitoring of the power supply status of each circuit in the power distribution cabinet. Once an abnormal state is detected, an alarm signal will be immediately issued to remind the operator to take timely measures to deal with it, such as issuing an alarm signal, cutting off the power supply of the relevant circuit, etc., to ensure the safe operation of the power distribution cabinet. At the same time, relevant information of the abnormal state, such as the time of occurrence, abnormal type, circuit number, etc., will also be recorded to provide a basis for subsequent troubleshooting and analysis.

[0046] The intelligent control circuit of the power distribution cabinet of the present invention can quickly cut off the power supply of all non-essential circuits and send emergency alarm information to the remote monitoring center through the wireless communication module. The wireless communication module is the key to the transmission of emergency alarm information. The present invention adopts advanced wireless communication technologies, such as 4G / 5G, LoRa, NB-IoT, etc., to achieve real-time communication with the remote monitoring center. Once an emergency is detected, the system will immediately send emergency alarm information to the remote monitoring center through the wireless communication module, including the type of accident, location information, etc., to facilitate rapid response and processing.

[0047] The wireless communication module uses the (Lora) communication module, the ATK-LoRa-02 wireless serial port module, and the Semtech SX1298 RF chip. The chip uses the LoRa modulation and demodulation technology to send data, reduce interference, and expand the transmission distance. Through the +40dBm power amplifier, wireless communication can be ensured under conditions with a sensitivity as low as -168dBm. In addition, the ATK-LoRa-02 module provides three working modes: general mode, wake-up mode, and power saving mode. It supports an operating voltage of 3.3 to 5V, and the operating current can be as low as 2.3μA, achieving low power consumption operation.

[0048] Users can remotely monitor the status of the power distribution cabinet through mobile devices or PC software, adjust setting parameters, and realize intelligent management. This remote control function not only improves management efficiency, but also reduces operation and maintenance costs.

[0049] A method for controlling an intelligent control loop of a power distribution cabinet comprises the following steps:

[0050] (1) Data collection: The sensor module collects the voltage, current, temperature and smoke concentration of each circuit in the distribution cabinet;

[0051] (2) Transmission analysis: After receiving the data transmitted by the sensor module network, the control unit module processes and analyzes the data according to a preset algorithm, and identifies the power supply status through a comprehensive judgment algorithm. If there is a fault, the overload, short circuit, leakage, overtemperature, and smoke concentration detection algorithm is used to reversely infer its abnormal variables, thereby finding the cause of the fault and determining whether the power supply status is abnormal;

[0052] (3) Quick response: When the power supply status is abnormal, the control unit module will immediately send emergency alarm information to the remote monitoring center through the wireless communication module to facilitate quick response and processing.

[0053] The present invention integrates an intelligent control unit and a sensor network to achieve real-time monitoring and intelligent management of the power supply status, thereby improving the safety and energy efficiency of the power distribution cabinet. In an emergency, the power supply can be quickly cut off and an alarm message can be sent, effectively preventing the accident from expanding and ensuring the safety of personnel and equipment.

[0054] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An intelligent control circuit control system for a power distribution cabinet, characterized in that: The circuit control system includes a sensor module, a control unit module, a wireless communication module, and a remote monitoring center. The sensor module collects the voltage, current, temperature, and smoke concentration of each circuit in the power distribution cabinet respectively. The sensor module transmits the collected data to the control unit module for processing and analysis. After receiving the data transmitted by the sensor module through the network, the control unit module processes and analyzes the data according to a preset algorithm to determine whether the power supply status is abnormal. When the power supply status is abnormal, the control unit module immediately sends an emergency alarm message to the remote monitoring center through the wireless communication module for quick response and handling.

2. The intelligent control loop control system of a power distribution cabinet according to claim 1, characterized in that: The sensor module consists of multiple different types of sensors, including a voltage sensor, a current sensor, a temperature sensor, and a smoke sensor, to realize the real-time monitoring of the power supply status of each circuit in the power distribution cabinet.

3. The intelligent control loop control system of a power distribution cabinet according to claim 1, characterized in that: The control unit module takes an integrated microprocessor as the core and processes and analyzes the data according to a preset algorithm. The preset algorithm includes overload, short circuit, leakage, over-temperature, smoke concentration detection algorithms, and a comprehensive judgment algorithm. Through the comprehensive judgment algorithm, the power supply status is identified. If there is a fault, the overload, short circuit, leakage, over-temperature, and smoke concentration detection algorithms are used to reverse-infer the abnormal variables to find the cause of the fault.

4. The intelligent control loop control system of a power distribution cabinet according to claim 3, characterized in that: The steps of the comprehensive judgment algorithm are as follows: 1) Preprocess and extract features from the data of the sensor module; 2) Judge the data of the sensor module according to the preset thresholds and rules; 3) Use a logistic regression model to fuse the data of multiple sensors; 4) Make a final judgment based on the fused data and take measures.

5. The intelligent control loop control system of a power distribution cabinet according to claim 4, characterized in that: After extracting the data feature quantities, the control unit module uses them as training samples to construct a logistic regression model. The specific process is as follows: (1) Suppose there are n features [x1, x2, ..., x n ], a bias term b and the corresponding weights [ω1,ω2,...,ω n ], then the logistic regression model can be expressed as: H; (2) Set a threshold K. The expSigmoid function maps the output of the operating state feature quantity to the [0,1] interval, and can identify whether the power supply status is normal according to different values. If H>K, it is identified that the power supply status has a fault and an alarm signal is sent. According to the control loop, the fault alarm index is prompted. At this time, the control unit module will automatically take corresponding measures for processing and repair. If H<K, it is identified that the power supply status is normal.

6. The intelligent control loop control system of a power distribution cabinet according to claim 3, characterized in that: The overload detection algorithm is based on the current threshold judgment; the short circuit detection algorithm is based on the current mutation and voltage drop for judgment; the leakage monitoring algorithm is based on the residual current judgment; the over-temperature detection algorithm is based on the allowable temperature of the power distribution cabinet for judgment; the smoke concentration detection algorithm is based on the smoke concentration threshold judgment.

7. The intelligent control loop control system of a power distribution cabinet according to claim 1, characterized in that: The wireless communication module selects the ATK-LoRa-02 wireless serial port module, uses the SX1298 radio frequency chip of Semtech, and can ensure wireless communication under the condition that the sensitivity is as low as -168dBm through a +40dBm power amplifier.

8. The intelligent control loop control system of a power distribution cabinet according to claim 7, characterized in that: The wireless communication module has three working modes: general mode, wake-up mode, and power-saving mode, supports a working voltage of 3.3~5V, and the working current can be as low as 2.3μA at the lowest, realizing low-power operation, so as to achieve a quick response in an emergency state.

9. The intelligent control loop control system of a power distribution cabinet according to claim 1, characterized in that: Users can remotely monitor the status of the distribution cabinet through mobile devices or PC software, adjust setting parameters, and realize intelligent management.

10. A method for implementing an intelligent control loop control system of a power distribution cabinet as described in any one of claims 1 to 9, characterized in that: The specific steps include: (1) Data collection: The sensor module collects the voltage, current, temperature and smoke concentration of each circuit in the distribution cabinet; (2) Transmission analysis: After receiving the data transmitted by the sensor module network, the control unit module processes and analyzes the data according to a preset algorithm, and identifies the power supply status through a comprehensive judgment algorithm. If there is a fault, the overload, short circuit, leakage, overtemperature, and smoke concentration detection algorithm is used to reversely infer its abnormal variables, thereby finding the cause of the fault and determining whether the power supply status is abnormal; (3) Quick response: When the power supply status is abnormal, the control unit module will immediately send emergency alarm information to the remote monitoring center through the wireless communication module to facilitate quick response and processing.

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