Freezing station equipment group control system with operation balancing and fault pre-judging functions

Abstract

The invention discloses a freezing station equipment group control system with operation balance and fault pre-judgment functions. The freezing station equipment group control system comprises a data acquisition layer, a local control layer and a cloud supervision layer, the data acquisition layer acquires operation parameters of field equipment of a freezing station and then transmits the operation parameters to the local control layer to provide data support for control decision for the local control layer; and the local control layer receives the operation parameters, then carries out comparative analysis, controls loading, load shedding or shutdown of field equipment of the freezing station according to an analysis result, and executes hierarchical response, thereby realizing balance control of the operation duration and multi-dimensional fault pre-judgment. According to the freezing station equipment group control system, intelligent management and control of freezing station equipment are achieved through cloud-side-end three-layer architecture cooperative linkage, the problem that traditional manual operation and control are weak is solved, reliability, intelligentization and energy saving performance of equipment operation control are considered, and the freezing station equipment group control system is suitable for being popularized and applied. And the long-period continuous operation requirement of the modern mine freezing station can be comprehensively met.

Description

A group control system for freezing station equipment that combines balanced operation and fault prediction Technical Field

[0001] This invention relates to the field of automated control technology for freezing engineering. Specifically, it relates to a group control system for freezing station equipment that combines balanced operation and fault prediction. Background Technology

[0002] Mine shaft freezing is a core construction method in water-rich, soft strata mines. By injecting circulating low-temperature brine (-25℃ to -35℃) into freezing pipes around the shaft, a frozen wall is formed to isolate groundwater and ensure safe tunneling. The freezing station, as the core refrigeration unit, needs to operate continuously for 6-18 months; its reliability directly determines the project's progress, safety, and cost.

[0003] In the current operation of traditional freezing stations, key equipment such as refrigeration units and brine pumps rely on manual inspection and experience-based operation, which presents many technical problems: First, the start-up, shutdown, and scheduling of equipment lack scientific basis, and some units operate at high loads for a long time, leading to accelerated equipment wear and frequent maintenance, thus increasing operation and maintenance costs; Second, fault monitoring is lagging behind, often only being discovered after equipment is severely damaged, causing unplanned shutdowns that affect the stability of the frozen wall and the construction progress; Third, energy consumption management is extensive, the system energy efficiency is low, and it does not meet the requirements of green and low-carbon development; Fourth, there is a lack of remote monitoring capabilities, and on-site operation and maintenance costs are high, making it unsuitable for the centralized management and control needs of deep well projects in remote western regions.

[0004] Existing PLC control systems can only achieve basic logic control such as pressure over-limit shutdown and equipment interlocking start. Due to the lack of an intelligent decision-making module, the above problems cannot be completely solved, and the following defects exist: 1) The balance of equipment operating time is not considered, and load balancing cannot be achieved to extend equipment life; 2) Fault judgment is limited to static threshold alarms, which can only detect faults that have occurred and lack trend analysis and prediction capabilities; 3) Energy consumption analysis and cloud interconnection functions are not integrated, making it difficult to meet the needs of remote management and control of intelligent mines.

[0005] In summary, existing control methods are insufficient for achieving precise regulation, lifespan optimization, risk warning, and remote monitoring of freezing stations, and cannot meet the high reliability, low energy consumption, and intelligent requirements of modern mines. Therefore, developing a comprehensive group control system that integrates dynamic load distribution, intelligent prediction, energy-saving regulation, and cloud interconnection has become an urgent technical challenge. Summary of the Invention

[0006] Therefore, the technical problem to be solved by this invention is to provide a freezing station equipment group control system that can achieve precise regulation, risk warning and remote monitoring of freezing stations to meet the high intelligence needs of modern mines, and has both operation balance and fault prediction. It is applicable to the control of low temperature refrigeration related equipment in coal, metal mines, tunnels and other fields. It solves the technical problems of traditional freezing stations such as "uneven equipment wear, delayed fault response, high energy consumption and difficult operation and maintenance", and realizes the full life cycle management of "intelligent scheduling, early warning and energy saving and efficiency improvement".

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0008] The freezing station equipment group control system, which combines operation balancing and fault prediction, includes a data acquisition layer for collecting on-site equipment operating parameters, a local control layer for realizing local closed-loop control and performing operation balancing and fault prediction, and a cloud monitoring layer for realizing remote monitoring, data storage and analysis and early warning push.

[0009] After the data acquisition layer collects the operating parameters of the field equipment at the freezing station, it transmits the operating parameters to the local control layer to provide data support for the local control layer to make control decisions.

[0010] After receiving the operating parameters transmitted by the data acquisition layer, the local control layer continuously compares the operating parameters with the preset safety thresholds, analyzes the comparison results according to the preset operating logic, and then executes a graded response based on the analysis results, thereby realizing runtime balanced control and multi-dimensional fault prediction.

[0011] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes a data acquisition layer comprising a first temperature sensor for detecting compressor exhaust temperature, a second temperature sensor for detecting brine temperature, a first pressure transmitter for detecting condensation pressure, a second pressure sensor for detecting evaporation pressure, a first current transformer for detecting compressor motor current, a second current transformer for detecting brine pump current, a first level sensor for detecting liquid level in the storage tank, a second level sensor for detecting liquid level in the siphon tank, a third level sensor for detecting liquid level in the evaporation skid, an energy meter for detecting the power consumption of each unit, and a flow switch for real-time monitoring of the brine system circulation status.

[0012] The first temperature sensor is located at the compressor exhaust port, the second temperature sensor is located inside the pipe of the evaporator skid, the first pressure transmitter is located at the condenser inlet, and the second pressure sensor is located at the evaporator outlet; the first current transformer is located inside the compressor motor distribution cabinet, and the second current transformer is located inside the brine pump motor distribution cabinet; the first liquid level sensor is located at the top of the liquid storage tank, the second liquid level sensor is located at the top of the siphon tank, and the third liquid level sensor is located at the top of the evaporator skid; there are three electricity meters, which are respectively installed in the distribution cabinets of the compressor, the evaporator, the condenser, and the brine pump; the flow switch is installed on the main pipeline of the brine system.

[0013] Each sensor and energy meter collects the core physical quantities of the reaction equipment status and system balance in real time, and transmits the collected core physical quantity data to the local control layer through a 4-20mA analog signal or Modbus protocol.

[0014] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes a local control layer comprising a PLC controller for balanced operation and multi-dimensional fault prediction, an edge gateway for transmitting data, analysis results and fault information to the cloud monitoring layer, and a local database for storing equipment operation time, fault records and control parameters.

[0015] The aforementioned freezing station equipment group control system, which combines operational balancing and fault prediction, includes the following steps in the PLC controller's process for performing runtime balancing control:

[0016] Step P1: Read the brine temperature and determine whether the brine temperature exceeds or falls below the set value; if not, continue reading and determining; if yes, proceed to step P2.

[0017] Step P2: Read the running time of similar devices in the local database, and filter the devices with the shortest and longest running times;

[0018] Step P3: Check whether the parameters of the device with the shortest running time selected in step P2 are normal; if not, remove the device with the shortest running time and repeat step P2 to select the device with the shortest running time from the remaining devices; if yes, proceed to step P4.

[0019] In steps P4 and P1, when the brine temperature exceeds the set value, it is determined that the cooling capacity needs to be increased, and the device with the shortest running time is started, and the cumulative running time is updated and stored in the local database; in step P1, when the brine temperature is lower than the set value, it is determined that the cooling capacity needs to be reduced, and the device with the longest running time is turned off.

[0020] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, uses a threshold comparison strategy for multi-dimensional fault prediction in its PLC controller. Every 10 seconds, it performs a centralized analysis of the data from each sensor and compares it with a pre-set threshold. When the warning conditions are met, it executes a graded response and sends a warning message to the cloud monitoring layer through the edge gateway. At the same time, it displays a real-time fault alarm on the local touch screen so that maintenance personnel can check it in a timely manner.

[0021] The PLC controller is equipped with early warning conditions for three types of faults: compressor failure, brine pump failure, and refrigerant leakage.

[0022] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes compressor faults such as liquid slugging risk, overpressure risk, and overload risk.

[0023] When the refrigerant level in the evaporator skid exceeds the preset liquid slugging warning threshold, it is determined that the liquid refrigerant has not been completely evaporated, posing a risk of liquid slugging, and triggering a liquid slugging warning.

[0024] The compressor compares the discharge pressure in the discharge pipe with three preset values: the limit loading pressure, the forced unloading pressure, and the shutdown threshold. When the discharge pressure reaches the limit loading pressure, the compressor stops loading to prevent the pressure from rising further. When the discharge pressure reaches the forced unloading pressure, the compressor automatically reduces the load. When the discharge pressure reaches the shutdown threshold, the compressor immediately stops running to avoid the risk of explosion.

[0025] When the compressor motor current exceeds the preset overload threshold, it is determined that the motor load is too high and there is an overload risk, triggering an overload warning.

[0026] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes brine pump faults such as circulation interruption and overload risk.

[0027] When the flow switch of the main pipeline of the brine system does not detect a flow signal, but the brine pump is running, it is determined that the brine pump has stopped running or the pipeline is blocked, resulting in the interruption of circulation, and thus the brine pump is determined to be faulty, triggering an early warning.

[0028] When the current of the brine pump motor exceeds the preset overload threshold, it is determined that there is a phenomenon of pump body jamming or abnormal voltage, resulting in excessive motor load and overload risk, triggering an overload warning.

[0029] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes refrigerant leakage, including abnormal liquid level and pressure-assisted leakage.

[0030] When the refrigerant level in the receiver is lower than the preset leak warning threshold or the refrigerant level in the siphon tank is lower than the lower limit of the normal range, it is determined that the total amount of refrigerant has decreased and there is a risk of leakage, triggering an abnormal level warning.

[0031] When the pressure in the compressor suction line is lower than the preset lower limit of the normal range, combined with abnormal liquid levels in the receiver or siphon tank, the judgment of refrigerant leakage is further strengthened.

[0032] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes a tiered response system comprising a first-level early warning, a second-level adjustment, and a third-level shutdown. When parameters approach a pre-set threshold, a first-level early warning is triggered, issuing an audible and visual alarm to remind maintenance personnel to check the equipment. When parameters are abnormal but have not yet endangered equipment safety or system operation, the local control layer automatically adjusts the equipment to ensure the overall stable operation of the system. When parameters reach a pre-set shutdown threshold or a cascading fault occurs that endangers equipment safety, the local control layer immediately controls the relevant equipment to stop operation and cuts off the source of danger to prevent equipment damage.

[0033] The aforementioned freezing station equipment group control system, which combines balanced operation and fault prediction, includes an internet cloud monitoring platform in its cloud monitoring layer. This platform enables remote monitoring of the equipment at the freezing station site and performs data storage and energy consumption analysis on the data collected by the data acquisition layer and the analysis results of the local control layer. It then generates analysis reports and early warning push information, which is then pushed to mobile phones or computers.

[0034] The technical solution of the present invention achieves the following beneficial technical effects:

[0035] The freezing station equipment group control system of this application works collaboratively through a three-layer architecture. The data acquisition layer comprehensively and accurately collects core operating parameters, providing reliable support for management and control. The local control layer realizes balanced equipment runtime and multi-dimensional fault prediction, extending equipment life, avoiding unplanned downtime, and ensuring continuous operation. The cloud monitoring layer realizes remote monitoring, energy consumption analysis, and early warning push, reducing operation and maintenance costs, adapting to centralized management and control, and meeting the needs of green and low-carbon development. Overall, this application realizes intelligent and energy-saving management and control of freezing station equipment, solving the technical problems of traditional management and control being extensive and lacking in intelligence. Attached Figure Description

[0036] Figure 1. Schematic diagram of the architecture and data flow of the freezing station equipment group control system of the present invention;

[0037] Figure 2. Flowchart of runtime balance control of the freezing station equipment group control system of the present invention;

[0038] Figure 3 is a schematic diagram of the cloud-based equipment monitoring interface of the freezing station equipment group control system of the present invention; Detailed Implementation

[0039] This embodiment discloses a group control system for freezing station equipment that combines operational balancing and fault prediction. As shown in Figure 1, it adopts a three-layer "cloud-edge-device" architecture, specifically including a data acquisition layer (device layer) for collecting operating parameters of the freezing station's field equipment, a local control layer (edge ​​layer) for implementing local closed-loop control and performing operational balancing and fault prediction, and a cloud-based monitoring layer (cloud layer) for remote monitoring, data storage and analysis, and early warning push. After collecting the operating parameters of the freezing station's field equipment, the data acquisition layer transmits the operating parameters to the local control layer, providing data support for control decisions. After receiving the operating parameters transmitted by the data acquisition layer, the local control layer continuously compares the operating parameters with pre-set safety thresholds, analyzes the comparison results according to pre-set operating logic, and then executes a graded response based on the analysis results, thereby achieving runtime balancing control and multi-dimensional fault prediction. Details are as follows:

[0040] 1. End layer: Data acquisition layer

[0041] It includes temperature sensors, pressure transmitters, current transformers, flow switches, level sensors, and electricity meters, with specific parameters shown in Table 1.

[0042] Table 1

[0043]

[0044] Specifically, the data acquisition layer includes a first temperature sensor for detecting the compressor exhaust temperature, a second temperature sensor for detecting the brine temperature, a first pressure transmitter for detecting the condensation pressure, a second pressure sensor for detecting the evaporation pressure, a first current transformer for detecting the compressor motor current, a second current transformer for detecting the brine pump current, a first level sensor for detecting the liquid level in the storage tank, a second level sensor for detecting the liquid level in the siphon tank, a third level sensor for detecting the liquid level in the evaporation skid, an energy meter for detecting the power consumption of each unit, and a flow switch for real-time monitoring of the brine system circulation status.

[0045] The first temperature sensor is located at the compressor exhaust port, the second temperature sensor is located inside the pipe of the evaporator skid, the first pressure transmitter is located at the condenser inlet, and the second pressure sensor is located at the evaporator outlet; the first current transformer is located inside the compressor motor distribution cabinet, and the second current transformer is located inside the brine pump motor distribution cabinet; the first liquid level sensor is located at the top of the liquid storage tank, the second liquid level sensor is located at the top of the siphon tank, and the third liquid level sensor is located at the top of the evaporator skid; there are three electricity meters, which are respectively installed in the distribution cabinets of the compressor, the evaporator, the condenser, and the brine pump; the flow switch is installed on the main pipeline of the brine system.

[0046] The group control system of this application deploys various types of sensors on key equipment to collect core physical quantities reflecting equipment status and system balance in real time (sampling frequency 1Hz). These are transmitted to the PLC controller via 4-20mA analog signals or Modbus protocol, providing a data basis for subsequent control decisions and fault prediction.

[0047] (1) Pressure and liquid level monitoring: Install liquid level sensors and pressure sensors with remote transmission function in the storage tank, siphon tank, evaporation skid, etc., so as to continuously monitor the liquid level and pressure changes.

[0048] (2) Temperature monitoring: Temperature sensors are installed at the inlet pipe of the siphon tank, the brine inlet and outlet of the evaporator skid, and the end of the brine main pipe in the loop, etc., to calculate the subcooling and monitor the heat exchange efficiency;

[0049] (3) Electrical condition monitoring: Collect equipment current through current transformers and electricity meters to determine whether there is an overload.

[0050] (4) Fluid status monitoring: Install a flow switch on the main pipeline of the brine system to monitor the circulation status in real time.

[0051] 2. Side layer: Local control layer

[0052] The local control layer includes a PLC controller for implementing runtime balanced control and multi-dimensional fault prediction, an edge gateway for transmitting data, analysis results, and fault information to the cloud monitoring layer, and a local database for storing device runtime, fault records, and control parameters. Specifically:

[0053] (1) PLC controller: Siemens S7-1500 series (or equivalent PLC controller) is adopted, which has high-speed processing capability (1ms instruction cycle) and supports complex logic operation and multi-task concurrent processing;

[0054] (2) Edge gateway: The Advantech UNO-2271A industrial gateway is used, which has a built-in Linux system and supports Modbus to MQTT protocol, enabling local data storage and cloud transmission;

[0055] (3) Local database: SQLite database is used to store information such as device runtime, fault records, and control parameters.

[0056] The PLC controller continuously compares and analyzes the real-time data acquired by the data acquisition layer with the pre-set safety thresholds and operating logic:

[0057] For each monitored parameter (such as liquid level, pressure, current, and water flow), normal ranges, alarm thresholds, and shutdown thresholds are set. Furthermore, the PLC controller not only performs single-parameter judgments but also complex logic operations. For example, it compares the exhaust pressure with "limited loading pressure" and "forced unloading pressure" to determine the compressor's loading / unloading / shutdown; it correlates the brine system's water flow status with the compressor's operating signals to determine if the cycle is normal. Based on the judgment results, the system executes a tiered response from early warning to emergency shutdown, achieving fault prediction and interception.

[0058] The PLC controller employs a load balancing strategy of "shortest running time priority start and longest running time priority shutdown" when performing runtime balancing control. The control logic is shown in Figure 2, and is as follows:

[0059] (1) Demand triggering: When the system detects that the brine temperature exceeds the set value (e.g., -28℃), the system determines that the cooling capacity needs to be increased, triggering the equipment start-up demand;

[0060] (2) Equipment screening: The PLC reads the cumulative running time of similar equipment (such as compressors) from the local database and filters out the equipment with the shortest running time;

[0061] (3) Start-up verification: Check whether the "current, pressure and temperature" of the equipment are normal (e.g., motor current ≤ 110% of the rated value). If they are normal, start the equipment.

[0062] (4) Duration update: After the equipment starts running, the PLC controller updates its cumulative running time every minute and stores it in the local database;

[0063] (5) Load reduction logic: When load reduction is required (e.g., when the brine temperature is below -32℃), the equipment with the longest running time will be shut down first to ensure that the running time deviation of similar equipment is ≤5%.

[0064] The PLC controller employs a threshold comparison strategy when performing multi-dimensional fault prediction, setting early warning conditions for three types of key faults (compressor fault, brine pump fault, and refrigerant leakage), as follows:

[0065] (1) Predicting compressor failure

[0066] Liquid slugging risk: When the refrigerant level in the evaporator skid exceeds the preset "liquid slugging warning threshold", it indicates that the liquid refrigerant has not been completely evaporated and may enter the compressor cylinder, causing liquid slugging damage. The system will trigger a warning.

[0067] Overpressure risk: The pressure in the compressor's exhaust pipe is compared with three preset values: "limited loading pressure", "forced unloading pressure", and "shutdown threshold". When the exhaust pressure reaches the "limited loading pressure", the system stops loading the compressor to prevent the pressure from rising further. When the exhaust pressure reaches the "forced unloading pressure", the compressor automatically reduces its load. When the exhaust pressure reaches the "shutdown threshold", the system immediately stops the compressor to avoid the risk of explosion.

[0068] Overload risk: When the compressor motor current exceeds the preset "overload threshold", it indicates that the motor load is too large and may burn out the windings, posing an overload risk. The system will issue an overload warning.

[0069] (2) Prediction of brine pump failure

[0070] Interruption of circulation: If the flow switch of the main pipeline of the brine system does not detect a flow signal, but the brine pump is running, it means that the brine pump may have stopped or the pipeline is blocked, causing the brine to be unable to circulate. The system will judge it as a brine pump failure.

[0071] Overload risk: When the brine pump motor current exceeds the preset "overload threshold", it indicates that the pump body may be stuck or the voltage is abnormal, resulting in excessive motor load and overload risk. The system will issue an overload warning.

[0072] (3) Prediction of refrigerant leakage

[0073] Abnormal liquid level: When the refrigerant level in the receiver is lower than the preset "leakage warning threshold" or the refrigerant level in the siphon tank is lower than the "lower limit of normal range", it indicates that the total amount of refrigerant in the system has decreased, and there may be a leak.

[0074] Pressure assistance: If the pressure in the compressor suction line is lower than the preset "lower limit of normal range", combined with the abnormal liquid level in the receiver or siphon tank, it will further strengthen the judgment of refrigerant leakage.

[0075] The PLC controller performs a centralized analysis of sensor data every 10 seconds, comparing it with pre-set thresholds. If the warning conditions are met, the system executes a tiered response and sends the warning information to the cloud via the edge gateway. Simultaneously, a real-time fault alarm is displayed on the local touchscreen for easy access by maintenance personnel.

[0076] The tiered response includes Level 1 early warning, Level 2 adjustment, and Level 3 shutdown, as detailed below:

[0077] (1) Level 1 warning: When the parameter approaches the preset threshold, a Level 1 warning is triggered, and an audible and visual alarm is issued to remind the operation and maintenance personnel to check the equipment as soon as possible;

[0078] (2) Secondary adjustment: When the parameters are abnormal but the equipment safety is not in danger, the system will automatically adjust, such as reducing the load of the compressor and starting the backup brine pump to restore circulation, so as not to affect the normal operation of the system.

[0079] (3) Level 3 shutdown: When the parameters reach the preset shutdown threshold or a chain failure that seriously threatens the safety of the equipment occurs (such as compressor liquid slugging, or interruption of brine pump circulation causing evaporation skid to freeze), the local control layer immediately controls the relevant equipment to stop running and cuts off the source of danger to prevent equipment damage.

[0080] 3. Cloud layer: Cloud-based regulatory layer

[0081] The cloud-based monitoring layer includes an internet-based cloud monitoring platform, used to remotely monitor the equipment at the freezing station, and to store and analyze the data collected by the data acquisition layer and the analysis results of the local control layer, thereby generating analysis reports and early warning push information, which is then pushed to mobile devices or computers. Specifically:

[0082] (1) Remote monitoring: View the real-time status of the equipment via Web or mobile terminal. Supports dynamic display of virtual configuration diagram, as shown in Figure 3. The equipment operating status, such as compressor start / stop status, brine temperature, equipment parameters, etc., can be displayed in real time.

[0083] (2) Data storage: Stores more than one year of historical system operation data (including sensor data, fault records, and energy consumption reports), and supports querying by time, device type, and parameter dimension;

[0084] (3) Analysis tools: Built-in energy consumption analysis module (calculates power consumption per unit cooling capacity), automatically generates daily / weekly / monthly energy consumption reports and equipment start-up and shutdown records, and supports exporting to Excel;

[0085] (4) Early warning push: Push fault early warning information to designated maintenance personnel via mobile phone or computer to ensure response within 30 minutes.

[0086] The edge gateway uploads data to the cloud via a wired network. The cloud platform cleans and analyzes the data, and then generates reports such as energy consumption reports and equipment fault records, which are sent to maintenance personnel.

[0087] The equipment in a coal mine freezing station typically includes compressors, evaporation skids, and brine pumps. The compressors include eight dual-stage screw compressors (ammonia refrigeration system), the evaporation skids are equipped with six sets and operate in parallel, and the brine pumps are used in one standby configuration and controlled by frequency converters. The PLC controller of the freezing station equipment group control system in this application is a Siemens S7-1500 CPU1516-3 PN / DP, the edge gateway is an Advantech UNO-2271A equipped with a 4G communication module, and the cloud monitoring platform is connected to the "Easy Cooling Cloud" IoT platform.

[0088] In practice, firstly, various sensors are installed at key nodes of the freezing station equipment and signal wiring is completed; then, the PLC control program is configured, embedding runtime balancing and fault prediction logic algorithms; next, the local SQLite database is set up, and the equipment ledger and operating parameters are initialized; then, the edge gateway is debugged, and the Modbus→MQTT protocol channel is established; then, the cloud platform is logged in, the device ID is bound, and alarm contacts are configured; the system is tested for 72 hours to verify the control logic and early warning accuracy before being officially put into operation and entering fully automatic intelligent management mode.

[0089] The freezing station equipment group control system of this application achieves intelligent management and control of freezing station equipment through the coordinated linkage of a three-layer architecture of data acquisition layer, local control layer and cloud monitoring layer. It not only solves the pain points of traditional manual operation and weak intelligent control, but also takes into account the reliability, intelligence and energy saving of equipment operation control, and can fully adapt to the long-term continuous operation needs of modern mine freezing stations.

[0090] The above embodiments are merely illustrative examples for clear explanation and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations here. However, obvious variations or modifications derived therefrom are still within the scope of protection of the claims of this patent application.

Claims

1. A group control system for freezing station equipment that combines balanced operation and fault prediction, characterized in that: The system includes a data acquisition layer for collecting operating parameters of the freezing station's field equipment, a local control layer for implementing local closed-loop control and performing operational balancing and fault prediction, and a cloud-based monitoring layer for remote monitoring, data storage and analysis, and early warning push notifications. After collecting the operating parameters of the freezing station's field equipment, the data acquisition layer transmits these parameters to the local control layer, providing data support for control decisions. Upon receiving the operating parameters from the data acquisition layer, the local control layer continuously compares them with pre-set safety thresholds, analyzes the comparison results according to pre-set operational logic, and then executes tiered responses based on the analysis results, thereby achieving operational duration balancing control and multi-dimensional fault prediction.

2. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 1, characterized in that, The data acquisition layer includes a first temperature sensor for detecting the compressor exhaust temperature, a second temperature sensor for detecting the brine temperature, a first pressure transmitter for detecting the condensing pressure, a second pressure sensor for detecting the evaporating pressure, a first current transformer for detecting the compressor motor current, a second current transformer for detecting the brine pump current, a first level sensor for detecting the liquid level in the receiver, a second level sensor for detecting the liquid level in the siphon tank, a third level sensor for detecting the liquid level in the evaporation skid, an energy meter for detecting the power consumption of each unit, and a flow switch for real-time monitoring of the brine system circulation status. The first temperature sensor is located at the compressor exhaust port, the second temperature sensor is located inside the pipes of the evaporation skid, and the first pressure transmitter is located at... At the condenser inlet, the second pressure sensor is located at the evaporator outlet; the first current transformer is located in the compressor motor distribution cabinet, and the second current transformer is located in the brine pump motor distribution cabinet; the first liquid level sensor is located at the top of the storage tank, the second liquid level sensor is located at the top of the siphon tank, and the third liquid level sensor is located at the top of the evaporation skid; there are three energy meters, which are respectively installed in the distribution cabinets of the compressor, the evaporator, the condenser, and the brine pump; the flow switch is installed on the main pipeline of the brine system; each sensor and energy meter collects the core physical quantities of the reaction equipment status and system balance in real time, and transmits the collected core physical quantity data to the local control layer through a 4-20mA analog signal or Modbus protocol.

3. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 1, characterized in that, The local control layer includes a PLC controller for implementing runtime balanced control and multi-dimensional fault prediction, an edge gateway for transmitting data information, analysis results and fault information to the cloud monitoring layer, and a local database for storing device runtime, fault records and control parameters.

4. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 3, characterized in that, The specific process of the PLC controller performing runtime balancing control includes the following steps: Step P1: Read the brine temperature and determine whether the brine temperature exceeds or falls below the set value; if not, continue reading and determining; if yes, proceed to step P2; Step P2: Read the running time of similar devices in the local database and filter the devices with the shortest and longest running times; Step P3: Check whether the parameters of the device with the shortest running time selected in step P2 are normal; if not, remove the device with the shortest running time and repeat step P2 to filter the device with the shortest running time from the remaining devices; if yes, proceed to step P4; Step P4: In step P1, when it is determined that the brine temperature exceeds the set value, it is determined that the cooling capacity needs to be increased, and the device with the shortest running time is started, and the accumulated running time is updated and stored in the local database; In step P1, when it is determined that the brine temperature is below the set value, it is determined that the cooling capacity needs to be reduced, and the device with the longest running time is turned off.

5. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 3, characterized in that, The PLC controller uses a threshold comparison strategy for multi-dimensional fault prediction. It performs a centralized analysis of the data from each sensor every 10 seconds and compares it with a pre-set threshold. When the warning conditions are met, it executes a graded response and sends a warning message to the cloud monitoring layer through the edge gateway. At the same time, it displays a real-time fault alarm on the local touch screen so that maintenance personnel can check it in a timely manner. The PLC controller is equipped with early warning conditions for three types of faults: compressor failure, brine pump failure, and refrigerant leakage.

6. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 5, characterized in that, The compressor malfunctions include liquid slugging risk, overpressure risk, and overload risk. When the refrigerant level in the evaporator skid exceeds a preset liquid slugging warning threshold, it is determined that the liquid refrigerant has not completely evaporated, posing a liquid slugging risk and triggering a liquid slugging warning. The discharge pressure in the compressor discharge pipe is compared with three preset values: the limit loading pressure, the forced unloading pressure, and the shutdown threshold. When the discharge pressure reaches the limit loading pressure, the compressor stops loading to prevent the pressure from continuing to rise. When the discharge pressure reaches the forced unloading pressure, the compressor automatically reduces its load to lower the load. When the discharge pressure reaches the shutdown threshold, the compressor immediately stops operating to avoid the risk of explosion. When the compressor motor current exceeds a preset overload threshold, it is determined that the motor load is too high, posing an overload risk and triggering an overload warning.

7. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 5, characterized in that, The brine pump malfunctions include circulation interruption and overload risk. When the flow switch of the main brine system pipeline does not detect a flow signal, but the brine pump is in operation, it is determined that the brine pump has stopped running or the pipeline is blocked, resulting in circulation interruption, which in turn determines that the brine pump is malfunctioning and triggers an early warning. When the current of the brine pump motor exceeds the preset overload threshold, it is determined that there is a phenomenon of pump body jamming or abnormal voltage, resulting in excessive motor load and overload risk, triggering an overload warning.

8. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 5, characterized in that, The refrigerant leakage includes abnormal liquid level and pressure-assisted leakage. When the refrigerant level in the receiver is lower than the preset leakage warning threshold or the refrigerant level in the siphon tank is lower than the lower limit of the normal range, it is determined that the total amount of refrigerant has decreased and there is a risk of leakage, triggering an abnormal liquid level warning. When the pressure in the compressor suction pipe is lower than the preset lower limit of the normal range, the judgment of refrigerant leakage is further strengthened in combination with the abnormal liquid level in the receiver or siphon tank.

9. The freezing station equipment group control system with both operational balancing and fault prediction as described in claim 5, characterized in that, The tiered response includes a level 1 warning, a level 2 adjustment, and a level 3 shutdown. When a parameter approaches a preset threshold, a level 1 warning is triggered, issuing an audible and visual alarm to remind maintenance personnel to check the equipment. When parameters are abnormal but have not yet endangered equipment safety or system operation, the local control layer automatically adjusts the equipment to ensure the overall stable operation of the system. When parameters reach a preset shutdown threshold or a cascading failure endangering equipment safety occurs, the local control layer immediately controls the relevant equipment to stop operating and cuts off the source of danger to prevent equipment damage.

10. The freezing station equipment group control system with both operational balancing and fault prediction as described in any one of claims 1-9, characterized in that, The cloud-based monitoring layer includes an internet cloud-based monitoring platform, which is used to remotely monitor the equipment at the freezing station, store and analyze the data collected by the data acquisition layer and the analysis results of the local control layer, and then generate analysis reports and early warning push information, and push the early warning push information to mobile phones or computers.

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