An abnormal monitoring and optimization system for in-situ trace element and isotope analysis equipment

Abstract

The present invention discloses an abnormality monitoring optimization system for an in-situ trace element and isotope analysis device, comprising: an optimization monitoring module and a clamp-on AC Hall effect transformer, a pressure sensor, an electromagnetic gate valve, an electromagnetic flowmeter, and a two-way three-way valve respectively connected to the optimization monitoring module; the clamp-on AC Hall effect transformer is installed in the main power supply circuit from the distribution box to the inductively coupled plasma mass spectrometer, and the electromagnetic gate valve and electromagnetic flowmeter are embedded in the carrier gas delivery pipeline of the gas management component in a series integration manner; the optimization monitoring module performs in-depth analysis and processing on the collected current, gas pressure, and flow data to monitor abnormal conditions and optimize the performance of online equipment. Through a highly integrated design, real-time data processing capabilities, flexible control strategies, and an efficient fault diagnosis mechanism, it optimizes the energy efficiency management of online equipment, improves maintenance convenience, and achieves efficient and stable operation of online equipment.

Description

Technical Field

[0001] The present invention relates to the field of high-end analytical instruments, and more particularly to an abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device. Background Art

[0002] The laser ablation device, inductively coupled plasma mass spectrometer, and its supporting gas management components are used for high-sensitivity, high-precision analysis of trace elements and isotopes. Through non-contact laser microsampling to form aerosols, they are then ionized in a high-temperature plasma and separated and detected with high sensitivity by a mass spectrometer. Intelligent gas management ensures analytical stability and accuracy throughout the entire process, demonstrating strong analytical capabilities and application value in a variety of fields, including geology, environment, and biomedicine.

[0003] In current, traditional anomaly monitoring and optimization systems, monitoring of key parameters is often fragmented, with different components often equipped with independent monitoring equipment and lacking unified coordination. This results in slow system response and difficulty in implementing immediate adjustments when faced with anomalies, impacting experimental continuity and data accuracy. Furthermore, these systems only offer basic data logging capabilities, lacking the ability to deeply analyze and process large amounts of real-time data.

[0004] In terms of gas management and flow control, traditional mechanical valves or simple electronic control devices may not be able to provide high-precision flow regulation, especially in advanced analytical applications that require precise control of gas ratios and flows, which directly affects the repeatability and reliability of analytical results.

[0005] Furthermore, energy management was not fully considered, and the efficiency of the main power supply was not effectively monitored, resulting in energy waste. As energy consumption increased in laboratory equipment, when equipment malfunctioned, the lack of integrated troubleshooting tools often necessitated troubleshooting each component individually. This process was time-consuming and inefficient, increasing equipment downtime and maintenance costs.

[0006] Therefore, how to design an abnormality monitoring optimization system for in-situ trace element and isotope analysis equipment, improve the stability of the entire online equipment, and solve the problems of energy efficiency management and maintenance convenience is an urgent problem that technical personnel in this field need to solve. Summary of the Invention

[0007] In view of this, the present invention provides an abnormality monitoring and optimization system for in-situ trace element and isotope analysis equipment, which realizes efficient and stable operation of online equipment through highly integrated design, real-time data processing capabilities, flexible control strategies and efficient fault diagnosis mechanisms.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] An abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device is applied to an online device consisting of a laser ablation device, an inductively coupled plasma mass spectrometer, and a gas management component. The system includes an optimization and monitoring module, and a clamp-on AC Hall effect transformer, a pressure sensor, an electromagnetic gate valve, an electromagnetic flowmeter, and a two-way three-way valve respectively connected to the optimization and monitoring module.

[0010] The clamp-on AC Hall effect transformer is installed in the main power supply circuit from the distribution box to the inductively coupled plasma mass spectrometer, and is used to collect current information in the main power supply circuit;

[0011] The pressure sensor is connected to the plasma gas channel inside the gas management component and is used to collect gas pressure information in the plasma gas channel;

[0012] The electromagnetic gate valve and electromagnetic flowmeter are embedded in the carrier gas delivery pipeline of the gas management component in a serial integration manner to control the carrier gas flow and collect carrier gas flow information;

[0013] The two-way three-way valve is installed at the exhaust port of the ablation chamber of the laser ablation device to switch the direction of the airflow;

[0014] The optimization and supervision module performs in-depth analysis and processing on the collected current, gas pressure and flow data, and performs abnormal condition monitoring and performance optimization on the online equipment.

[0015] Among them, the optimization supervision module includes an early warning monitoring unit, which is used to calculate the difference between the current gas pressure value and the standard gas pressure value through the gas pressure information in the plasma gas channel, and compare the difference with the preset gas pressure difference threshold. When the difference is greater than the preset gas pressure difference threshold, the operation signal trigger terminal is used to control the laser ablation device to stop running.

[0016] Preferably, the optimization supervision module includes an abnormality monitoring unit, which is used to calculate the real-time power of the main power circuit through the current information in the main power circuit, and compare it with the preset main power circuit power threshold. When the real-time power of the main power circuit is less than the preset main power circuit power threshold, the operation signal trigger terminal is used to control the laser erosion device to stop running, and the two-way three-way valve is switched to the pressure relief side, and the electromagnetic gate valve is closed.

[0017] Preferably, the optimization supervision module includes a security risk level assessment unit for classifying security risk levels based on the threshold comparison results in the early warning monitoring unit and the abnormality monitoring unit.

[0018] Preferably, the optimization and supervision module includes a carrier gas delivery pipeline optimization unit, which is used to predict the carrier gas flow rate within a preset time period based on the carrier gas flow rate information, and to control the electromagnetic gate valve based on the prediction result to match the carrier gas flow rate demand.

[0019] Preferably, the optimization supervision module includes a current identification and division unit, which is used to identify the auxiliary electrical current in the main power circuit based on the current information in the main power circuit and extract the working current of the inductively coupled plasma mass spectrometer.

[0020] Preferably, the optimization supervision module includes an auxiliary electrical appliance operation optimization unit, which is used to perform time series load forecasting on the auxiliary electrical appliances based on historical power data of the auxiliary electrical appliances, and to optimize the operation of the auxiliary electrical appliances based on the time series load forecasting results.

[0021] Preferably, the optimization supervision module includes a main power circuit power threshold adjustment unit, which is used to analyze the changing trend of the main power circuit power, match it with the typical power curve corresponding to the task type of the inductively coupled plasma mass spectrometer, and adjust the main power circuit power threshold.

[0022] Preferably, the optimization monitoring module includes an adaptive gas pressure threshold adjustment unit for analyzing historical gas pressure information in the plasma gas channel and predicting and setting the gas pressure threshold under different circumstances.

[0023] Preferably, the optimization and supervision module includes a communication unit for remotely transmitting relevant information in the abnormal monitoring and optimization system to a central monitoring platform or other designated terminals for remote monitoring and fault diagnosis.

[0024] It can be seen from the above technical solution that compared with the prior art, the technical solution of the present invention has the following advantages:

[0025] Beneficial effects:

[0026] By integrating key components such as clamp-on AC Hall effect sensors, pressure sensors, solenoid gate valves, electromagnetic flowmeters, and two-way three-way valves into a unified monitoring system, comprehensive monitoring of equipment power supply, gas flow control, and exhaust paths is achieved. This integrated design improves system response speed and monitoring accuracy, reducing the risk of overall system failure due to a single point of failure.

[0027] 2. The optimized monitoring module not only receives data from various sensors and actuators, but also performs in-depth analysis and processing to promptly identify problems such as current anomalies, gas pressure fluctuations, or flow mismatches, thereby quickly responding and taking preventive measures to avoid potential equipment damage or deviations in experimental results, ensuring stable equipment operation and data accuracy.

[0028] 3. The tandem integration of a solenoid gate valve and electromagnetic flowmeter provides precise control of carrier gas flow, ensuring gas stability during ICP-MS analysis and improving the sensitivity and accuracy of the online instrument. Furthermore, the use of a two-way three-way valve increases system operational flexibility, enabling efficient switching of gas flow paths as needed to adapt to varying experimental conditions or respond to emergencies.

[0029] 4. The system integrates abnormal condition monitoring function, which can quickly locate the source of the fault. Whether it is an electrical problem or gas flow abnormality, it can be accurately diagnosed through the information fed back by the system, greatly shortening the troubleshooting time, simplifying the maintenance process and reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0031] Figure 1 A schematic diagram of the structure of an abnormality monitoring and optimization system provided by an embodiment of the present invention;

[0032] Figure 2 A schematic diagram of the structure of an optimization supervision module provided in an embodiment of the present invention;

[0033] Among them, 1- clamp-on AC Hall effect transformer, 2- pressure sensor, 3- electromagnetic gate valve, 4- electromagnetic flowmeter, 5- two-way three-way valve, 6- optimization supervision module, 7- inductively coupled plasma mass spectrometer, 8- laser ablation device, 9- gas management component, 10- operation signal trigger terminal, 11- ablation chamber exhaust port, 12- auxiliary electrical appliances, 9-1- plasma gas channel, 9-2- carrier gas delivery pipeline. DETAILED DESCRIPTION

[0034] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0035] like Figure 1 As shown, this embodiment provides an abnormality monitoring optimization system for an in-situ trace element and isotope analysis device, comprising: a clamp-on AC Hall effect transformer 1, a pressure sensor 2, an electromagnetic gate valve 3, an electromagnetic flowmeter 4, a two-way three-way valve 5, and an optimization monitoring module 6;

[0036] The clamp-on AC Hall effect transformer 1 is installed in the main power supply circuit from the distribution box to the inductively coupled plasma mass spectrometer 7, and is used to collect current information in the main power supply circuit;

[0037] The pressure sensor 2 is connected to the plasma gas channel 9-1 inside the gas management component 9 and is used to collect gas pressure information in the plasma gas channel 9-1;

[0038] The electromagnetic gate valve 3 and the electromagnetic flowmeter 4 are embedded in the carrier gas delivery pipe 9-2 of the gas management component 9 in a serial integration manner to control the carrier gas flow and collect carrier gas flow information;

[0039] The two-way three-way valve 5 is installed at the exhaust port 11 of the ablation chamber of the laser ablation device 8 to switch the direction of the air flow;

[0040] The optimization and supervision module 6 is connected to the operation signal trigger terminal 10 of the laser ablation device 8, the clamp-on AC Hall transformer 1, the pressure sensor 2, the electromagnetic gate valve 3, the electromagnetic flowmeter 4 and the two-way three-way valve 5, and is used to perform in-depth analysis and processing on the collected current, gas pressure and flow data, and to monitor the abnormal conditions of the online equipment and optimize its performance.

[0041] Through its highly integrated design, real-time data processing capabilities, flexible control strategies, and efficient fault diagnosis mechanisms, the system optimizes the energy efficiency management of online equipment, improves maintenance convenience, and ensures efficient and stable operation of online equipment.

[0042] like Figure 2 As shown, the optimization and supervision module includes: an early warning monitoring unit, an abnormality monitoring unit, a safety risk level assessment unit, a carrier gas pipeline optimization unit, a current identification and division unit, an auxiliary electrical operation optimization unit, a main power circuit power threshold adjustment unit, an adaptive gas pressure threshold adjustment unit and a communication unit;

[0043] The following is a further detailed description of each unit of the optimization supervision module and related technical features:

[0044] In this embodiment, the optimization supervision module includes an early warning monitoring unit, which is used to calculate the difference between the current gas pressure value and the standard gas pressure value through the gas pressure information in the plasma gas channel, and compare the difference with the preset gas pressure difference threshold. When the difference is greater than the preset gas pressure difference threshold, the operation signal trigger terminal is used to control the laser ablation device to stop running.

[0045] The optimization supervision module includes an abnormality monitoring unit, which is used to calculate the real-time power of the main power circuit through the current information in the main power circuit, and compare it with the preset main power circuit power threshold. When the real-time power of the main power circuit is less than the preset main power circuit power threshold, the operation signal trigger terminal is used to control the laser erosion device to stop running, switch the two-way three-way valve to the pressure relief side, and close the electromagnetic gate valve.

[0046] The optimized supervision module includes a security risk level assessment unit, which is used to classify security risk levels by comparing the thresholds in the early warning monitoring unit and the abnormality monitoring unit. When integrating the data from the early warning monitoring unit and the abnormality monitoring unit to perform security risk level assessment, risk matrix analysis is used to ensure the accuracy and practicality of the assessment results. The specific steps are as follows:

[0047] Determine risk scoring criteria: Detailed scoring criteria will be established for gas pressure overlimit and main power circuit power overload. These criteria include: Based on the degree of overpressure, the risk can be categorized as minor (+1 point), moderate (+2 points), and severe (+3 points), determined by the absolute value of the overpressure or the percentage relative to a preset threshold. Similarly, the risk is categorized as minor (+1 point), moderate (+2 points), and severe (+3 points), determined by the percentage or absolute value of the power overlimit exceeding the preset threshold, as well as the duration of the overload.

[0048] Create a risk matrix: A risk matrix is ​​a two-dimensional table with the horizontal axis representing likelihood (frequency or probability of occurrence) and the vertical axis representing impact (severity of consequences). Likelihood is categorized as low, medium, and high, and impact is also categorized as low, medium, and high. Each intersection represents a risk level, ranked from low to high.

[0049] Conversion to risk: Based on historical data and equipment characteristics, assign a score to the frequency of pressure overlimit and power overload (e.g., frequent occurrence = 3, occasional = 2, and extremely rare = 1). Also assign a score based on the potential impact of overpressure or overload on equipment, the environment, and operators (e.g., minor impact = 1, moderate impact = 2, and severe impact = 3).

[0050] Apply a weighted average method: assign different weights to the pressure and power overload scores (e.g., a weight of 0.6 for pressure overload and a weight of 0.4 for power overload), then add them together to create a total risk score. The specific calculation formula is: Total Risk Score = Pressure Overload Score × Weight 1 + Power Overload Score × Weight 2.

[0051] Mapping Scores to Risk Matrix: The total risk score is mapped to a pre-defined risk matrix to determine the corresponding risk level. For example, a low total score is classified as "Acceptable Risk" or "Requires Attention," while a high total score is classified as "High Risk" or "Unacceptable Risk."

[0052] In this embodiment, the optimization and supervision module includes a carrier gas delivery pipeline optimization unit, which is used to predict the carrier gas flow rate within a preset time period based on the carrier gas flow rate information, and control the electromagnetic gate valve based on the prediction result to match the carrier gas flow rate demand.

[0053] The system uses electromagnetic flowmeters to accumulate and verify historical carrier gas flow records, performing data cleansing to eliminate outliers and noise, ensuring data accuracy. Key indicators, including flow peaks, mean values, and rates of change, are extracted from this historical data to construct a feature dataset. An autoregressive integrated moving average (ARIMA) model is then trained on this feature dataset, and the trained model is used to predict future carrier gas flows. Based on the predicted results, the electromagnetic gate valve opening is dynamically adjusted to precisely match fluctuations in flow demand.

[0054] The optimization supervision module includes a current identification and division unit, which is used to identify the auxiliary electrical current in the main power circuit based on the current information in the main power circuit and extract the working current of the inductively coupled plasma mass spectrometer. Specifically, it includes:

[0055] Real-time data acquisition: Continuously and accurately read the main circuit's current data through the Hall circulator to ensure the real-time and accuracy of the data.

[0056] Abnormal point detection and recording: The improved k-score algorithm is used to analyze the current data and effectively identify abnormal points of current mutation.

[0057] Mutation point classification: Apply the incremental k-means clustering algorithm to dynamically classify the identified current mutation points and distinguish the current change patterns when different electrical appliances are turned on or off.

[0058] Feature matching and identification: Access a pre-built mutation feature library, compare the recorded current mutation features, and automatically match them to known electrical appliance categories.

[0059] The system combines current data with the voltage and operating status of identified appliances to calculate the real-time power of each appliance, ensuring accurate power calculations. Real-time power data for all appliances is written to a database for historical queries, trend analysis, and remote monitoring.

[0060] The system automatically pauses for 5 seconds and then restarts the cycle from step 1 to ensure continuous current monitoring and electrical appliance status identification.

[0061] The system continuously captures current data through a Hall effect circulator. Combined with an improved k-score algorithm to identify abnormal current behavior and an incremental k-means clustering algorithm to classify mutation points, the system efficiently distinguishes and matches the operating status of various electrical appliances. Leveraging a pre-built feature library, it enables automatic identification and classification, significantly improving monitoring accuracy and response speed. Furthermore, it integrates current and voltage information to accurately calculate real-time power, ensuring accurate power management. Real-time database recording also provides detailed data support for energy efficiency analysis, remote monitoring, and fault tracing.

[0062] In this embodiment, the optimization supervision module includes an auxiliary electrical appliance operation optimization unit, which is used to perform time series load forecasting on the auxiliary electrical appliances based on the historical power data of the auxiliary electrical appliances, and to optimize the operation of the auxiliary electrical appliances based on the time series load forecasting results.

[0063] In this embodiment, the auxiliary electrical appliances that the auxiliary electrical appliance operation optimization unit focuses on generally include those that support the normal operation of the laser ablation device, inductively coupled plasma mass spectrometer, and its gas management system, but are not directly involved in the core analysis process. These auxiliary electrical appliances include:

[0064] Cooling system: Maintains equipment temperature within a suitable range to prevent overheating that could affect performance or cause damage. Vacuum pump: Ensures the required vacuum level in the analysis chamber, which is crucial for mass spectrometer performance. Circulating water pump: Circulates coolant through the water cooling system, dissipating heat from key components. Gas compressor: Provides a stable gas source for the gas management system. Heater: Used in certain processes to preheat gas and ensure stable gas properties.

[0065] Specifically include:

[0066] Collect power consumption data for all auxiliary appliances from the system over a specific period of time. This includes each appliance's operating time, power consumption, and correlation with the operating status of the primary appliance. The data must be arranged in time series.

[0067] Use time series analysis methods to identify the power consumption pattern of each auxiliary electrical appliance, including daily, weekly, and monthly variation patterns, as well as special load characteristics during specific time periods (such as maintenance cycles and intensive experimental periods). Based on historical data, a load forecasting model is constructed to predict the power load for the next week or month. According to the predicted low-power consumption period, high-energy-consuming auxiliary electrical appliances (such as maintenance operations of large cooling systems and vacuum pumps) are scheduled to operate during this period to reduce power demand during peak hours. Before the peak power consumption is predicted, the status of the auxiliary electrical appliances is adjusted in advance through the intelligent scheduling system, such as shutting down non-essential equipment in advance or reducing the operating intensity of non-core functions.

[0068] It also includes: developing interactive mechanisms with key auxiliary electrical appliances so that they can dynamically adjust their own energy consumption according to the current grid load conditions, such as participating in load balancing by adjusting equipment operating efficiency, temporarily reducing non-core functions, etc.

[0069] The optimization and supervision module includes a main power circuit power threshold adjustment unit, which is used to analyze the change trend of the main power circuit power, match it with the typical power curve corresponding to the task type of the inductively coupled plasma mass spectrometer, and adjust the main power circuit power threshold. Specifically, it includes:

[0070] Based on the real-time power of the main circuit obtained in the above-mentioned abnormality monitoring unit, the real-time power change trend is dynamically monitored, the rise and fall rates of the power curve are analyzed, and it is compared with historical data. The current working state is matched with the typical power curve corresponding to the task type of the inductively coupled plasma mass spectrometer to evaluate whether it conforms to the expected power consumption pattern. In this process, a set of typical power consumption curve databases are established for different ICP-MS task types (conventional quantitative analysis, trace element detection, complex matrix sample analysis, etc.). These curves reflect the expected power change trend of the ICP-MS equipment over time when performing specific tasks, including the power characteristics of the startup phase, stable analysis phase, and end phase. Then, the power curve of the actual working state is generated.

[0071] Based on the assessment results, adjustments need to balance the requirements for safe and efficient equipment operation, ensuring that work interruptions due to misjudging high power demand as abnormal can be prevented, while also ensuring timely response and control of truly abnormal high power consumption.

[0072] Through the above steps, the control module can dynamically and accurately adjust the main circuit power threshold, ensuring that the inductively coupled plasma mass spectrometer equipment can operate efficiently under various working conditions while avoiding unnecessary downtime and potential equipment damage risks.

[0073] In this embodiment, the optimization and supervision module includes an adaptive gas pressure threshold adjustment unit, which is used to analyze the historical gas pressure information in the plasma gas channel and predict and set the gas pressure threshold under different circumstances. Specifically, it includes:

[0074] Data collation and analysis: Extract pressure data within a specified timeframe and calculate the mean, maximum, minimum, and standard deviation. Use the K-means algorithm to categorize operating conditions, ensuring data aggregation within similar conditions. Use the Z-score method to identify outliers.

[0075] Construction of threshold adjustment model: The model adopts a multilayer perceptron (MLP) network, uses the mean plus or minus two times the standard deviation to define the normal working range, uses the least squares method to fit the best straight line model, and recursively segments the data set to establish a rule set to predict the pressure threshold.

[0076] Threshold calculation: Based on the predicted output of the selected model and the new operating conditions input, the specific gas pressure threshold range is calculated.

[0077] By continuously monitoring the actual pressure value and comparing it with the adjusted threshold, the PID controller automatically adjusts the gas supply to ensure that the pressure is stable within the set range.

[0078] In this embodiment, the optimization and supervision module includes a communication unit for remotely transmitting relevant information in the abnormal monitoring and optimization system to a central monitoring platform or other designated terminals for remote monitoring and fault diagnosis.

[0079] The control module includes an IoT communication unit, which transmits all monitoring system data, warning information, operating status, and adjustment operation records to a central monitoring platform or other designated terminals via IoT technology. This unit supports remote monitoring, fault diagnosis, and system upgrades. Communication content is encrypted to ensure data transmission security and privacy protection. The unit is compatible with multiple communication protocols to accommodate diverse network environments and device access requirements.

[0080] The overall working process of the abnormal monitoring and optimization system in this implementation specifically includes:

[0081] During the data acquisition phase, a clamp-on AC Hall effect transformer monitors the current in the main power circuit in real time, acquiring current data. A pressure sensor is connected to the plasma gas channel to measure and record gas pressure. A solenoid gate valve and electromagnetic flowmeter are connected in series to the carrier gas pipeline to jointly control and record the carrier gas flow rate. A two-way three-way valve adjusts the airflow direction at the laser ablation device's exhaust port according to commands.

[0082] Real-time analysis and processing: The early warning monitoring unit in the optimization and supervision module compares real-time gas pressure data with preset thresholds to identify overpressure. The abnormality monitoring unit calculates real-time power based on current information and compares it with the preset power threshold to determine whether there is an overload. The current identification and classification unit separates the current of auxiliary electrical appliances from the current of main equipment; the carrier gas pipeline optimization unit adjusts the solenoid gate valve based on flow predictions; the auxiliary electrical operation optimization unit optimizes the use of auxiliary electrical appliances based on load predictions; the power and gas pressure threshold adjustment unit dynamically adjusts the thresholds based on historical data; and the safety risk level assessment unit conducts a risk assessment based on the comprehensive monitoring results.

[0083] Response and Control Phase: When the early warning or abnormality monitoring unit detects overpressure or overload, the operating signal triggers the terminal to immediately stop the laser ablation device and implement appropriate safety measures, such as switching the two-way three-way valve to the pressure relief side and closing the solenoid gate valve to protect the system. Based on carrier gas flow prediction and auxiliary electrical optimization results, the system configuration is automatically adjusted to achieve optimal operation.

[0084] Remote monitoring and fault diagnosis: The communication unit transmits all monitoring data, abnormal alarms, system status, and other information to the central monitoring platform or other designated terminals in real time. This enables remote monitoring, data analysis, fault warning, and diagnosis, improving system maintenance efficiency and response speed.

[0085] It forms a closed-loop monitoring and optimization process that can not only monitor key parameters in real time and promptly detect and handle abnormal situations, but also perform predictive maintenance and performance optimization based on data analysis to ensure the safe and efficient operation of online equipment.

[0086] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. References to the same or similar parts between the various embodiments are sufficient. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple. For relevant parts, refer to the method description.

[0087] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device, applied to an online device consisting of a laser ablation device, an inductively coupled plasma mass spectrometer, and a gas management component, characterized in that: include: An optimization and supervision module and a clamp-type AC Hall effect transformer, a pressure sensor, an electromagnetic gate valve, an electromagnetic flowmeter and a two-way three-way valve respectively connected to the optimization and supervision module; The clamp-on AC Hall effect transformer is installed in the main power supply circuit from the distribution box to the inductively coupled plasma mass spectrometer, and is used to collect current information in the main power supply circuit; The pressure sensor is connected to the plasma gas channel inside the gas management component and is used to collect gas pressure information in the plasma gas channel; The electromagnetic gate valve and electromagnetic flowmeter are embedded in the carrier gas delivery pipeline of the gas management component in a serial integration manner to control the carrier gas flow and collect carrier gas flow information; The two-way three-way valve is installed at the exhaust port of the ablation chamber of the laser ablation device to switch the direction of the airflow; The optimization and supervision module performs in-depth analysis and processing on the collected current, gas pressure and flow data to monitor abnormal conditions of the online equipment and optimize its performance; The optimization supervision module includes an early warning monitoring unit for calculating the difference between the current gas pressure value and the standard gas pressure value based on the gas pressure information in the plasma gas channel, and comparing the difference with a preset gas pressure difference threshold. When the difference is greater than the preset gas pressure difference threshold, the operation signal trigger terminal is used to control the laser ablation device to stop operating; The optimization supervision module includes an abnormality monitoring unit for calculating the real-time power of the main power circuit based on the current information in the main power circuit and comparing it with a preset main power circuit power threshold. When the real-time power of the main power circuit is less than the preset main power circuit power threshold, the operation signal trigger terminal is used to control the laser ablation device to stop running, switch the two-way three-way valve to the pressure relief side, and close the electromagnetic gate valve. The optimization and supervision module includes a carrier gas delivery pipeline optimization unit, which is used to predict the carrier gas flow rate within a preset time period based on the carrier gas flow rate information, and control the electromagnetic gate valve based on the prediction result to match the carrier gas flow rate demand.

2. The abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device according to claim 1, characterized in that: The optimization supervision module includes a security risk level assessment unit, which is used to classify the security risk level based on the threshold comparison results in the early warning monitoring unit and the abnormality monitoring unit.

3. The abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device according to claim 1, characterized in that: The optimization supervision module includes a current identification and division unit, which is used to identify the auxiliary electrical current in the main power circuit based on the current information in the main power circuit and extract the working current of the inductively coupled plasma mass spectrometer.

4. The abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device according to claim 1, characterized in that: The optimization supervision module includes an auxiliary electrical appliance operation optimization unit, which is used to perform time series load forecasting on the auxiliary electrical appliances based on historical power data of the auxiliary electrical appliances, and to optimize the operation of the auxiliary electrical appliances based on the time series load forecasting results.

5. The abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device according to claim 1, characterized in that: The optimization supervision module includes a main power circuit power threshold adjustment unit, which is used to analyze the change trend of the main power circuit power, match it with the typical power curve corresponding to the task type of the inductively coupled plasma mass spectrometer, and adjust the main power circuit power threshold.

6. The abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device according to claim 1, characterized in that: The optimization supervision module includes an adaptive gas pressure threshold adjustment unit, which is used to analyze historical gas pressure information in the plasma gas channel and predict and set the gas pressure threshold under different situations.

7. The abnormality monitoring and optimization system for an in-situ trace element and isotope analysis device according to claim 1, characterized in that: The optimization and supervision module includes a communication unit for remotely transmitting relevant information in the abnormal monitoring and optimization system to a central monitoring platform or other designated terminals for remote monitoring and fault diagnosis.

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