Mass spectrometer stability determination method and trace element analyzer performance testing method

Abstract

The present disclosure provides a mass spectrometer stability determination method and a trace element analyzer performance testing method. The determination method comprises: acquiring key performance parameters of a mass spectrometer to be evaluated; controlling said mass spectrometer to undergo a performance test so as to obtain test data; performing steady-state analysis on the basis of the test data to obtain a statistical steady state and a technical steady state of each key performance parameter, wherein the statistical steady state indicates whether the key performance parameters are in a controlled state within a preset time period, and the technical steady state indicates whether the key performance parameters are within a preset parameter range within the preset time period; and according to the statistical steady state and the technical steady state, determining whether each key performance parameter meets a stability requirement. According to the method, accurate and efficient evaluation of the stability of the key performance of mass spectrometers in use is achieved from two dimensions.

Description

Method for determining mass spectrometer stability and performance testing of trace element analyzers

[0001] This disclosure claims priority to Chinese patent application No. 2023107154480, filed with the Patent Office of China on June 15, 2023, entitled “Mass Spectrometer Stability Determination Method, Device, Storage Medium and Electronic Device,” and claims priority to Chinese patent application No. 2023107155036, filed with the Patent Office of China on June 15, 2023, entitled “Trace Element Analyzer Detection Limit Performance Test Method, Device and Electronic Device,” all of which are incorporated by reference into this disclosure. Technical Field

[0002] The present disclosure relates to the technical field of mass spectrometers, and in particular to a method for determining the stability of a mass spectrometer, a method for testing the detection limit performance of a trace element analyzer, a device, a storage medium, and an electronic device. Background Art

[0003] Mass spectrometry offers high sensitivity, specificity, and reproducibility, along with the advantages of high throughput, high efficiency, and low cost. With the continuous development and advancement of clinical mass spectrometry, its application is becoming increasingly widespread. The most commonly used mass spectrometry techniques include gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, time-of-flight mass spectrometry, and inductively coupled plasma-mass spectrometry.

[0004] Stability is the ability of an instrument to maintain consistent characteristics over time. It is a fundamental attribute that an instrument must possess and a key indicator for ensuring its effectiveness during use. Therefore, in addition to meeting conventional performance requirements, mass spectrometers should also meet key performance stability requirements specific to their intended use scenario.

[0005] However, an efficient and accurate solution for evaluating the key performance stability of mass spectrometers during use has not yet been established in the prior art.

[0006] In addition, in order to achieve an accurate evaluation of the key performance stability of the mass spectrometer during use, it is particularly important to obtain key performance. Among the key performance tests, the detection limit performance test of the trace element analyzer is particularly important. The current technology lacks a standardized trace element analyzer detection limit performance test process.

[0007] Summary of the Invention

[0008] The main purpose of the present disclosure is to provide a method for determining the stability of a mass spectrometer, a method, device, storage medium and electronic device for testing the detection limit performance of a trace element analyzer, so as to at least solve the problem that there is no efficient and accurate solution in the prior art to evaluate the stability of key performance of mass spectrometers during use.

[0009] In order to achieve the above-mentioned purpose, according to one aspect of the present disclosure, a method for determining the stability of a mass spectrometer is provided, comprising: obtaining key performance parameters of a mass spectrometer to be evaluated, wherein the key performance parameters include at least one of the following: parameters affecting the safety performance of the mass spectrometer to be evaluated, parameters affecting the mass spectrometer to be evaluated in achieving a first-level important function, and parameters affecting the mass spectrometer to be evaluated in achieving a second-level important function; controlling the mass spectrometer to be evaluated to perform a performance test to obtain test data; performing a steady-state analysis based on the test data to obtain a statistical steady-state and a technical steady-state of each of the key performance parameters, the statistical steady-state characterizing whether the key performance parameter is in a controlled state within a preset time, and the technical steady-state characterizing whether the key performance parameter is within a preset parameter range within the preset time; and determining whether each of the key performance parameters meets the stability requirements based on the statistical steady-state and the technical steady-state.

[0010] According to another aspect of the present disclosure, a method for testing the detection limit performance of a trace element analyzer is provided, comprising: performing ignition control on the trace element analyzer, and performing tuning control on the trace element analyzer after the trace element analyzer is successfully ignited; after the tuning control and the trace element analyzer meets the test standard, selecting parameters of the trace element analyzer to obtain target parameters, and editing the target parameters, wherein the target parameters are parameters required for performing a detection limit performance test on the trace element analyzer, and wherein the editing is to set relevant performance of the target parameters; performing sample-related performance testing on the selected and edited target parameters, analyzing the sample-related performance test results and obtaining analysis results of the detection limit performance test.

[0011] According to another aspect of the present disclosure, a mass spectrometer stability determination device is provided, comprising: a first acquisition unit, configured to acquire key performance parameters of the mass spectrometer to be evaluated, wherein the key performance parameters include at least one of the following: parameters affecting the safety performance of the mass spectrometer to be evaluated, parameters affecting the mass spectrometer to be evaluated in achieving a first importance level function, and parameters affecting the mass spectrometer to be evaluated in achieving a second importance level function; a control unit, configured to control the mass spectrometer to be evaluated to perform a performance test to obtain test data; an analysis unit, configured to perform a steady-state analysis based on the test data to obtain a statistical steady-state and a technical steady-state of each of the key performance parameters, the statistical steady-state characterizing whether the key performance parameter is in a controlled state within a preset time, and the technical steady-state characterizing whether the key performance parameter is within a preset parameter range within the preset time; a first determination unit, configured to determine whether each of the key performance parameters meets the stability requirements based on the statistical steady-state and the technical steady-state.

[0012] According to another aspect of the present disclosure, a detection limit performance testing device for a trace element analyzer is provided, comprising: a first control unit, configured to perform ignition control on the trace element analyzer, and to perform tuning control on the trace element analyzer after the trace element analyzer is successfully ignited; a first processing unit, configured to select parameters of the trace element analyzer to obtain target parameters, and to edit the target parameters after the tuning control and the trace element analyzer meets the test standards, wherein the target parameters are parameters required for performing a detection limit performance test on the trace element analyzer, and wherein the editing is to set relevant performance of the target parameters; a second processing unit, configured to perform sample-related performance detection on the selected and edited target parameters, and to analyze the sample-related performance detection results and obtain analysis results of the detection limit performance test.

[0013] According to another aspect of the present disclosure, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute any one of the mass spectrometer stability determination methods.

[0014] According to another aspect of the present disclosure, an electronic device is provided, comprising: one or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include a method for executing any one of the mass spectrometer stability determination methods.

[0015] The technical solution disclosed herein obtains the key performance parameters of a mass spectrometer to be evaluated, controls the mass spectrometer to be evaluated, conducts a performance test to obtain test data, and performs steady-state analysis based on the test data to obtain the statistical steady-state and technical steady-state of each key performance parameter. Based on the statistical and technical steady-state, it is determined whether each key performance parameter meets stability requirements. This solution determines whether each key performance parameter meets stability requirements based on the statistical and technical steady-state of the key performance parameters. This allows for accurate and efficient evaluation of the key performance stability of a mass spectrometer during use from two dimensions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which constitute part of the present disclosure, are intended to provide a further understanding of the present disclosure. The exemplary embodiments of the present disclosure and their descriptions are intended to explain the present disclosure and do not constitute an improper limitation of the present disclosure. In the accompanying drawings:

[0017] FIG1 shows a hardware structure block diagram of a mobile terminal for executing a method for determining mass spectrometer stability according to an embodiment of the present disclosure;

[0018] FIG2 shows a schematic flow chart of a method for determining mass spectrometer stability according to an embodiment of the present disclosure;

[0019] FIG3 shows a schematic flow chart of a specific method for determining mass spectrometer stability according to an embodiment of the present disclosure;

[0020] FIG4 shows a structural block diagram of a mass spectrometer stability determination device provided according to an embodiment of the present disclosure;

[0021] FIG5 shows a schematic flow chart of a method for testing the detection limit performance of a trace element analyzer according to an embodiment of the present disclosure;

[0022] FIG6 shows a schematic diagram of a first display interface provided according to an embodiment of the present disclosure;

[0023] FIG7 shows a schematic diagram of a second display interface provided according to an embodiment of the present disclosure;

[0024] FIG8( a ) shows a first partial schematic diagram of a third display interface provided according to an embodiment of the present disclosure;

[0025] FIG8( b ) shows a second partial schematic diagram of the third display interface provided according to an embodiment of the present disclosure;

[0026] FIG9 shows a schematic diagram of a fourth display interface provided according to an embodiment of the present disclosure;

[0027] FIG10 shows a schematic diagram of a fifth display interface provided according to an embodiment of the present disclosure;

[0028] FIG11 shows a schematic diagram of a sixth display interface provided according to an embodiment of the present disclosure;

[0029] FIG12 shows a schematic diagram of a seventh display interface provided according to an embodiment of the present disclosure;

[0030] FIG13( a ) shows a first partial schematic diagram of an eighth display interface provided according to an embodiment of the present disclosure;

[0031] FIG13( b ) shows a second partial schematic diagram of the eighth display interface provided according to an embodiment of the present disclosure;

[0032] FIG14 shows a schematic diagram of a ninth display interface provided according to an embodiment of the present disclosure;

[0033] FIG15 shows a schematic diagram of a tenth display interface provided according to an embodiment of the present disclosure;

[0034] FIG16 shows a schematic diagram of an eleventh display interface provided according to an embodiment of the present disclosure;

[0035] FIG17 shows a schematic diagram of a twelfth display interface provided according to an embodiment of the present disclosure;

[0036] FIG18 shows a schematic diagram of a thirteenth display interface provided according to an embodiment of the present disclosure;

[0037] FIG19 shows a schematic diagram of a fourteenth display interface provided according to an embodiment of the present disclosure;

[0038] FIG20( a ) shows a first partial schematic diagram of a fifteenth display interface provided according to an embodiment of the present disclosure;

[0039] FIG20( b ) shows a second partial schematic diagram of the fifteenth display interface provided according to an embodiment of the present disclosure;

[0040] FIG21 shows a schematic flow chart of a specific method for testing the detection limit performance of a trace element analyzer according to an embodiment of the present disclosure;

[0041] FIG22( a) shows a mean control chart in a mean-range control chart of detection limits of Li elements provided according to an embodiment of the present disclosure;

[0042] FIG22( b ) shows a mean control chart in a mean-range control chart of detection limits of element Y provided according to an embodiment of the present disclosure;

[0043] FIG22( c ) shows a mean control chart in a mean-range control chart of detection limits of Tl element provided according to an embodiment of the present disclosure;

[0044] FIG23( a) shows a histogram of the Li element detection limit data after conversion according to an embodiment of the present disclosure;

[0045] FIG23( b ) shows a histogram of the Y element detection limit data after conversion according to an embodiment of the present disclosure;

[0046] FIG23( c ) shows a histogram of the Tl element detection limit data after conversion according to an embodiment of the present disclosure;

[0047] FIG24 shows a structural block diagram of a detection limit performance testing device for a trace element analyzer provided according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0048] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0049] In order to enable those skilled in the art to better understand the solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the embodiments described are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present disclosure.

[0050] It should be noted that the terms "first," "second," and the like in the specification and claims of the present disclosure and the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate for the embodiments of the present disclosure described herein. In addition, the terms "including" and "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or inherent to these processes, methods, products, or apparatus.

[0051] For ease of description, some nouns or terms involved in the embodiments of the present disclosure are explained below:

[0052] Key performance stability capability index: refers to the degree to which key performance capabilities meet product quality standard requirements (specification range, etc.), and also refers to the actual performance capability of key performance under control within a certain period of time.

[0053] Statistical process control (SPC) applies mathematical statistics to analyze sample process data to determine whether process fluctuations are acceptable. When necessary, process parameters are adjusted to reduce deviations from target values ​​for product quality characteristics, maintaining the entire process in a stable, controlled state, influenced only by chance, and improving process efficiency. It emphasizes ensuring that processes operate under control and capability, ensuring that products and services consistently meet customer requirements. SPC often uses statistical techniques, such as control charts, to analyze processes or their outputs, allowing appropriate measures to achieve and maintain a state of statistical control, thereby improving process capability. Control charts, with control limits, are used to analyze and determine process stability. They distinguish between normal and abnormal fluctuations and are important statistical tools in on-site quality management. The PPK (Process Performance Index) value in SPC is used to calculate process performance, or an index of process performance, providing a quantitative assessment of process performance.

[0054] Statistical stability: The control charts of key performance indicator parameters must meet statistical stability requirements;

[0055] Technical steady state: The stability capability index value of the key performance indicator parameter must meet the given requirements and is equivalent to the process performance index PPK.

[0056] Trace element analyzers: Trace element analyzers are mostly instruments used to measure trace element levels in the human body. Formal and accurate test results are achieved using electrochemical analysis, atomic absorption spectrometry, and inductively coupled plasma mass spectrometry (ICP-MS). Most analyzers use electrochemical analyzers, which hold the largest market share. Electrochemical analyzers are mid- to high-end products, characterized by simple operation, accurate and reliable test results, and low consumables, making them popular among hospitals.

[0057] As introduced in the background technology, the prior art has not yet established an efficient and accurate solution to evaluate the stability of key performance of mass spectrometers during use. In order to solve the problem that there has not yet been an efficient and accurate solution to evaluate the stability of key performance of mass spectrometers during use, the embodiments of the present disclosure provide a mass spectrometer stability determination method, device, storage medium and electronic device.

[0058] The technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present disclosure.

[0059] The method embodiments provided in the embodiments of the present disclosure can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking operation on a mobile terminal as an example, FIG1 is a hardware structure block diagram of a mobile terminal of a mass spectrometer stability determination method according to an embodiment of the present disclosure. As shown in FIG1 , the mobile terminal may include one or more (only one is shown in FIG1 ) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the mobile terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It will be understood by those skilled in the art that the structure shown in FIG1 is only for illustration and does not limit the structure of the mobile terminal. For example, the mobile terminal may also include more or fewer components than those shown in FIG1 , or have a configuration different from that shown in FIG1 .

[0060] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the mass spectrometer stability determination method in the embodiment of the present disclosure. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, realizing the above-mentioned method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned networks include but are not limited to the Internet, corporate intranets, local area networks, mobile communication networks and combinations thereof. The transmission device 106 is used to receive or send data via a network. The above-mentioned network specific examples may include a wireless network provided by the communication provider of the mobile terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0061] In this embodiment, a method for determining the stability of a mass spectrometer running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0062] FIG2 is a flow chart of a method for determining mass spectrometer stability according to an embodiment of the present disclosure. As shown in FIG2 , the method includes the following steps:

[0063] Step S202: Acquire key performance parameters of the mass spectrometer to be evaluated, wherein the key performance parameters include at least one of the following: a parameter affecting the safety performance of the mass spectrometer to be evaluated, a parameter affecting the mass spectrometer to be evaluated in achieving a first-level function, and a parameter affecting the mass spectrometer to be evaluated in achieving a second-level function;

[0064] Specifically, the mass spectrometer to be evaluated in the present disclosure can be a clinical mass spectrometer. The vast majority of clinical device adverse event reports received in 2021 involved Class II and Class III clinical devices. There were 305,645 reports involving Class II clinical devices, accounting for 46.97% of the total reports; most clinical instrument failures can be attributed to unstable instrument performance. The clinical use environment of mass spectrometers is mostly long-term, large-volume, and high-matrix, which also places very high demands on the performance stability of the instrument. The mass spectrometer stability determination method disclosed in the present disclosure can accurately determine whether the key performance parameters of clinical mass spectrometers meet stability requirements.

[0065] Among them, the parameters to be evaluated for the safety performance of the mass spectrometer include: parameters that directly affect safety, lead to failure to meet laws and regulations, and have no warning, such as water / gas lines, which affect the operation of the entire machine. Failure of this indicator will cause the instrument to stop working, and there will be no warning for the failure, which directly affects safety;

[0066] Among the parameters to be evaluated for mass spectrometer safety performance, there are also those that directly impact safety, leading to non-compliance with laws and regulations, with warnings, such as temperature control, which affects the operation of the entire instrument. Failure of this indicator will cause the instrument to stop working, with warnings, but also poses a safety hazard.

[0067] Parameters that affect the mass spectrometer's ability to achieve the first level of criticality include: loss of basic functionality or degradation of key functions, inoperability or low performance, sensitivity / detection limit, and overall performance. Failure in these parameters can degrade overall measurement performance or even render detection impossible.

[0068] Among them, the parameters that affect the mass spectrometer to be evaluated in achieving the second-level important function include: parameters that cause the loss or degradation of secondary functions, interference removal performance, and impact on the test levels of some elements. Failure of this indicator will cause the measurement levels of some elements to deteriorate or become undetectable.

[0069] Specifically, the key performance parameters include at least one of the following: detection limit, ion transmission efficiency, and parameters affecting anti-interference capability. Of course, the key performance parameters may also include parameters other than detection limit, ion transmission efficiency, and parameters affecting anti-interference capability.

[0070] It should be noted that parameters that affect the customer experience, such as noise / light pollution, have no impact on the performance of the entire device, but do affect the customer experience and are not key performance parameters of the mass spectrometer to be evaluated.

[0071] Step S204: controlling the mass spectrometer to be evaluated to perform a performance test to obtain test data;

[0072] In other words, test data is obtained through performance testing. Specifically, taking ICP-MS as an example, blood and urine samples are commonly tested in clinical applications. Prolonged injection of these samples can clog the nebulizer and cause matrix precipitation at the orifice, thereby reducing instrument performance. To ensure more realistic testing, the ICP-MS was kept operating for extended periods during the test. Maintaining constant ambient conditions, the ICP-MS was optimized for performance, simulating actual operating conditions, and testing the detection limit and interference rejection. The test procedure is as follows: After igniting the instrument, perform autotune in standard mode, achieving optimal performance in standard mode. Inject 18 MΩ.cm high-purity water and measure the ion count rates at masses 7, 89, and 205. Inject high-purity water, the detection limit test solution, and measure the ion count rates at masses 7, 89, and 205. The detection limit is calculated by dividing the standard deviation of the measurement results by three times the sensitivity of the Li, Y, and Tl. Autotune in collision mode to optimize the CO / ArO ratio in collision mode. The instrument remains operational and is tested again after four and eight hours to assess collision reaction cell performance. Using ICP-MS as an example, this study demonstrates that its technology shares many similarities with other types of mass spectrometers. Clinical ICP-MS is suitable for analyzing major, minor, and trace elements in serum, blood, and urine. Determining stability requirements using ICP-MS as an example provides valuable insights for other mass spectrometers.

[0073] In other words, users of clinical ICP-MS primarily assess two key aspects of performance: detection capability and interference rejection. These two capabilities can be considered key performance characteristics of clinical ICP-MS. Detection capability is reflected in the detection limit (LOD), which is the analyte concentration corresponding to the minimum value that can be detected with an appropriate confidence level. The JJF1159-2006 standard stipulates that among the key technical specifications of ICP-MS, the detection limit calibration element must include three levels: low, medium, and high, covering the entire mass range of the mass axis, serving as a key basis for evaluating instrument performance. Interference rejection in ICP-MS is primarily achieved through the collision reaction cell. A collision reaction cell typically consists of a cell body with a built-in quadrupole or multipole. For example, a hexapole collision reaction cell typically incorporates helium gas, using collisions to remove interferences. Instrument parameters are adjusted to optimize the CO / ArO ratio, based on ArO ion interference (which affects Fe detection). A higher CO / ArO ratio indicates better interference rejection.

[0074] Step S206: Perform steady-state analysis based on the test data to obtain statistical steady-state and technical steady-state of each key performance parameter. The statistical steady-state indicates whether the key performance parameter is in a controlled state within a preset time, and the technical steady-state indicates whether the key performance parameter is within a preset parameter range within a preset time.

[0075] Step S208: Determine whether each key performance parameter meets the stability requirement based on the statistical steady state and the technical steady state.

[0076] The disclosed method for determining mass spectrometer stability obtains key performance parameters of the mass spectrometer to be evaluated, controls the mass spectrometer to be evaluated, conducts performance tests to obtain test data, and performs steady-state analysis based on the test data to obtain statistical steady-state and technical steady-state values ​​for each key performance parameter. Based on these statistical and technical steady-state values, it is determined whether each key performance parameter meets stability requirements. This solution determines whether each key performance parameter meets stability requirements based on the statistical and technical steady-state values ​​of the key performance parameters. This approach enables accurate and efficient evaluation of the key performance stability of mass spectrometers during use from two dimensions.

[0077] Furthermore, in step S206: performing steady-state analysis based on the test data to obtain the statistical steady-state of each key performance parameter includes:

[0078] Step S2061: Determine the mean-range control chart of each key performance parameter based on the test data; the mean-range control chart belongs to the field of statistical process control.

[0079] Step S2062: determining characteristic parameters based on the mean-range control chart, the characteristic parameters including at least one of the following: a mean data point, a positional relationship between the mean data point and the control limit, a positional relationship between the mean data point and the center line, and a fluctuation characteristic of the mean-range control chart;

[0080] Step S2063: Determine the statistical steady state of the key performance parameters according to the characteristic parameters.

[0081] In other words, the statistical steady state of key performance parameters can be accurately determined through the mean-range control chart. Specifically, in the mean-range control chart, the subgroup size and number of subgroups must be reasonably determined first. Then, the mean and range of each subgroup are calculated, as shown in Formulas 1 and 2. Then, the control limits of the range chart and the mean chart need to be calculated, as shown in Formulas 3, 4, 5, and 6.

[0082]

[0083] In formula 3, formula 4 and formula 5, D4, D3 and A2 are constants. They vary with the sample size and can be found by looking up the corresponding table. X1~Xn are the N values ​​of the key performance parameters. X 最大值 is the maximum value among the N values ​​of the key performance parameter, X 最小值is the minimum value among the N values ​​of the key performance parameter, represents the mean, Represents range, U represents upper limit, L represents lower limit, UCL(R) represents upper control limit of range chart, LCL(R) represents lower control limit of range chart; UCL(X) represents upper control limit of mean chart, LCL(X) represents lower control limit of mean chart.

[0084] After calculating the control limits for the mean and range control charts, a mean-range control chart can be drawn. Using the key performance statistical steady-state evaluation criteria, the positional relationship of the mean data points relative to the control limits and center line on the control chart, as well as their fluctuation characteristics, can be compared to determine whether the mass spectrometer's key performance indicators are in statistical steady-state.

[0085] Furthermore, in step S206: performing steady-state analysis based on the test data to obtain the technical steady-state of each key performance parameter includes:

[0086] Determine whether each key performance parameter set conforms to a normal distribution based on test data, where the key performance parameter set includes multiple key performance parameters of the same type;

[0087] When the key performance parameter set conforms to the normal distribution, the stability capability index of the corresponding key performance parameter is calculated based on the key performance parameter set. The stability capability index represents the technical steady state of the key performance parameter.

[0088] When the key performance parameter set does not conform to the normal distribution, the key performance parameter set is subjected to normality transformation to obtain the transformed key performance parameter set that conforms to the normal distribution, and the stability capability index SCI of the corresponding key performance parameter is calculated based on the transformed key performance parameter set that conforms to the normal distribution.

[0089] That is, based on multiple key performance parameters in the key performance parameter set, the stability capability index (SCI) of the key performance parameter is obtained, and the technical steady state of the key performance parameter is determined based on the stability capability index (SCI). Table 1 shows the stability capability index level of the key performance of the mass spectrometer.

[0090] Table 1 Mass spectrometer key performance stability capability index level table

[0091] Furthermore, the test data is used to determine whether each key performance parameter set conforms to a normal distribution, including:

[0092] The Kolmogorov-Smirnov test method (KS test) is used to perform a normal distribution conformity test on each key performance parameter set to determine whether each key performance parameter set conforms to the normal distribution.

[0093] Specifically, the KS test method is used to perform normal distribution N(μ, σ 2 )Conformity inspection.

[0094] The KS (Kolmogorov-Smirnov) test can be used to test the degree of conformity between the distribution of a set of sample data and a specified theoretical distribution;

[0095] Assume that the overall distribution is F(x), F0(x) is a known continuous distribution function, and the hypothesis test problem is: H0: F(x) = F0(x). The KS test steps are as follows:

[0096] 1) For a sample of size n, x(1), x(2), x(3), … x(n), the order statistics are: x(1)≤x(2)≤x(3)…≤x(n), and the empirical distribution function is:

[0097] Kolmogorov proposed that the statistic for testing hypothesis H0 is:

[0098] 2) Calculate each sample data x i The corresponding empirical distribution function Fn(x i ) and the known distribution function F0(t i ), and connect (Formula 7) and (Formula 8) in parallel to obtain:

[0099] δ i =max{|F0(x (i) )-(i-1) / n|,|F0(x (i) )-i / n|}, (i=1, 2,...n) (Formula 9)

[0100] Then in δ i The largest one is Dn, that is, Dn=max{δ i}.

[0101] 3) For a given significance level α and sample size n, find the critical value from the Kolmogorov test critical table

[0102] d(n, α). When D n≤d(n, α), accept hypothesis H0; otherwise reject hypothesis H0.

[0103] More specifically, the stability capability index (SCI) of the corresponding key performance parameters is calculated based on the key performance parameter set, including:

[0104] When the key performance parameter is a large parameter, the stability capability index (SCI) of the key performance parameter is determined based on the mean value of the key performance parameter, the lower limit value of the key performance parameter and the standard deviation of the key performance parameter;

[0105] When the key performance parameter is a minimum parameter, the stability capability index (SCI) of the key performance parameter is determined based on the mean value of the key performance parameter, the upper limit value of the key performance parameter and the standard deviation of the key performance parameter;

[0106] When the key performance parameter is a target parameter, the stability capability index SCI of the key performance parameter is determined based on the mean value of the key performance parameter, the lower limit value of the key performance parameter, the upper limit value of the key performance parameter and the standard deviation of the key performance parameter.

[0107] Specifically, ① For the Wangda feature, the larger the better:

[0108] ②For the small size characteristic, the smaller the better:

[0109] ③ For the eye-catching characteristic, there is a target value m. It is hoped that the quality characteristic x fluctuates around the target value m, and the smaller the fluctuation, the better. Then x is called the eye-catching characteristic. The calculation formula is as follows:

[0110] In formula 10, formula 11 and formula 12, s is the sample standard deviation of the sampling population. The larger the performance index value, the better. Therefore, the lower limit of this performance parameter is defined as K. L The smaller the performance index value, the better. Therefore, the upper limit of this performance parameter is defined as K. u ; The performance index should not be too large or too small, so the range of this performance parameter is defined as (K L , K u ).

[0111] Furthermore, the normality conversion process is performed on the key performance parameter set that does not conform to the normal distribution, including at least one of the following:

[0112] The logarithmic transformation method is used to transform the key performance parameter set that does not conform to the normal distribution into a normal state. The logarithmic transformation is as follows: the key performance indicator X is taken as the logarithm (common logarithm or natural logarithm);

[0113] The square root transformation method is used to transform the key performance parameter set that does not conform to the normal distribution into a normal state. The square root transformation is as follows: taking the square root of the key performance indicator X;

[0114] The square root arcsine transformation method is used to transform the key performance parameter set that does not conform to the normal distribution into a normal state. The square root arcsine transformation is specifically as follows: taking the arcsine of the square root of the key performance indicator X;

[0115] The square transformation method is used to transform the key performance parameter set that does not conform to the normal distribution into a normal state. The square transformation is as follows: square the key performance indicator X;

[0116] The reciprocal transformation method is used to transform the key performance parameter set that does not conform to the normal distribution into a normal state; reciprocal transformation: the key performance indicator X is taken as the reciprocal;

[0117] The Box-Cox transformation method is used to transform the key performance parameter set that does not conform to the normal distribution to normality. The Box-Cox transformation method refers to a generalized power transformation method, a data transformation commonly used in statistical modeling, used when the dependent variable of continuous measurement data does not conform to the normal distribution. The Box-Cox transformation transforms the dependent variable X, and the transformation method of X is determined by the variable parameter λ. The transformation form is:

[0118] The Box-Cox transformation can significantly improve the normality, symmetry and homogeneity of variance of the data and is applicable to many data.

[0119] The normal scoring method is used to perform normal transformation on the key performance parameter set that does not conform to the normal distribution. The normal scoring method is: directly sorting the data, and then reassigning the data at each position in combination with the standard normal distribution to achieve normal transformation.

[0120] Furthermore, the method further comprises:

[0121] In the case where the key performance parameter is a parameter that affects the mass spectrometer to be evaluated in achieving the second importance level function, the importance level of the key performance parameter is determined to be the fourth importance level;

[0122] In the case where the key performance parameter is a parameter that affects the mass spectrometer to be evaluated in achieving the first importance level function, the importance level of the key performance parameter is determined to be the third importance level;

[0123] When the key performance parameter is a parameter that affects the safety performance of the mass spectrometer to be evaluated and there is a warning message, the importance level of the key performance parameter is determined to be the second importance level;

[0124] When the key performance parameter is a parameter that affects the safety performance of the mass spectrometer to be evaluated and there is no warning information, the importance level of the key performance parameter is determined to be the first importance level, where the importance levels are arranged in the following order from high to low: first importance level, second importance level, third importance level, and fourth importance level.

[0125] The details are shown in Table 2:

[0126] Table 2 Importance level of key performance of clinical mass spectrometer

[0127] In Table 2, level 1 indicates the first importance level, level 2 indicates the second importance level, level 3 indicates the third importance level, level 4 indicates the fourth importance level; and level 5 indicates the unimportant level.

[0128] Furthermore, the method further comprises:

[0129] When the importance level of the key performance parameter is the fourth importance level, the stability capability index SCI requirement level of the key performance parameter is determined to be the fourth capability level;

[0130] When the importance level of the key performance parameter is the third importance level, the stability capability index SCI requirement level of the key performance parameter is determined to be the third capability level;

[0131] When the importance level of the key performance parameter is the second importance level, the stability capability index SCI requirement level of the key performance parameter is determined to be the second capability level;

[0132] When the importance level of the key performance parameter is the first importance level, the stability capability index SCI requirement level of the key performance parameter is determined to be the second capability level or the first capability level, where the capability levels are arranged from high to low as follows: first capability level, second capability level, third capability level and fourth capability level.

[0133] The details are shown in Table 3:

[0134] Table 3 Correspondence between the importance level of key performance and stability capability index level of clinical mass spectrometer

[0135] B in Table 3 represents the fourth ability level, A represents the third ability level, A+ represents the second ability level, and A+ and above represent the first ability level.

[0136] Furthermore, based on statistical steady state and technical steady state, determine whether each key performance parameter meets the stability requirements, including:

[0137] When the statistical steady state meets the statistical steady state requirement and the technical steady state meets the technical steady state requirement, determine whether the key performance parameters first meet the stability requirement;

[0138] When the statistical steady state does not meet the statistical steady state requirement and the technical steady state meets the technical steady state requirement, determining that the key performance parameter meets the stability requirement to a second degree, wherein the first degree is greater than the second degree;

[0139] In the case that the technical steady state does not meet the technical steady state requirements, it is determined that the key performance parameters do not meet the stability requirements.

[0140] The details are shown in Table 4:

[0141] Table 4 Stability levels of key performance indicators of clinical mass spectrometers

[0142] State I: The performance is in a statistically stable state and the stability capability index meets the requirements. This is the most ideal state, and it is determined that the key performance parameters meet the stability requirements to the greatest extent.

[0143] State II: The performance is in a statistically stable state, but the stability capability index does not meet the requirements, so it is rejected and performance improvement is required;

[0144] State III: The performance is in a state of statistical instability, but the stability capability index meets the specified requirements and is acceptable. It is recommended to analyze the abnormal causes of statistical instability when conditions permit and make continuous improvements.

[0145] State IV: The performance is in a statistically unstable state, the stability capability index does not meet the requirements, it is rejected, and performance improvement is required.

[0146] Furthermore, when the statistical steady state does not meet the statistical steady state requirement and the technical steady state meets the technical steady state requirement, after determining that the key performance parameter meets the stability requirement to a second degree, the method further includes:

[0147] Obtain the causes of statistical glitches;

[0148] Based on the cause of the statistical out-of-state, the performance of the statistical steady state that affects the key performance parameters is improved until the statistical steady state of the key performance parameters meets the statistical steady state requirements. In other words, the cause of the statistical out-of-state is found and then the performance of the statistical steady state is improved to meet the statistical steady state requirements.

[0149] Furthermore, the method further comprises:

[0150] Determine whether the statistical steady state of key performance parameters meets the statistical steady state requirements;

[0151] Determining whether the statistical steady state of key performance parameters meets the statistical steady state requirements includes:

[0152] Obtain multiple continuous quantity points of key performance parameters;

[0153] Determine the maximum number of out-of-bounds points allowed for various numbers of consecutive points;

[0154] When the number of out-of-bounds points corresponding to at least one of the multiple numbers of consecutive points is less than the corresponding maximum allowed number of out-of-bounds points, it is determined that the statistical steady state of the key performance parameter meets the statistical steady state requirement.

[0155] For example, the control chart of key performance indicator parameters must meet the statistical stability requirements. The requirements for statistical stability of control charts in statistical process control and practice are as follows:

[0156] ① 25 consecutive points, the number of out-of-bounds points d = 0;

[0157] ② 35 consecutive points, with the number of out-of-bounds points d≤1;

[0158] ③ For 100 consecutive points, the number of out-of-bounds points d≤2.

[0159] If the above conditions are not met, it is considered statistically unstable. When an instrument is in statistical instability, its actual performance values ​​will fluctuate significantly, resulting in statistical instability. At this time, the instrument may be abnormal, causing its performance to fluctuate significantly and making it difficult to operate normally and stably.

[0160] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0161] The present disclosure also provides a specific method for determining the stability of a mass spectrometer, as shown in FIG3 , the method comprising:

[0162] ① Determine key performance according to the technical requirements of clinical mass spectrometer;

[0163] ② Determine key performance stability requirements based on performance importance levels;

[0164] ③ Obtain key performance data of clinical mass spectrometers through performance experiments;

[0165] ④ Draw a mean-range control chart based on key performance data, and determine the statistical steady-state results based on the control chart results;

[0166] ⑤ For key performance data that conform to the normal distribution, the SCI value is directly calculated; for those that do not conform to the normal distribution, the SCI value is calculated and the technical steady-state result is finally determined by the SCI data value;

[0167] ⑥ Determine the key performance stability level based on statistical steady-state and technical steady-state results;

[0168] ⑦ Based on the key performance stability level, draw the final stability conclusion.

[0169] This paper proposes a method for evaluating the stability of key mass spectrometer performance. First, statistical steady-state analysis of key performance is performed using control charts. Then, technical steady-state analysis of key performance is performed using the stability capability index. Finally, the statistical and technical steady-state results are combined to determine the stability level and final results of the key performance of clinical mass spectrometers. While evaluating the stability of key performance, the stability evaluation results can be used to promptly identify instrument problems, ensuring the accuracy and effectiveness of mass spectrometer application test results.

[0170] The introduction of this evaluation method fills the gap in the stability evaluation system of clinical mass spectrometers, effectively promotes the establishment of a quality control and stability evaluation system for clinical mass spectrometers, provides a basis and method for regulatory agencies to control the quality stability evaluation of medical devices when they enter the market, and provides an evaluation basis for medical device manufacturers to continuously improve product stability, enabling mass spectrometers to achieve more stable and efficient detection in clinical applications.

[0171] The embodiments of the present disclosure also provide a mass spectrometer stability determination device. It should be noted that the mass spectrometer stability determination device of the embodiments of the present disclosure can be used to execute the mass spectrometer stability determination method provided by the embodiments of the present disclosure. The device is used to implement the above-mentioned embodiments and preferred implementation modes, and the details that have been described will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0172] The following introduces the mass spectrometer stability determination device provided by the embodiment of the present disclosure.

[0173] FIG4 is a schematic diagram of a mass spectrometer stability determination device according to an embodiment of the present disclosure. As shown in FIG4 , the device includes:

[0174] A first acquiring unit 41 is configured to acquire key performance parameters of the mass spectrometer to be evaluated, wherein the key performance parameters include at least one of the following: a parameter affecting the safety performance of the mass spectrometer to be evaluated, a parameter affecting the mass spectrometer to be evaluated in achieving a first importance level function, and a parameter affecting the mass spectrometer to be evaluated in achieving a second importance level function;

[0175] a control unit 42 configured to control the mass spectrometer to be evaluated to perform a performance test to obtain test data;

[0176] An analysis unit 43 is configured to perform steady-state analysis based on the test data to obtain statistical steady-state and technical steady-state of each key performance parameter. The statistical steady-state indicates whether the key performance parameter is in a controlled state within a preset time, and the technical steady-state indicates whether the key performance parameter is within a preset parameter range within a preset time.

[0177] The first determining unit 44 is configured to determine whether each key performance parameter meets the stability requirement according to the statistical steady state and the technical steady state.

[0178] The mass spectrometer stability determination device disclosed herein comprises a first acquisition unit that acquires key performance parameters of the mass spectrometer to be evaluated, a control unit that controls the mass spectrometer to be evaluated to perform a performance test to obtain test data, and an analysis unit that performs a steady-state analysis based on the test data to obtain the statistical steady-state and technical steady-state of each key performance parameter. Based on the statistical steady-state and technical steady-state, the first determination unit determines whether each key performance parameter meets the stability requirements. This solution determines whether each key performance parameter meets the stability requirements based on the statistical steady-state and technical steady-state of the key performance parameters. This achieves accurate and efficient evaluation of the key performance stability of the mass spectrometer during use from two dimensions.

[0179] Furthermore, the analysis unit includes a first determination module, a second determination module, and a third determination module. The first determination module is used to determine the mean-range control chart of each key performance parameter based on the test data; the second determination module is used to determine characteristic parameters based on the mean-range control chart, and the characteristic parameters include at least one of the following: the mean data point, the positional relationship between the mean data point and the control limit, the positional relationship between the mean data point and the center line, and the fluctuation characteristics of the mean-range control chart; and the third determination module is used to determine the statistical steady state of the key performance parameter based on the characteristic parameters. Accurate determination of the statistical steady state of the key performance parameter is achieved.

[0180] Furthermore, the analysis unit includes a fourth determination module, a calculation module, and a processing module. The fourth determination module is used to determine whether each key performance parameter set conforms to a normal distribution based on the test data. The key performance parameter set includes multiple key performance parameters of the same type. The calculation module is used to calculate the stability capability index of the corresponding key performance parameter based on the key performance parameter set when the key performance parameter set conforms to a normal distribution. The stability capability index represents the technical steady state of the key performance parameter. The processing module is used to perform normality conversion processing on the key performance parameter set when the key performance parameter set does not conform to a normal distribution to obtain a converted key performance parameter set that conforms to a normal distribution, and calculate the stability capability index (SCI) of the corresponding key performance parameter based on the converted key performance parameter set that conforms to a normal distribution. This achieves accurate determination of the technical steady state of the key performance parameters.

[0181] Furthermore, the fourth determination module is further configured to perform a normal distribution conformity test on each key performance parameter set using the Kolmogorov-Smirnov test method to determine whether each key performance parameter set conforms to the normal distribution, thereby achieving verification of the normal distribution.

[0182] Furthermore, the conversion module includes a first determining submodule, a second determining submodule and a third determining submodule.

[0183] The first determination submodule is used to determine the stability capability index SCI of the key performance parameter according to the mean value of the key performance parameter, the parameter lower limit value of the key performance parameter and the standard deviation of the key performance parameter when the key performance parameter is a large parameter;

[0184] The second determination submodule is used to determine the stability capability index SCI of the key performance parameter according to the mean value of the key performance parameter, the parameter upper limit value of the key performance parameter and the standard deviation of the key performance parameter when the key performance parameter is a minimum parameter;

[0185] The third determination submodule is configured to determine the stability capability index (SCI) of the key performance parameter based on the mean value, lower limit value, upper limit value, and standard deviation of the key performance parameter when the key performance parameter is a target parameter. This allows for accurate determination of the stability capability index (SCI) of the key performance parameter under different circumstances.

[0186] Furthermore, the processing module includes at least one of a first conversion submodule, a second conversion submodule, a third conversion submodule, a fourth conversion submodule, a fifth conversion submodule, a sixth conversion submodule, and a seventh conversion submodule.

[0187] The first conversion submodule is used to perform normality conversion processing on the key performance parameter set that does not conform to the normal distribution using a logarithmic transformation method;

[0188] The second conversion submodule is used to perform normality conversion processing on the key performance parameter set that does not conform to the normal distribution using the square root transformation method;

[0189] The third conversion submodule is used to perform normality conversion processing on the key performance parameter set that does not conform to the normal distribution by using the square root arcsine transformation method;

[0190] The fourth conversion submodule is used to perform normality conversion processing on the key performance parameter set that does not conform to the normal distribution by using the square transformation method;

[0191] The fifth conversion submodule is used to perform normality conversion processing on the key performance parameter set that does not conform to the normal distribution by using the inverse transformation method;

[0192] The sixth conversion submodule is used to perform normality conversion processing on the key performance parameter set that does not conform to the normal distribution using the Box-Cox transformation method;

[0193] The seventh conversion submodule is used to perform normality conversion on the key performance parameter set that does not conform to the normal distribution using the normal score method, and to convert the key performance parameter set that does not conform to the normal distribution into the key performance parameter set that conforms to the normal distribution using different methods.

[0194] Furthermore, the device further includes a second determining unit, a third determining unit, a fourth determining unit and a fifth determining unit.

[0195] The second determining unit is configured to determine the importance level of the key performance parameter as a fourth importance level when the key performance parameter is a parameter that affects the mass spectrometer to be evaluated to achieve a function of a second importance level;

[0196] The third determining unit is configured to determine the importance level of the key performance parameter as a third importance level when the key performance parameter is a parameter that affects the mass spectrometer to be evaluated to achieve a function of the first importance level;

[0197] The fourth determining unit is configured to determine that the importance level of the key performance parameter is a second importance level when the key performance parameter is a parameter that affects the safety performance of the mass spectrometer to be evaluated and there is a warning message;

[0198] The fifth determination unit is used to determine that the importance level of the key performance parameter is the first importance level when the key performance parameter is a parameter that affects the safety performance of the mass spectrometer to be evaluated and there is no warning information, wherein the importance levels are arranged in the following order from high to low: first importance level, second importance level, third importance level, fourth importance level.

[0199] Furthermore, the apparatus further includes a sixth determining unit, a seventh determining unit, an eighth determining unit, and a ninth determining unit.

[0200] The sixth determining unit is configured to determine, when the importance level of the key performance parameter is the fourth importance level, the stability capability index SCI requirement level of the key performance parameter to be the fourth capability level;

[0201] The seventh determining unit is configured to determine, when the importance level of the key performance parameter is the third importance level, the stability capability index SCI requirement level of the key performance parameter to be the third capability level;

[0202] The eighth determining unit is configured to determine, when the importance level of the key performance parameter is the second importance level, the stability capability index SCI requirement level of the key performance parameter to be the second capability level;

[0203] The ninth determination unit is used to determine the stability capability index SCI requirement level of the key performance parameter as the second capability level or the first capability level when the importance level of the key performance parameter is the first importance level, wherein the arrangement order of the capability levels from high to low is: first capability level, second capability level, third capability level and fourth capability level.

[0204] Furthermore, the first determining unit includes a fifth determining module, a sixth determining module and a seventh determining module.

[0205] The fifth determining module is used to determine that the key performance parameter firstly satisfies the stability requirement when the statistical steady state satisfies the statistical steady state requirement and the technical steady state satisfies the technical steady state requirement;

[0206] The sixth determining module is configured to determine, when the statistical steady state does not meet the statistical steady state requirement and the technical steady state meets the technical steady state requirement, whether the key performance parameter meets the stability requirement to a preliminary second degree, wherein the first degree is greater than the second degree;

[0207] The seventh determination module is used to determine that the key performance parameter does not meet the stability requirement when the technical steady state does not meet the technical steady state requirement.

[0208] Furthermore, the device also includes: an acquisition unit and an improvement unit, the acquisition unit is used to obtain the cause of the statistical malfunction after determining that the key performance parameters preliminarily meet the stability requirements to a second extent when the statistical steady state does not meet the statistical steady state requirements and the technical steady state meets the technical steady state requirements; the improvement unit is used to improve the performance of the statistical steady state that affects the key performance parameters based on the cause of the statistical malfunction until the statistical steady state of the key performance parameters meets the statistical steady state requirements.

[0209] Furthermore, the device further includes a tenth determining unit, which is used to determine whether the statistical steady state of the key performance parameter meets the statistical steady state requirement; the tenth determining unit includes an acquisition module, an eighth determining module and a ninth determining module,

[0210] The acquisition module is used to obtain the number of multiple continuous points of key performance parameters;

[0211] The eighth determination module is used to determine the maximum allowable number of out-of-bounds points corresponding to various numbers of consecutive points;

[0212] The ninth determination module is used to determine that the statistical steady state of the key performance parameter meets the statistical steady state requirement when the number of out-of-bounds points corresponding to at least one of the multiple numbers of consecutive points is less than the corresponding maximum allowable number of out-of-bounds points.

[0213] Furthermore, the key performance parameters include at least one of the following: detection limit, ion transmission efficiency, and parameters affecting anti-interference capability.

[0214] The mass spectrometer stability determination device includes a processor and a memory. The first acquisition unit, control unit, analysis unit, first determination unit, etc. are all stored as program units in the memory. The processor executes the program units stored in the memory to implement corresponding functions. The above modules are all located in the same processor; alternatively, the above modules can be located in different processors in any combination.

[0215] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the stability of the mass spectrometer can be accurately determined by adjusting the kernel parameters.

[0216] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0217] In this embodiment, a method for testing the detection limit performance of a trace element analyzer running on a mobile terminal, a computer terminal or a similar computing device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0218] FIG5 is a flow chart of a method for testing the detection limit performance of a trace element analyzer according to an embodiment of the present disclosure. As shown in FIG5 , the method includes the following steps:

[0219] Step S501, performing ignition control on the trace element analyzer, and performing tuning control on the trace element analyzer after the trace element analyzer is successfully ignited;

[0220] The purpose of controlling the ignition of the trace element analyzer is to put the trace element analyzer into operation so as to perform subsequent detection limit performance testing.

[0221] The purpose of tuning control is to achieve the desired signal strength and resolution by adjusting relevant parameters.

[0222] Step S502, when the trace element analyzer has been tuned and controlled and meets the test standard, selecting parameters of the trace element analyzer to obtain target parameters, and editing the target parameters, wherein the target parameters are parameters required for the detection limit performance test of the trace element analyzer, wherein editing is to set the relevant performance of the target parameters;

[0223] After the instrument is successfully ignited, automatic tuning is performed. When the response values ​​meet Li ≥ 100,000, Co ≥ 600,000, In ≥ 1,000,000, U ≥ 1,000,000, oxidation rate ≤ 3%, and double charge rate ≤ 3%, where Li represents lithium, Co represents cobalt, In represents indium, and U represents uranium, it is considered that the automatic tuning meets the test standards.

[0224] The detection limit is the analyte concentration corresponding to the minimum measured value that can be detected with an appropriate confidence level. The JJF1159-2006 standard stipulates that the detection limit calibration elements, among the key technical indicators of ICP-MS, include Li, Y, and Tl. Furthermore, as elements required for human body detection, these elements have mass numbers ranging from low, medium, and high, covering the entire mass range of the mass axis, serving as an important basis for evaluating instrument performance. Therefore, Li, Y, and Tl can be selected as target parameters.

[0225] The relevant performance of the target parameters includes time, peristaltic pump speed, injector hole position, etc. The relevant performance corresponding to different target parameters may be the same or different.

[0226] Step S503 , performing sample-related performance testing on the selected and edited target parameters, analyzing the sample-related performance testing results, and obtaining the analysis results of the detection limit performance test.

[0227] Among them, relevant performance tests include mean, range, etc., and then the detection limit of each target parameter is analyzed.

[0228] The disclosed method for testing the detection limit performance of a trace element analyzer involves controlling the ignition of the trace element analyzer and, after successful ignition, performing tuning control on the trace element analyzer. After the tuning control and if the trace element analyzer meets the test criteria, the method selects parameters of the trace element analyzer to obtain target parameters, edits the target parameters, performs sample-related performance testing on the selected and edited target parameters, and analyzes the sample-related performance test results to obtain the analysis results of the detection limit performance test. The disclosed solution implements standardized testing of the detection limit of a trace element analyzer.

[0229] In an embodiment of the performance testing method disclosed herein, ignition control of a trace element analyzer includes:

[0230] In response to a first preset operation performed on the instrument control, displaying an instrument operation interface on the display screen;

[0231] The instrument controls are in the lower right corner of Figure 6, and the instrument operation interface is shown in the middle of Figure 6;

[0232] In response to a second preset operation on a connect instrument control in the instrument operation interface, the trace element analyzer is connected, and a vacuum open control and an instrument ignition control are popped up in the display screen;

[0233] The second preset operation may be a single-click operation, a double-click operation, or the like;

[0234] The instrument connection control is the disconnection control in Figure 6. Click the disconnection control to disconnect the trace element analyzer, and click the disconnection control again to connect to the trace element analyzer; the vacuum opening control is the vacuum closing control in Figure 6. Click the vacuum closing control to close the vacuum, and click the vacuum closing control again to open the vacuum;

[0235] In response to a third preset operation acting on a vacuum opening control, controlling the trace element analyzer to enter a vacuum ready state;

[0236] The third preset operation may be a single-click operation, a double-click operation, or the like;

[0237] In response to a fourth preset operation acting on the instrument ignition control, the trace element analyzer is controlled to enter an operating state.

[0238] The fourth preset operation may be a single-click operation, a double-click operation, or the like;

[0239] As above, the trace element analyzer is controlled to enter the operating state by connecting the instrument, turning on the vacuum and igniting.

[0240] In an embodiment of the performance testing method disclosed herein, after the trace element analyzer is successfully ignited, tuning and controlling the trace element analyzer includes:

[0241] In response to a fifth preset operation on the instrument control in the display interface, a manual tuning control and an automatic tuning control pop up below the instrument control;

[0242] The fifth preset operation may be a single-click operation, a double-click operation, or the like;

[0243] As shown in Figure 7, manual tuning controls and automatic tuning controls are displayed below the instrument control controls;

[0244] In response to a sixth preset operation on the automatic tuning control, a list of automatic tuning methods is displayed on the display interface; in response to a seventh preset operation on the list of automatic tuning methods, a target automatic tuning method is selected from the list of automatic tuning methods to automatically tune the trace element analyzer using the target automatic tuning method;

[0245] The sixth preset operation may be a single-click operation, a double-click operation, or the like;

[0246] The seventh preset operation may be a single-click operation, a double-click operation, or the like;

[0247] The list of automatic tuning methods is displayed on the left side of Figure 8(a). The automatic tuning methods include: Standard Mode - Full Version - Dual Mode - Test 2; Standard Mode - Simple Version - Dual Mode - Test 2; Collision Mode - Full Version - Dual Mode - Test 2; Collision Mode - Simple Version - Dual Mode - Test 2, etc. In a tuning mode, there are multiple tuning stages, and controls for adding a stage, deleting a stage, moving a stage up, moving a stage down, modifying a stage name, and setting tuning parameters are displayed. A tuning parameter feature code is also displayed, and the tuning parameter feature code is used to set the mode.

[0248] As shown in Figure 8(b), the display interface under Standard Mode - Full Version - Dual Mode - Test2 also displays stage parameter controls, instrument parameter controls, and element parameter controls; stage parameters include: stage, number of iterations, fine adjustment percentage, coarse adjustment average times, fine adjustment average times, and sample introduction time;

[0249] In response to an eighth preset operation acting on the manual tuning control, historical data obtained during the automatic tuning process is called to perform tuning control on the trace element analyzer.

[0250] The eighth preset operation may be a single-click operation, a double-click operation, or the like;

[0251] In the embodiment of the performance testing method disclosed herein, selecting parameters of a trace element analyzer to obtain target parameters and editing the target parameters include:

[0252] In response to a ninth preset operation on the method editing control in the display interface, presenting a parameter selection editing screen on the display screen;

[0253] The ninth preset operation may be a single-click operation, a double-click operation, or the like;

[0254] As shown in Figure 9, click the method editing control in the display interface to display the parameter selection editing screen;

[0255] In response to a sampling parameter control being acted on a parameter selection editing screen, a parameter display list is popped up on the parameter selection editing screen, and in response to a tenth preset operation being acted on the parameter display list, an element is added or an element is subtracted, and a tuning is added or deleted;

[0256] The sampling parameter control is shown in the first option on the left side of FIG9 , wherein the tenth preset operation may be a single-click operation, a double-click operation, and the like. The single-click operation may specifically be right-clicking the right box in FIG9 to increase or decrease an element;

[0257] As shown in the tuning method in the lower left corner of Figure 9, you can add or delete tuning by right-clicking the tuning interface.

[0258] In response to the analysis parameter control acting on the parameter selection editing screen, a parameter analysis list pops up on the parameter selection editing screen, and in response to the eleventh preset operation acting on the parameter analysis list, an item to be modified is selected to be modified;

[0259] In response to the analysis parameter control acting on the parameter selection editing screen as shown in FIG10 , the parameter analysis list includes scan code addition, concentration level, quality control level, fill down, etc.;

[0260] The eleventh preset operation may be a single-click operation, a double-click operation, or the like;

[0261] In response to the injection parameter control acting on the parameter selection editing screen, a parameter editing screen pops up on the parameter selection editing screen, and in response to the twelfth preset operation on the parameter editing control acting on the parameter editing screen, parameter editing is performed.

[0262] The twelfth preset operation may be a single-click operation, a double-click operation, or the like;

[0263] In response to the injection parameter control acting on the parameter selection editing screen as shown in FIG11 , the injection parameter settings include whether each step is used, as well as the time of each step, the peristaltic pump speed, the injector hole position, and whether the flushing loop is selected;

[0264] In an embodiment of the performance testing method of the present disclosure, after performing parameter editing in response to a twelfth preset operation on a parameter editing control in a parameter editing screen, the method further includes:

[0265] In response to the sample list control in the parameter selection editing screen, a sample list screen pops up in the fourth preset area of ​​the parameter selection editing screen, and in response to the thirteenth preset operation on the sample list screen, at least samples are added.

[0266] The thirteenth preset operation may be a single-click operation, a double-click operation, or the like;

[0267] In response to the sample list control in the parameter selection editing screen, as shown in Figure 12, the sample list screen includes: add sample, insert sample, fill down, priority acquisition, re-acquisition, delete acquisition, eliminate data, eliminate position, etc.

[0268] In an embodiment of the performance testing method disclosed herein, after tuning and controlling the trace element analyzer, the method further includes: performing sample detection control on the trace element analyzer;

[0269] Among them, sample detection control of trace element analyzers includes:

[0270] In response to the fourteenth preset operation on the sample detection control in the display interface, the sample detection screen is displayed on the display screen, and in response to the fifteenth preset operation on the creation control on the sample detection screen, a selection detection template list pops up on the sample detection screen to select a target detection template from the selection detection template list to use the target detection template for sample detection.

[0271] The reagents required for the detection limit test are shown in Table 5.

[0272] Table 5 Reagents required for detection limit test

[0273] The fourteenth preset operation and the fifteenth preset operation may be single-click operation, double-click operation, etc.;

[0274] As shown in Figure 13(a) and Figure 13(b), create a control in Figure 13(b), click Create, and the edited template will pop up. The edited template is in Figure 13(a), click the required template, and click OK;

[0275] It also includes: as shown in Figure 14, place the mouse in the operation area and right-click to set, click Tuning Settings, and select the required tuning parameters, as shown in Figure 15.

[0276] After the settings are completed, click Start. During the detection process, if you need to re-detect, you can click the Re-detect button, as shown in Figure 16.

[0277] After the test is completed, click Close, and a save interface will pop up. Click "Yes" to save the test file, as shown in Figure 17.

[0278] In the embodiment of the performance testing method disclosed herein, analyzing the sample-related performance test results includes:

[0279] In response to a sixteenth preset operation acting on the sample analysis control in the display interface, displaying a detection list and an analysis control in the display interface;

[0280] In response to a seventeenth predetermined operation on the analysis control, performing sample analysis;

[0281] Wherein, in response to a seventeenth preset operation acting on the analysis control, performing sample analysis includes:

[0282] In response to a seventeenth preset operation acting on the analysis control, displaying a sample analysis screen in the display interface;

[0283] In response to an eighteenth preset operation acting on the drop-down list on the sample analysis screen, a next-level analysis item is selected to perform sample analysis.

[0284] After selecting a next level analysis item in response to an eighteenth preset operation on the drop-down list on the sample analysis screen to perform sample analysis, the method further includes:

[0285] In response to the nineteenth preset operation performed on the sample analysis screen, a file export method list pops up, which includes the export file format and file display information.

[0286] The sixteenth preset operation and the seventeenth preset operation may be single-click operation, double-click operation, etc.;

[0287] As shown in Figure 18, the analysis control is in the lower right corner of Figure 18; after entering the analysis page, click the small triangle on the left to display the next level of test items, as shown in Figure 19.

[0288] Right-click to select the export format, display status, etc. (If N / A is displayed after the test, click to display CPS), as shown in Figure 20(a). Figure 20(b) shows the trace element analysis results, trace element fitting parameters, standard trace elements, and trace elements to be measured.

[0289] In order to enable those skilled in the art to more clearly understand the technical solution of the present disclosure, the implementation process of the detection limit performance testing method of the trace element analyzer disclosed in the present disclosure will be described in detail below with reference to specific embodiments.

[0290] This embodiment relates to a specific method for testing the detection limit performance of a trace element analyzer, as shown in Figure 21, including: instrument ignition, instrument control, automatic tuning, method editing, sample detection and sample analysis. If the automatic tuning response value does not meet the standard, manual tuning is performed.

[0291] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0292] This embodiment relates to a specific key performance test, including:

[0293] 1) Experimental Platform

[0294] The experiments were conducted on an Inspector SQ60 equipped with a high-efficiency concentric nebulizer and a small-volume cyclonic spray chamber, resulting in high atomization efficiency, low dead volume, and minimal memory effect. A self-excited, all-solid-state RF generator with a frequency of 27.12 MHz was used. A hexapole collision reaction cell was employed, balancing ion focusing with optimal transmission efficiency across the entire mass range.

[0295] 2) Experimental reagents

[0296] Homemade tuning solution (Li, Co, In, U, Ce, Ba solution);

[0297] Detection limit test solution (Li, Y, Tl solution);

[0298] 18.2MΩ.cm ultrapure water, obtained by Milli-Q ultrapure water machine;

[0299] Homemade diluent (simulated blood sample).

[0300] 3) Experimental methods

[0301] Adjust the instrument performance to the best, simulate the actual use environment, and perform detection limit testing. Test process:

[0302] 1. First ignite the instrument and perform automatic tuning in standard mode. At this time, the instrument performance reaches the best in standard mode.

[0303] 2. Inject 18 MΩ.cm high-purity water and measure the ion count rates at masses 7, 89, and 205. Inject the detection limit test solution, high-purity water, and measure the ion count rates at masses 7, 89, and 205. Use a dwell time of 50 ms, 3 channels, and 10 scans. Measure 11 data points for each measurement. Divide 3 times the standard deviation of the measurement results by the sensitivity of Li, Y, and Tl to obtain the detection limit.

[0304] 3. Pump in the homemade diluent to simulate blood sample injection.

[0305] 4. After four hours, repeat step 2)

[0306] 5. Perform daily cleaning and maintenance.

[0307] The following results are obtained:

[0308] Table 6 Mean and range of key performance indicators of detection limit for each subgroup

[0309] Table 7 Average values ​​of the detection limit key performance indicators of each subgroup and the average values ​​of the range of each subgroup

[0310] The calculated detection limits and control limits of each element are shown in Table 8.

[0311] Table 8 Detection limits and control limits of Li, Y, and Tl elements

[0312] Based on the data in Tables 6 and 8, the mean control chart of the detection limit mean-range control chart of the three elements Li, Y, and Tl was drawn, as shown in Figure 22.

[0313] From the mean control chart in the mean-range control chart of the detection limits of the three elements Li, Y, and Tl in Figure 22, it can be seen that the total number of detection limit means of each element subgroup is 75, and the number of points where the detection limit mean of the Li element sample subgroup is outside the control limit is 1, the number of points where the detection limit mean of the Y element sample subgroup is outside the control limit is 8, and the number of points where the detection limit mean of the Tl element sample subgroup is outside the control limit is 6, as shown in Table 5.

[0314] Table 9 Statistics of out-of-bounds points in the mean-range control chart of the detection limits of the three elements Li, Y, and Tl

[0315] The detection limit performance index data set was transformed using the Box-Cox function of minitab17 software. The transformed frequency histogram was then plotted, as shown in Figure 23, and the mean and standard deviation were calculated, as shown in Tables 10 and 11.

[0316] Table 10 Mean and standard deviation of detection limit data after transformation

[0317] The normality test of the transformed data set was performed using the KS test, as shown in Tables 11, 12, and 13.

[0318] Table 11 Normal distribution test table of Li element detection limit data after transformation

[0319] From Table 11, we can get: Dn=max{δ i}=0.0340.

[0320] From the significance level α = 0.05, the sample size n = 375, and the calculation result d(375, 0.05) = 0.07023, Dn < d(375, 0.05), we accept the null hypothesis H0, that is, the data set after the detection limit of Tl element is transformed and obeys the normal distribution N[0.9108, (0.08405) 2 ].

[0321] Table 12 Normal distribution test table of Y element detection limit data after transformation

[0322] From Table 12, we can get: Dn=max{δ i}=0.0391.

[0323] From the significance level α = 0.05, the sample size n = 375, we can calculate d(375, 0.05) = 0.07023, Dn < d(375, 0.05), so we accept the null hypothesis H0, that is, the data set after the detection limit transformation of the Y element obeys the normal distribution N[0.7833, (0.04086) 2 ].

[0324] Table 13 Normal distribution test table of Tl element detection limit data after transformation

[0325] From Table 13, we can get: Dn=max{δ i}=0.0440.

[0326] From the significance level α = 0.05, the sample size n = 375, and the calculation result d(375, 0.05) = 0.0702, Dn < d(375, 0.05), we accept the null hypothesis H0, that is, the data set after the detection limit of Tl element is transformed and obeys the normal distribution N[1.024, (0.01063) 2 ].

[0327] The stability index (SCI) value was calculated for the data set that conformed to the normal distribution after the detection limit performance index was transformed. The detailed results are shown in Table 14.

[0328] Table 14 Detection limit performance index SCI value

[0329] It can be seen from Table 14 that the SCI level of detection limit of Li element is A, the SCI level of detection limit of Y element is A++, and the SCI level of detection limit of Tl element is A++.

[0330] According to the technical steady-state evaluation standard for bond performance, it can be seen from Table 14 that the SCI grade of the detection limits of Li, Y, and Tl elements all belong to A++ level, so the technical steady-state meets the requirements.

[0331] The stability results of key performance indicators of clinical mass spectrometer are shown in Table 15.

[0332] Table 15 Key performance indicator stability results

[0333] Table 15 shows that the detection limit performance indicator stability for the element Li is at state I, indicating good performance stability, which is at an ideal level. The detection limit performance for elements Y and Tl is in a state of statistical instability, but the technical stability capability index meets the specified requirements, indicating technical stability, and is acceptable. However, due to the statistical instability of elements Y and Tl, the instrument was repaired, and an insulation burn fault was discovered on the power cord of the RF power amplifier board of the ICP-MS main unit. Further analysis revealed that the RF power amplifier board draws a high current during operation, and the rated current of the power cord is almost identical to the operating current, leaving no current margin. The high current caused the wire to heat up significantly during long-term operation, resulting in insulation burn, which ultimately affected the stability of the instrument's detection limit performance. Replacing the power cord with a higher rated current significantly reduced the heat generated, resolving the issue and returning the instrument's detection limit performance stability to the required level.

[0334] The embodiments of the present disclosure also provide a trace element analyzer detection limit performance test device. It should be noted that the trace element analyzer detection limit performance test device of the embodiments of the present disclosure can be used to execute the trace element analyzer detection limit performance test method provided by the embodiments of the present disclosure. The device is used to implement the above-mentioned embodiments and preferred implementation methods, and those that have been explained will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceived.

[0335] The following introduces the detection limit performance testing device of the trace element analyzer provided in the embodiment of the present disclosure.

[0336] FIG24 is a schematic diagram of a detection limit performance test device for a trace element analyzer according to an embodiment of the present disclosure. As shown in FIG24 , the device includes:

[0337] The first control unit 100 of the testing device is used to control the ignition of the trace element analyzer and to perform tuning control on the trace element analyzer after the trace element analyzer is successfully ignited;

[0338] The first processing unit 200 of the testing device is configured to select parameters of the trace element analyzer to obtain target parameters, and edit the target parameters, when the trace element analyzer has been tuned and controlled and meets the test standards. The target parameters are parameters required for performing a detection limit performance test on the trace element analyzer, and editing is to set performance related to the target parameters.

[0339] The second processing unit 300 of the testing device is used to perform sample-related performance testing on the selected and edited target parameters, analyze the sample-related performance testing results, and obtain analysis results of the detection limit performance test.

[0340] The present invention discloses a detection limit performance test device for a trace element analyzer. The first control unit of the test device controls the ignition of the trace element analyzer. The first processing unit of the test device performs tuning control on the trace element analyzer after the trace element analyzer is successfully ignited. After the tuning control and when the trace element analyzer meets the test standard, the first processing unit of the test device selects parameters of the trace element analyzer to obtain target parameters and edits the target parameters. The second processing unit of the test device performs sample-related performance testing on the selected and edited target parameters, analyzes the sample-related performance test results, and obtains the analysis results of the detection limit performance test. The disclosed solution realizes the standardized testing of the detection limit of the trace element analyzer.

[0341] In an embodiment of the device disclosed herein, the first control unit of the test device includes a first response module of the test device, a second response module of the test device, a third response module of the test device, and a fourth response module of the test device. The first response module of the test device is used to respond to a first preset operation acting on the instrument control and display the operating instrument interface on the display screen; the second response module of the test device is used to respond to a second preset operation acting on the connecting instrument control in the operating instrument interface to connect the trace element analyzer, and pop up the vacuum opening control and the instrument ignition control on the display screen; the third response module of the test device responds to the third preset operation acting on the vacuum opening control to control the trace element analyzer to enter the vacuum ready state; the fourth response module of the test device is used to respond to the fourth preset operation acting on the instrument ignition control to control the trace element analyzer to enter the running state. As above, controlling the trace element analyzer to enter the running state is achieved by connecting the instrument, turning on the vacuum, and igniting.

[0342] In an embodiment of the device disclosed herein, the first control unit of the test device further includes a fifth response module, a sixth response module, and a seventh response module. The fifth response module is configured to, in response to a fifth preset operation on an instrument control control in a display interface, pop up a manual tuning control and an automatic tuning control below the instrument control control; the sixth response module is configured to, in response to a sixth preset operation on the automatic tuning control, display a list of automatic tuning methods on the display interface; and, in response to a seventh preset operation on the list of automatic tuning methods, select a target automatic tuning method from the list of automatic tuning methods to automatically tune the trace element analyzer using the target automatic tuning method; and the seventh response module is configured to, in response to an eighth preset operation on the manual tuning control, call historical data obtained during the automatic tuning process to perform tuning control on the trace element analyzer. This achieves tuning control of the trace element analyzer.

[0343] In an embodiment of the device disclosed herein, the first processing unit of the test device includes an eighth response module, a ninth response module, a tenth response module, and an eleventh response module. The eighth response module is configured to display a parameter selection and editing screen on the display screen in response to a ninth preset operation on a method editing control in a display interface; the ninth response module is configured to pop up a parameter display list on the parameter selection and editing screen in response to a sampling parameter control on the parameter selection and editing screen, and to add or subtract elements and add or delete tuning in response to a tenth preset operation on the parameter display list; the tenth response module is configured to pop up a parameter analysis list on the parameter selection and editing screen in response to an analysis parameter control on the parameter selection and editing screen, and to select an item to be modified in response to an eleventh preset operation on the parameter analysis list for modification; and the eleventh response module is configured to pop up a parameter editing screen on the parameter selection and editing screen in response to an injection parameter control on the parameter selection and editing screen, and to perform parameter editing in response to a twelfth preset operation on the parameter editing control on the parameter editing screen. This enables parameter editing.

[0344] In an embodiment of the device disclosed herein, the device further includes a first test device response unit, configured to, after performing parameter editing in response to a twelfth preset operation on a parameter editing control in the parameter editing screen, respond to a sample list control in the parameter selection editing screen to pop up a sample list screen in a fourth preset area of ​​the parameter selection editing screen, and respond to a thirteenth preset operation on the sample list screen to at least add a sample, thereby at least implementing the addition of a sample.

[0345] In an embodiment of the device disclosed herein, the device further comprises a second control unit of the testing device, the second control unit of the testing device being configured to perform sample detection control on the trace element analyzer after performing tuning control on the trace element analyzer;

[0346] The second control unit of the testing device includes a twelfth response module of the testing device, which is used to respond to a fourteenth preset operation on the sample detection control in the display interface, display a sample detection screen on the display screen, and respond to a fifteenth preset operation on the create control on the sample detection screen, pop up a detection template selection list on the sample detection screen, select a target detection template from the detection template selection list, and use the target detection template to perform sample detection. The target detection template is selected from the detection template selection list.

[0347] In an embodiment of the device disclosed herein, the second processing unit of the testing device includes a thirteenth response module of the testing device and a fourteenth response module of the testing device. The thirteenth response module of the testing device is used to respond to the sixteenth preset operation acting on the sample analysis control in the display interface, and display the detection list and analysis control on the display interface; the fourteenth response module of the testing device is used to respond to the seventeenth preset operation acting on the analysis control to perform sample analysis.

[0348] In the device embodiment of the present disclosure, the fourteenth response module of the test device includes a first response submodule of the test device and a second response submodule of the test device. The first response submodule of the test device is used to display a sample analysis screen on the display interface in response to a seventeenth preset operation on the analysis control; the second response submodule of the test device is used to select a next-level analysis item in response to an eighteenth preset operation on the drop-down list on the sample analysis screen to perform sample analysis. This implements sample analysis.

[0349] In an embodiment of the device disclosed herein, the device further includes a second response unit of the testing device, which is configured to, after selecting a next-level analysis item for sample analysis in response to an eighteenth preset operation on a drop-down list on a sample analysis screen, pop up a file export method list in response to a nineteenth preset operation on the sample analysis screen, including an export file format and file display information, thereby saving the analysis results.

[0350] The detection limit performance testing device for a trace element analyzer includes a processor and memory. The first control unit, first processing unit, and second processing unit of the testing device are stored as program units in the memory. The processor executes the program units stored in the memory to implement corresponding functions. The aforementioned modules are all located in the same processor; alternatively, the aforementioned modules can be located in different processors in any combination.

[0351] An embodiment of the present disclosure provides a computer-readable storage medium, which includes a stored program. When the program is run, the device where the computer-readable storage medium is located is controlled to execute the mass spectrometer stability determination method and the trace element analyzer detection limit performance test method.

[0352] An embodiment of the present disclosure provides a processor, which is used to run a program, wherein when the program is run, the method for determining the stability of a mass spectrometer and the method for testing the detection limit performance of a trace element analyzer are executed.

[0353] An embodiment of the present disclosure provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the mass spectrometer stability determination method and the trace element analyzer detection limit performance test method are implemented.

[0354] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0355] The present disclosure also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes at least the steps of the mass spectrometer stability determination method and the trace element analyzer detection limit performance test method.

[0356] Obviously, those skilled in the art should understand that the modules or steps of the present disclosure described above can be implemented using a general-purpose computing device, they can be concentrated on a single computing device, or distributed across a network composed of multiple computing devices, they can be implemented using program code executable by the computing device, and thus, they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be performed in a different order than herein, or they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. Thus, the present disclosure is not limited to any particular combination of hardware and software.

[0357] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0358] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0359] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0360] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0361] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0362] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0363] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0364] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, commodity, or apparatus that includes the element.

[0365] The foregoing description is merely a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present disclosure shall be included within the scope of protection of the present disclosure.

Claims

1. A method for determining the stability of a mass spectrometer, wherein: include: Acquiring key performance parameters of the mass spectrometer to be evaluated, wherein the key performance parameters include at least one of the following: parameters affecting the safety performance of the mass spectrometer to be evaluated, parameters affecting the mass spectrometer to be evaluated to achieve a first importance level function, and parameters affecting the mass spectrometer to be evaluated to achieve a second importance level function; Controlling the mass spectrometer to be evaluated to perform a performance test to obtain test data; Perform steady-state analysis based on the test data to obtain statistical steady-state and technical steady-state of each of the key performance parameters, wherein the statistical steady-state indicates whether the key performance parameter is in a controlled state within a preset time, and the technical steady-state indicates whether the key performance parameter is within a preset parameter range within the preset time; According to the statistical steady state and the technical steady state, it is determined whether each of the key performance parameters meets the stability requirement.

2. The method according to claim 1, wherein: Based on the test data, a steady-state analysis is performed to obtain the statistical steady-state of each of the key performance parameters, including: Determine a mean range control chart of each of the key performance parameters based on the test data; Determining characteristic parameters based on the mean range control chart, the characteristic parameters including at least one of the following: mean data points, positional relationships between the mean data points and control limits, positional relationships between the mean data points and center lines, and fluctuation characteristics of the mean range control chart; The statistical steady state of the key performance parameter is determined based on the characteristic parameter.

3. The method according to claim 1, wherein: Based on the test data, a steady-state analysis is performed to obtain the technical steady-state of each of the key performance parameters, including: Determining whether each key performance parameter set conforms to a normal distribution according to the test data, wherein the key performance parameter set includes a plurality of key performance parameters of the same type; In the case where the key performance parameter set conforms to a normal distribution, a stability capability index of the corresponding key performance parameter is calculated according to the key performance parameter set, wherein the stability capability index represents the technical steady state of the key performance parameter; In the case that the key performance parameter set does not conform to the normal distribution, the key performance parameter set is subjected to normality conversion processing to obtain a converted key performance parameter set that conforms to the normal distribution, and the stability capability index SCI of the corresponding key performance parameter is calculated based on the converted key performance parameter set that conforms to the normal distribution.

4. The method according to claim 3, wherein: Determine whether each key performance parameter set conforms to a normal distribution based on the test data, including: The Kolmogorov-Smirnov test method is used to perform a normal distribution conformity test on each of the key performance parameter sets to determine whether each key performance parameter set conforms to the normal distribution.

5. The method according to claim 3, wherein: The stability capability index SCI of the corresponding key performance parameter is calculated according to the key performance parameter set, including: In the case where the key performance parameter is a large parameter, determining the stability capability index SCI of the key performance parameter according to the mean value of the key performance parameter, the parameter lower limit value of the key performance parameter and the standard deviation of the key performance parameter; In the case where the key performance parameter is a minimum parameter, determining the stability capability index SCI of the key performance parameter according to the mean value of the key performance parameter, the parameter upper limit value of the key performance parameter and the standard deviation of the key performance parameter; When the key performance parameter is a target parameter, the stability capability index SCI of the key performance parameter is determined according to the mean value of the key performance parameter, the lower limit value of the key performance parameter, the upper limit value of the key performance parameter and the standard deviation of the key performance parameter.

6. The method according to claim 3, wherein: The key performance parameter set that does not conform to the normal distribution is subjected to normal transformation processing, including at least one of the following: Performing the normality transformation processing on the key performance parameter set that does not conform to the normal distribution by using a logarithmic transformation method; Performing the normality transformation process on the key performance parameter set that does not conform to the normal distribution by using a square root transformation method; Performing the normality transformation process on the key performance parameter set that does not conform to the normal distribution by using the square root arcsine transformation method; Performing the normality transformation process on the key performance parameter set that does not conform to the normal distribution by using a square transformation method; Performing the normality conversion process on the key performance parameter set that does not conform to the normal distribution by using the inverse transformation method; Using the Box-Cox transformation method to perform the normality transformation processing on the key performance parameter set that does not conform to the normal distribution; The normality conversion process is performed on the key performance parameter set that does not conform to the normal distribution using the normal score method.

7. The method according to claim 1, wherein: The method further comprises: In the case where the key performance parameter is a parameter that affects the mass spectrometer to be evaluated to achieve a function of the second importance level, determining the importance level of the key performance parameter to be the fourth importance level; In the case where the key performance parameter is a parameter that affects the mass spectrometer to be evaluated to achieve a function of a first importance level, determining the importance level of the key performance parameter to be a third importance level; When the key performance parameter is a parameter that affects the safety performance of the mass spectrometer to be evaluated and there is warning information, determining the importance level of the key performance parameter to be the second importance level; When the key performance parameter is a parameter that affects the safety performance of the mass spectrometer to be evaluated and there is no warning information, the importance level of the key performance parameter is determined to be the first importance level, wherein: The order of importance levels from high to low is: the first importance level, the second importance level, the third importance level, and the fourth importance level.

8. The method according to claim 7, wherein: The method further comprises: When the importance level of the key performance parameter is the fourth importance level, determining the stability capability index SCI requirement level of the key performance parameter to be the fourth capability level; When the importance level of the key performance parameter is the third importance level, determining the stability capability index SCI requirement level of the key performance parameter to be the third capability level; When the importance level of the key performance parameter is the second importance level, determining the stability capability index SCI requirement level of the key performance parameter to be the second capability level; When the importance level of the key performance parameter is the first importance level, the stability capability index SCI requirement level of the key performance parameter is determined to be the second capability level or the first capability level, wherein the capability levels are arranged from high to low as follows: the first capability level, the second capability level, the third capability level and the fourth capability level.

9. The method according to claim 1, wherein: Determining whether each of the key performance parameters meets the stability requirement according to the statistical steady state and the technical steady state includes: In the case where the statistical steady state meets the statistical steady state requirement, and the technical steady state meets the technical steady state requirement, determining that the key performance parameter meets the stability requirement to a first degree; In the case where the statistical steady state does not meet the statistical steady state requirement and the technical steady state meets the technical steady state requirement, determining that a second degree of the key performance parameter meets the stability requirement, wherein the first degree is greater than the second degree; In a case where the technical steady state does not meet the technical steady state requirement, it is determined that the key performance parameter does not meet the stability requirement.

10. The method according to claim 9, wherein: In the case where the statistical steady state does not meet the statistical steady state requirement and the technical steady state meets the technical steady state requirement, after determining that the key performance parameter meets the stability requirement to a second degree, the method further includes: Obtain the causes of statistical glitches; The performance of the statistical steady state affecting the key performance parameter is improved based on the cause of the statistical out-of-state, until the statistical steady state of the key performance parameter meets the statistical steady state requirement.

11. The method according to claim 9, wherein: The method further comprises: Determining whether the statistical steady state of the key performance parameter meets the statistical steady state requirement; Wherein, determining whether the statistical steady state of the key performance parameter meets the statistical steady state requirement includes: Obtaining the number of multiple consecutive points of the key performance parameters; Determine the maximum allowable number of out-of-bounds points corresponding to the various consecutive numbers of points; When the number of out-of-bounds points corresponding to at least one of the multiple numbers of consecutive points is less than the corresponding maximum allowed number of out-of-bounds points, it is determined that the statistical steady state of the key performance parameter meets the statistical steady state requirement.

12. The method according to any one of claims 1 to 11, wherein: The key performance parameters include at least one of the following: Detection limit, ion transmission efficiency, and parameters affecting anti-interference ability.

13. A method for testing the detection limit performance of a trace element analyzer, wherein: The trace element analyzer is a mass spectrometer, and the stability of the mass spectrometer is achieved by using the mass spectrometer stability determination method according to any one of claims 1 to 12, comprising: Performing ignition control on a trace element analyzer, and performing tuning control on the trace element analyzer after the trace element analyzer is successfully ignited; After the tuning control and when the trace element analyzer meets the test standard, the parameters of the trace element analyzer are selected to obtain target parameters, and the target parameters are edited, wherein the target parameters are parameters required for the detection limit performance test of the trace element analyzer, and the editing is to set the relevant performance of the target parameters; The selected and edited target parameters are subjected to sample-related performance testing, and the sample-related performance testing results are analyzed to obtain the analysis results of the detection limit performance test.

14. The method according to claim 13, wherein: Ignition control for trace element analyzers, including: In response to a first preset operation acting on the instrument control, displaying an operating instrument interface on the display screen; In response to a second preset operation on a connect instrument control in the operating instrument interface, the trace element analyzer is connected, and a vacuum open control and an instrument ignition control are popped up in the display screen; In response to a third preset operation acting on the vacuum opening control, controlling the trace element analyzer to enter a vacuum ready state; In response to a fourth preset operation acting on the instrument ignition control, the trace element analyzer is controlled to enter an operating state.

15. The method according to claim 13, wherein: After the trace element analyzer is successfully ignited, the trace element analyzer is tuned and controlled, including: In response to a fifth preset operation acting on an instrument control control in the display interface, a manual tuning control and an automatic tuning control are popped up below the instrument control control; In response to a sixth preset operation on the automatic tuning control, displaying an automatic tuning method list on the display interface, and in response to a seventh preset operation on the automatic tuning method list, selecting a target automatic tuning method from the automatic tuning method list to automatically tune the trace element analyzer using the target automatic tuning method; In response to an eighth preset operation acting on the manual tuning control, historical data obtained during the automatic tuning process is called to perform tuning control on the trace element analyzer.

16. The method according to claim 13, wherein: Selecting parameters of the trace element analyzer to obtain target parameters, and editing the target parameters, including: In response to a ninth preset operation acting on a method editing control in the display interface, displaying a parameter selection editing screen on the display screen; In response to a sampling parameter control acting on the parameter selection editing screen, a parameter display list pops up on the parameter selection editing screen, and in response to a tenth preset operation acting on the parameter display list, an element is added or an element is reduced, and a tuning is added or deleted; In response to the analysis parameter control acting on the parameter selection editing screen, a parameter analysis list pops up on the parameter selection editing screen, and in response to the eleventh preset operation acting on the parameter analysis list, an item to be modified is selected to be modified; In response to the injection parameter control acting on the parameter selection and editing screen, a parameter editing screen pops up on the parameter selection and editing screen, and in response to the twelfth preset operation acting on the parameter editing control in the parameter editing screen, parameter editing is performed.

17. The method according to claim 16, wherein: After responding to a twelfth preset operation on the parameter editing control in the parameter editing screen to perform parameter editing, the method further includes: In response to a sample list control in the parameter selection editing screen, a sample list screen pops up in a fourth preset area of ​​the parameter selection editing screen, and in response to a thirteenth preset operation on the sample list screen, at least samples are added.

18. The method according to claim 13, wherein: After performing tuning control on the trace element analyzer, the method further includes: performing sample detection control on the trace element analyzer; Wherein, the sample detection control of the trace element analyzer includes: In response to the fourteenth preset operation acting on the sample detection control in the display interface, a sample detection screen is displayed on the display screen, and in response to the fifteenth preset operation acting on the creation control on the sample detection screen, a detection template selection list pops up on the sample detection screen to select a target detection template from the detection template selection list, so as to use the target detection template for sample detection.

19. The method according to claim 13, wherein: Analysis of sample-related performance test results includes: In response to a sixteenth preset operation acting on a sample analysis control in the display interface, a detection list and an analysis control are displayed on the display interface; In response to a seventeenth preset operation acting on the analysis control, sample analysis is performed.

20. The method according to claim 19, wherein: In response to a seventeenth preset operation acting on the analysis control, the sample analysis is performed, including: In response to a seventeenth preset operation acting on the analysis control, displaying a sample analysis screen in the display interface; In response to an eighteenth preset operation acting on the drop-down list on the sample analysis screen, a next level analysis item is selected to perform the sample analysis.

21. The method according to claim 20, wherein: After selecting a next level analysis item in response to an eighteenth preset operation on the drop-down list on the sample analysis screen to perform the sample analysis, the method further includes: In response to the nineteenth preset operation on the sample analysis screen, a file export method list pops up, and the file export method list includes an export file format and file display information.

22. A mass spectrometer stability determination device, wherein: include: A first acquisition unit is configured to acquire key performance parameters of the mass spectrometer to be evaluated, wherein the key performance parameters include at least one of the following: a parameter affecting the safety performance of the mass spectrometer to be evaluated, a parameter affecting the mass spectrometer to be evaluated to achieve a first importance level function, and a parameter affecting the mass spectrometer to be evaluated to achieve a second importance level function; A control unit configured to control the mass spectrometer to be evaluated to perform a performance test to obtain test data; an analysis unit, configured to perform steady-state analysis based on the test data to obtain a statistical steady-state and a technical steady-state of each of the key performance parameters, wherein the statistical steady-state indicates whether the key performance parameter is in a controlled state within a preset time, and the technical steady-state indicates whether the key performance parameter is within a preset parameter range within the preset time; The first determination unit is configured to determine whether each of the key performance parameters meets the stability requirement according to the statistical steady state and the technical steady state.

23. A detection limit performance test device for a trace element analyzer, wherein: The trace element analyzer is a mass spectrometer, and the stability of the mass spectrometer is achieved by using the mass spectrometer stability determination method according to any one of claims 1 to 12, comprising: The first control unit of the testing device is used to perform ignition control on the trace element analyzer, and to perform tuning control on the trace element analyzer after the trace element analyzer is successfully ignited; The first processing unit of the testing device is used for selecting parameters of the trace element analyzer to obtain target parameters and editing the target parameters when the trace element analyzer meets the test standard after the tuning control, wherein the target parameters are parameters required for the detection limit performance test of the trace element analyzer, and wherein the editing is to set the relevant performance of the target parameters; The second processing unit of the testing device is used to perform sample-related performance testing on the selected and edited target parameters, analyze the sample-related performance testing results, and obtain the analysis results of the detection limit performance test.

24. A computer-readable storage medium, wherein: The computer-readable storage medium includes a stored program, wherein when the program is run, the device where the computer-readable storage medium is located is controlled to execute the mass spectrometer stability determination method described in any one of claims 1 to 12 or the trace element analyzer detection limit performance test method described in any one of claims 13 to 21.

25. An electronic device, wherein: include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, and the one or more programs include methods for executing the mass spectrometer stability determination method described in any one of claims 1 to 12 or the trace element analyzer detection limit performance test method described in any one of claims 13 to 21.

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