Metabolic chamber and method for assessing gas concentrations thereof

Abstract

The application discloses a metabolic cabin, comprising a cabin body, a tangential fan arranged in the cabin body, the tangential fan being used for mixing the gas in the cabin body, a gas collecting system arranged at an exhaust port of the cabin body and used for collecting sample gas in the cabin body, and a gas detecting system connected with the gas collecting system, so that the sample gas can be transported into the gas detecting system and detected. The gas in the cabin body is continuously stirred by the tangential fan, so that the cabin air is fully mixed before being sampled by the detecting system, and the accuracy of detection is ensured. The application also discloses a metabolic cabin gas concentration evaluation method.

Description

Technical Field

[0001] This invention relates to the field of gas concentration assessment technology, specifically to a metabolic chamber and a method for assessing gas concentration therein. Background Technology

[0002] Accurate measurement of human energy expenditure (EE) is crucial for studying various questions related to how humans achieve or fail to achieve energy balance. One of the most accurate techniques available for measuring EE is the medical metabolic chamber, which uses indirect calorimetry. This chamber measures human metabolic expenditure by measuring oxygen consumption and carbon dioxide production within the chamber, calculating energy expenditure using the Weir equation, and extrapolating the percentage of the three macronutrients consumed.

[0003] Because the metabolic chamber is relatively large (the chamber volume is usually over 30 cubic meters), the concentration change caused by the gas produced by the subject's respiration when entering the chamber is very small, and the time for the gas to diffuse evenly into the internal space of the chamber is relatively long. This results in a relatively long response time for detection using indirect calorimetry in the metabolic chamber, making the rapid calculation of gas concentration changes within the chamber particularly important.

[0004] For example, our patent application No. 202211695112.4, filed on December 28, 2022, describes an algorithm for noise suppression and trend recognition of gas concentration changes in a chamber. This algorithm can estimate the portion of gas diffused in the chamber that is not detected by oxygen or carbon dioxide concentration sensors, and achieve rapid response to changes in gas concentration within the chamber, as well as noise suppression. Currently, there is still a problem of not being able to accurately measure transient changes in human energy expenditure (EE). Summary of the Invention

[0005] The purpose of this invention is to address the problem that current methods cannot accurately measure transient changes in human energy expenditure (EE). To solve this problem, this application provides a metabolic chamber and a method for assessing its gas concentration. The chamber design is improved to ensure that the air inside is fully mixed before sampling by the detection system. Furthermore, the algorithm model is improved to further eliminate errors caused by electrical spike noise and the influence of random white noise on the calculation results.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a metabolic chamber, comprising:

[0007] hull;

[0008] A tangential fan, installed inside the chamber, is used to mix the gases inside the chamber;

[0009] A gas collection system, located at the exhaust port of the chamber, is used to collect sample gases inside the chamber.

[0010] A gas detection system is connected to a gas collection system so that sample gas can be delivered to the gas detection system for detection.

[0011] As one specific implementation, the gas collection system includes:

[0012] Multiple gas collecting tubes, each with the same characteristics, including shape, material, length, and diameter;

[0013] The exhaust pipe is connected to the output end of each gas collection pipe.

[0014] An exhaust fan is installed on the exhaust pipe;

[0015] A mass flow controller is installed on the exhaust pipe and is located upstream of the exhaust fan; the sample gas is delivered to the gas detection system through the output of the mass flow controller.

[0016] The return air duct is connected at one end to the exhaust pipe, and the connection point between the return air duct and the exhaust pipe is located upstream of the mass flow controller; the other end of the return air duct is connected to the cabin.

[0017] An exhaust fan is installed on the return air duct.

[0018] As one specific implementation, the gas collecting pipe is made of polyethylene.

[0019] As one specific implementation, the gas detection system comprises: a CO2 detection unit, including a four-way valve and a CO2 filter. The CO2 analyzer allows sample gas, standard gas, and ambient gas to be introduced into the CO2 filter through a four-way valve.

[0020] The O2 detection unit includes an O2 filter, an O2 analyzer, and an ambient gas channel connected to the O2 filter.

[0021] The condenser has its inlet connected to both a CO2 filter and an O2 filter.

[0022] The dryer has its input end connected to the output end of the condenser, and the output end of the dryer is connected to the CO2 analyzer and the O2 analyzer respectively, so that the standard gas, sample gas and ambient gas can be passed into the CO2 analyzer and the O2 analyzer respectively through the condenser and the dryer.

[0023] Electronic equipment, which is connected to the CO2 analyzer and the O2 analyzer for data exchange, and is electrically connected to the exhaust fan and the tangential fan.

[0024] This application also discloses a method for assessing gas concentration in a metabolic chamber, wherein the metabolic chamber is based on the above-mentioned metabolic chamber, and the method for assessing gas concentration in a metabolic chamber includes the following steps:

[0025] Set the various condition parameters of the chamber to bring it to the test state. The condition parameters include: the flow rate of the exhaust fan, the flow rate of the extraction fan, the flow rate of the gas entering the metabolic chamber inlet, the flow rate of the tangential fan, as well as temperature, pressure and humidity.

[0026] For the test personnel in the test chamber, sample gases related to them are collected from the chamber, and multiple sets of relevant experimental data are collected according to the set sampling period;

[0027] The collected experimental data were preprocessed separately, and the average value of the preprocessed experimental data was obtained separately.

[0028] A moving average model is built using the average value, and the relevant moving average value is obtained through the moving average model.

[0029] The rate of change of gas concentration is obtained by using the moving average and the law of conservation of mass.

[0030] As a specific implementation method, the collected experimental data are preprocessed, including obtaining the total average value of all data collected in each group corresponding to one needle sampling period, and removing data in the group that are greater than twice the total average value.

[0031] As a specific implementation method, the moving average model is as follows:

[0032] ;

[0033] Reduced to the Items, total indivual;

[0034] Where p is an even number, for Where k = 1, 2, 3…; This represents the average of multiple sets of experimental data after preprocessing. This is the set of averages of multiple preprocessed experimental data sets, where n = 1, 2, 3…; according to , measurement Fluctuating around the actual gas concentration Used to reflect the changing trend of gas concentration inside the cabin.

[0035] As one specific implementation method, the rate of change of gas concentration is obtained using a moving average and the law of conservation of mass, including:

[0036] The obtained Dk Substituting the values ​​into the law of conservation of mass, we obtain the rate of change in the gas consumed by the test personnel during the measurement period; the law of conservation of mass is:

[0037] ;

[0038] in, It is the product of the cabin outlet flow rate (L / s) and the outlet gas concentration (%). It is the product of the inlet flow rate (L / s) and the inlet gas concentration (%). It is the rate of change of gas concentration, used to express the trend of gas concentration change inside the chamber, and the unit is % / s; This refers to the volume of the cabin, in liters (L). It refers to time, measured in seconds (s).

[0039] As one specific implementation method, the metabolic chamber gas concentration assessment method also includes verifying the accuracy of the gas concentration change rate calculation by burning propane gas in the metabolic chamber.

[0040] As one specific implementation method, the sampling frequency for collecting sample gas is 60 Hz / s.

[0041] As one specific embodiment, the purity of the propane gas is 99.0%.

[0042] Compared with the prior art, the beneficial effects of the present invention are:

[0043] 1) This invention incorporates a tangential fan inside the chamber to continuously agitate the gas inside, ensuring uniform mixing and guaranteeing thorough mixing before sampling by the gas detection system. Additionally, a return air duct with an exhaust fan ensures a relatively stable total flow rate across multiple gas collection pipes, and a stable measurement environment helps reduce errors.

[0044] 2) This invention can first merge and reduce a large amount of data through preprocessing of sample data, thereby improving the efficiency of subsequent calculations. Furthermore, it uses calculated averages to remove data points with errors caused by lighting, motors, and compressors, and then uses the calculated averages to evaluate the removed data, further eliminating errors caused by electrical spike noise.

[0045] 3) The present invention reduces the influence of random white noise on the calculation results by calculating the moving average between data points through the designed calculation model, and can be used for research on the role of acute changes in human energy consumption (EE) in daily energy balance.

[0046] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the metabolic chamber structure according to an embodiment of the present invention;

[0049] Figure 2 This is a flowchart of the gas concentration assessment method steps according to an embodiment of the present invention;

[0050] Figure 3 This is a line graph showing the removal of outliers according to an embodiment of the present invention;

[0051] Figure 4 A line graph is calculated for the moving average value in this embodiment of the invention.

[0052] Figure 5 This is a line graph of data points obtained from the propane combustion experiment in an embodiment of the present invention; wherein, Figure 5-1 This refers to data obtained after hardware modifications but before the application of any signal processing methods; Figure 5-2 The data obtained after implementing the autoregressive moving average model; Figure 5-3 This is the data obtained after all system modifications are completed.

[0053] In the picture:

[0054] 10-Carrier, 11-Carrier air inlet, 12-Tangential fan, 13-Gas collection system, 131-Gas collection pipe, 132-Exhaust pipe, 133-Exhaust fan, 134-Mass flow controller, 135-Return air pipe, 136-Exhaust fan, 20-Gas detection system, 21-CO2 detection unit, 211-Four-way valve, 212-CO2 filter, 213-CO2 extraction pump, 214-CO2 flow meter, 215-CO2 analyzer, 22-O2 detection unit, 221-O2 filter, 222-O2 extraction pump, 223-O2 flow meter, 224-O2 analyzer, 23-Condenser, 24-Dryer, 25-Electronic equipment. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] The inventors discovered through research that the main problem with using a medical metabolic chamber to assess the dynamic changes in human energy expenditure (EE) is the oxygen consumption (VO2) related to the chamber size. To accurately measure transient changes in human energy expenditure (EE), efforts must be made to significantly reduce measurement errors caused by gas analyzers, ensure that the indoor air is thoroughly mixed before being sampled by the analyzer, and further eliminate errors caused by electrical spike noise and the influence of random white noise on the calculation results.

[0057] Reference Figure 1 This invention provides a metabolic chamber, including a chamber body 10 and a gas detection system 20 for detecting sample gas inside the chamber body 10. The chamber body 10 is provided with an air inlet and an air outlet, and an air inlet fan (not shown in the figure) is provided at the air inlet. A tangential fan 12 is provided inside the chamber body 10 to continuously agitate the gas inside the chamber body 10, ensuring uniform mixing of the gas. Exemplarily, multiple sets of tangential fans 12 are provided and installed on the side wall of the chamber body 10.

[0058] A gas collection system 13 is installed at the exhaust port of the chamber 10 to collect sample gas, which is used to systematically deliver the gas exhaled by the test subject to the gas detection system 20. (Continue referring to...) Figure 1 The gas collection system 13 includes multiple gas collection pipes 131. Exemplarily, the gas collection pipes 131 are flexible polyethylene pipes with the same geometry, and the inlet ends of the multiple gas collection pipes 131 are arranged in an equidistant circular pattern and connected to the interior of the cabin 10. The outlet ends of the multiple gas collection pipes 131 are centrally connected to an exhaust pipe 132 for exhausting gas. Exemplarily, the exhaust pipe 132 is made of PVC.

[0059] An exhaust fan 133 is installed at the output end of the exhaust pipe 132 to draw gas from the chamber 10. A mass flow controller 134 is installed on the exhaust pipe, and the mass flow controller 134 is located upstream of the exhaust fan 133. The output end of the mass flow controller 134 is connected to the gas detection system 20 through a delivery branch pipe, and is used to deliver the sample gas from the chamber 10 to the gas detection system 20.

[0060] A return air duct 135 is also connected to the exhaust pipe 132. One end of the return air duct 135 is connected to the exhaust pipe 132 upstream of the mass flow controller 134, and the other end of the return air duct 135 is connected to the interior of the chamber 10. An exhaust fan 136 is installed on the return air duct 135. By controlling the exhaust fan 136, some of the gas in the exhaust pipe 132 can be returned to the interior of the metabolic chamber. When the flow rate of the exhaust fan 133 increases, the flow rate of the exhaust fan 136 can be increased proportionally, and vice versa, thereby ensuring that the total flow rate of the gas collected by the multiple gas collection pipes 131 remains relatively stable. A stable measurement environment helps to reduce errors.

[0061] Since the multiple gas collecting tubes 131 are made of the same material, have the same length and diameter, the air resistance of each gas collecting tube 131 is the same, and therefore the flow rate through each gas collecting tube 131 is also the same. The time delay from the free end of the multiple gas collecting tubes 131 to the gas detection system 20 is also the same for each tube, so the system delay is shorter and less variable.

[0062] Continue to refer to Figure 1 The gas detection system 20 consists of a CO2 detection unit 21, an O2 detection unit 22, a standard gas, and an electronic device 25.

[0063] The CO2 detection unit 21 includes a four-way valve 211, a CO2 analyzer 215, a CO2 flow meter 214, a CO2 pump 213, CO2 filters 221 and 212, a dryer 24, and a condenser 23.

[0064] The O2 detection unit 22 includes an O2 analyzer 224, an O2 flow meter 223, an O2 pump 222, an O2 filter 221, and a dryer 24 and a condenser 23 shared with the CO2 detection unit 21.

[0065] Sample gas and standard gas are connected to the input of four-way valve 211. The CO2 analyzer 215 and O2 analyzer 224 are calibrated by introducing the standard gas to reduce drift error. Fresh air is connected to the filter in CO2 detection unit 21 via a branch pipe to the input of four-way valve 211, and the output of four-way valve 211 is connected to the filter in CO2 detection unit 21. The ambient gas channel is directly connected to the filter in O2 detection unit 22.

[0066] In the CO2 detection gas path, CO2 filters 221 and 212 are connected to CO2 extraction pump 213. In the O2 detection unit 22, O2 filter 221 is connected to O2 extraction pump 222. CO2 extraction pump 213 and O2 extraction pump 222 are connected to the two input terminals of a shared condenser 23. The two output terminals of the condenser 23 are connected to the two input terminals of a shared dryer 24. The two input terminals of the dryer 24 are respectively connected to CO2 flow meter 214 and O2 flow meter 223. CO2 flow meter 214 and O2 flow meter 223 are respectively connected to the input terminals of CO2 analyzer 215 and O2 analyzer 224, so that standard gas, sample gas, or ambient gas can be simultaneously introduced into CO2 analyzer 215 and O2 analyzer 224. That is, when the introduced gas is sample gas, CO2 and O2 in the sample gas can be detected simultaneously. The data ports of CO2 analyzer 215 and O2 analyzer 224 are connected to electronic device 25, which can control exhaust fan 136 and tangential fan 12.

[0067] When the gas detection system 20 performs detection, it switches via the four-way valve 211 to first introduce standard gas to flush and calibrate the measuring instruments (such as CO2 analyzer 215 and O2 analyzer 224) to reduce drift errors. Then, only sample gas is introduced for detection. After the sample gas detection is complete, standard gas is introduced again for calibration. Next, ambient gas is introduced for detection to measure the concentrations of oxygen and carbon dioxide in the ambient gas. Finally, standard gas is introduced again to calibrate the measuring instruments.

[0068] The gas exchange of a subject in a medical metabolic process (closed chamber) is calculated based on the law of conservation of mass. For any gas (G) to be measured, the rate of change of the amount of gas breathed by the test subject is (G / G). )for:

[0069]

[0070] in, It is the product of the cabin outlet flow rate (L / s) and the outlet gas concentration (%). It is the product of the inlet flow rate (L / s) and the inlet gas concentration (%). It is the rate of change of gas concentration, reflecting the trend of gas concentration change inside the chamber, and the unit is % / s; This refers to the volume of the cabin, in liters (L). This refers to time, measured in seconds (s). Flow rate and volume need to be converted to standard state (STPD). It is assumed here that the indoor air is sufficiently mixed before being exhausted; therefore... It also represents the indoor gas concentration.

[0071] The first term in equation (1) Second item This is expressed as the change in gas volume at the cabin's outlet and the change in gas volume at the cabin's inlet, with the last item representing the change. This represents the net change in gas volume within the chamber per unit time. In the last term, if no large volume of additional objects are introduced into or removed from the chamber, and no significant environmental changes (temperature T, air pressure P, or humidity Rh) occur, then V can be assumed to be a constant during the measurement period. This is obtained by measuring the gas concentration at the beginning and end of a measurement cycle (e.g., 1 minute) and dividing the difference by the cycle. Calculations can demonstrate that, when frequent measurements are taken to detect rapid changes in EE, This limits the accuracy of the measurement.

[0072] Based on this, the present invention provides a method for assessing gas concentration in a metabolic chamber. Please refer to [link / reference]. Figure 2 The steps are as follows:

[0073] Step S1: Setting initial conditions: Set the flow rate Ve of the exhaust fan on the exhaust pipe of the metabolic chamber, the flow rate Vb of the exhaust fan on the return air pipe, the flow rate Vi of the gas entering through the intake port of the metabolic chamber, and the flow rate Vp of the tangential fan. Specifically, the mixing and circulation of gas in the chamber can be adjusted by the coordination between the fans.

[0074] Since the subjects have minimal impact on the environmental factors inside the chamber, other conditions inside the chamber are assumed to be constant. That is, environmental factors such as pressure P, temperature T, and humidity Rh inside the metabolic chamber are set to be constant. For example, the experiment was conducted at room temperature (25°C), normal pressure (one atmosphere), and constant humidity (50%).

[0075] Step S2: Data Acquisition: The experimenter enters the metabolic chamber where the initial conditions were set in Step S1. The sampling time period is t, and the sampling frequency is 60Hz / s (i.e., 60 sample data points are collected per second). The collected sample data is transmitted to the electronic device.

[0076] Step S3: Preprocessing of sample data: The average SD is important for evaluating the accuracy of short-term measurements. On the other hand, when the average SD is quite large, it indicates that the system noise is quite high for short-term measurement types. Therefore, the average SD can be used to characterize the change in error and as a standard for judging noise reduction.

[0077] A large number of data points (N) will produce more accurate data, but will require more sampling and computation time because N determines the sampling interval. This scheme uses N=300 data points (i.e., 5-second intervals) to calculate the average value SDi (i=1, 2, 3…), which can aggregate the data collected in step S2 into a single data point at 5-second intervals, thereby reducing the time for post-processing data and improving the efficiency of the inspection. To further eliminate errors caused by electrical spike noise, such as those caused by lights, motors, and compressors, the original data is checked again by a program on the electronic device, and outliers with values ​​>2SDi (e.g., ...) are removed from the 300 data points in each 5-second interval. Figure 3 The image shown is a line chart of one set of data after outlier removal. After outlier removal, the average of the remaining dataset is calculated again, thus obtaining a series of new averages corresponding to the processed dataset. .

[0078] The result calculated using the above method can make the average value The noise frequency is uniformly distributed over a wide range without any obvious peaks, ensuring that the main periodic interference of the system has been eliminated and the remaining errors are close to random white noise.

[0079] Step S4: Establishing the calculation model: Based on step S3, a series of average values ​​can be calculated. Let the average of this series The set is Where n = 1, 2, 3, ..., let for ( Let k be the gas concentration change trend (where k = 1, 2, 3…); Based on the approximate linearity of the gas concentration change trend over a short period, then the gas concentration change trend D… k It can be obtained by the difference between two points at a fixed distance, i.e. , measurement Fluctuating around the concentration of real gases (such as O2), the above The gas concentration at the current point. This represents the gas concentration at the next point after a fixed interval.

[0080] therefore, The calculation model can be derived by considering the fluctuations around the actual O2 concentration differences:

[0081]

[0082] Reduced to the Items, total indivual;

[0083] Where p is an even number, Similar to the center using the previous method around Moving average of values; moving average The value is obtained through calculation. ,Right now The value reflects the trend of gas concentration changes inside the cabin; therefore, the moving average... The value process effectively eliminates these errors.

[0084] Another advantage is that computational errors do not propagate: by summing the results of each computation cycle, it is easy to find the VO2 value with a longer cycle; the longer the cycle, the more accurate the result.

[0085] For example, the calculation period is 30 seconds (e.g.) Figure 4 As shown), then p=6 and from equation (2) we can obtain

[0086] ;

[0087] ;

[0088] ;

[0089] D1 reflects the rate of change in oxygen concentration during the first 30-second period. 1. D2 reflects the rate of change in oxygen concentration during the second 30-second period. 2. Thus, the rate of change in oxygen concentration for the first 60-second cycle can be obtained as D1 + D2. And so on, through... The sum can be used to find the rate of change of oxygen concentration for any 1-minute period. ;

[0090] For example, a 60-second period is... ;

[0091] For example, a 90-second period is... ;

[0092] The calculated D k Value (i.e., the rate of change of oxygen concentration during the measurement period) Substituting the value of % / s into formula (1), we can calculate the rate of change of oxygen consumption by the test personnel during the measurement period, VO2, with the unit being L / s. Similarly, we can calculate the rate of change of carbon dioxide production by the test personnel during the measurement period, VCO2.

[0093] Step S5: Validation experiment of the calculation model: In order to verify the accuracy of the gas concentration change rates VO2 and VCO2 calculated in step S4, based on the characteristics that the oxygen consumption and carbon dioxide production rates of the combustion experiment are relatively stable and measurable, propane gas was burned in the metabolic chamber for experimental verification.

[0094] The chemical reaction formula for the combustion of propane gas is as follows:

[0095] C3H8+5O2→3CO2+4H2O (3)

[0096] Take a 5L propane gas combustion bottle and burn it inside the metabolic chamber in step S1 to simulate the CO2 gas produced by human respiration and the O2 gas consumed. During the combustion process, the propane gas combustion bottle is placed on a precision scale weighing table. The actual VO2 of propane gas is calculated using formula (3), and compared with the VO2 detected by the metabolic chamber calculated using formula (2) in step S4.

[0097] Step S6: Analysis and conclusion of experimental results: The performance of the improved metabolic chamber was evaluated by conducting three propane gas combustion experiments in Step S5. All measurements were performed at 1-minute intervals, and the average test duration was 300 ± 10 minutes.

[0098] Prior to the hardware modifications and signal processing techniques described earlier, the measured data was extremely noisy, and the signal from the propane gas test was almost invisible within a 1-minute interval. The effects of the hardware modifications and signal processing were as follows: Figure 5 The figure shown is a line graph of data points obtained from three propane gas combustion experiments. Among them,

[0099] Figure 5 5-1 represents data obtained after hardware modifications but before the application of any signal processing methods;

[0100] Figure 5 Figure 5-2 shows the data obtained after implementing the autoregressive moving average model;

[0101] Figure 5 Figure 5-3 shows the data obtained after all system modifications were completed.

[0102] In this experiment, the average percentage of the calculated rate of change of oxygen consumption VO2 to the actual rate of change of oxygen consumption VO2 was 97.29 ± 0.93% (n=15).

[0103] Since the combustion of propane gas cannot be 100% complete, the purity of propane gas is 99.0%. Considering the 1% purity loss of propane gas and incomplete combustion (0.5-1.5%), the measured VO2 is approximately 99.3% of the actual VO2 value. Based on the calculated percentage average SD in VO2, it can be concluded that the error of EE measurement is within 2.0%, with a confidence level ≥95%.

[0104] In summary, the technical solution of this application embodiment can accurately measure human energy expenditure (EE) within 1 minute in subjects moving freely in a metabolic chamber, and the system can be used to study the role of acute changes in human energy expenditure (EE) in daily energy balance.

[0105] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0106] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method of metabolic chamber gas concentration assessment, comprising: The metabolic cabin comprises a cabin body, a tangential fan, a gas collection system and a gas detection system; The tangential fan is arranged in the cabin body and is used for mixing the gas in the cabin body; The gas collection system is arranged at the exhaust port of the cabin body and is used for collecting sample gas in the cabin body; The gas detection system is connected with the gas collection system, so that the sample gas can be transported into the gas detection system and detected; The gas collection system comprises a plurality of gas collection pipes and an exhaust pipe; An exhaust fan is arranged on the exhaust pipe; A mass flow controller is arranged on the exhaust pipe; A return air pipe is connected with the exhaust pipe at one end; An air extraction fan is arranged on the return air pipe; The metabolic cabin gas concentration evaluation method comprises the following steps: Setting condition parameters of the cabin body to make the cabin body reach a test state, wherein the condition parameters comprise a flow rate of the exhaust fan, a flow rate of the air extraction fan, a flow rate of inlet gas of the metabolic cabin, a flow rate of the tangential fan, and temperature, pressure and humidity; Collecting sample gas related to a test person in the cabin body in the test state, and collecting a plurality of groups of related experimental data according to a set sampling period; Preprocessing the collected plurality of groups of experimental data respectively, and obtaining average values of the preprocessed plurality of groups of experimental data respectively; Using the average values to establish a moving average value model, and obtaining related moving average values through the moving average value model; Using the moving average values and a mass conservation law equation to obtain a gas concentration change rate; The moving average value model is as follows: ， to the 1st items, a total of items; wherein p is an even number, is wherein k = 1, 2, 3,...; is the average value of a plurality of sets of the experimental data after preprocessing, is a set of average values of a plurality of sets of the experimental data after preprocessing, wherein n = 1, 2, 3,...; according to , the measured fluctuates around the actual gas concentration, the value is used to reflect the change trend of the gas concentration in the cabin; The use of the moving average values and the mass conservation law equation to obtain the gas concentration change rate comprises, The obtained D k The value is substituted into the mass conservation law equation to obtain the change rate of the test person's consumed gas within the measurement period; the mass conservation law equation is: ， wherein, is the rate of change of the volume of respiratory gas of the test person, is the product of the outlet flow (L / s) and the outlet gas concentration (%), is the product of the inlet flow (L / s) and the inlet gas concentration (%), is the rate of change of the gas concentration, which indicates the trend of the change in the gas concentration in the cabin, in % / s; is the volume of the cabin, in L; is the time, in s.

2. The metabolic chamber gas concentration assessment method of claim 1 wherein, The preprocessing of the collected plurality of groups of experimental data respectively comprises that each group of data corresponds to all data collected in a sampling period, a total average value of all data of the group is obtained, and data greater than twice the total average value in the group are removed.

3. The metabolic chamber gas concentration assessment method of claim 1 wherein, The metabolic cabin gas concentration evaluation method further comprises verifying the accuracy of the calculation of the gas concentration change rate by burning propane gas in the metabolic cabin.

4. The metabolic chamber gas concentration assessment method of claim 1, wherein, The sampling frequency of the sample gas collection is 60 Hz / s.

5. A metabolic chamber for carrying out the method of assessing the gas concentration of a metabolic chamber according to any one of claims 1 to 4, characterized in that The features of each gas collection pipe are the same, and the features comprise shape, material, length and diameter; The output ends of each gas collection pipe are in communication with the exhaust pipe; The mass flow controller is located upstream of the exhaust fan; the sample gas is transported into the gas detection system through the output end of the mass flow controller; The one end of the return air pipe is connected with the exhaust pipe upstream of the mass flow controller; and the other end of the return air pipe is in communication with the cabin body.

6. The metabolic chamber of claim 5, wherein, The material of the gas collection pipe is polyethylene.

7. The metabolic chamber of claim 5, wherein, The gas detection system comprises a CO2 detection unit, a four-way valve, a CO2 filter and a CO2 analyzer; the sample gas, standard gas and ambient gas can pass through the four-way valve and enter the CO2 filter; An O2 detection unit, comprising an O2 filter, an O2 analyzer, and an ambient gas channel connected to the O2 filter; A condenser, with input ends connected to the CO2 filter and the O2 filter respectively; A dryer, with an input end connected to an output end of the condenser, and with output ends connected to the CO2 analyzer and the O2 analyzer respectively, so that the standard gas, the sample gas, and the ambient gas can pass through the condenser and the dryer and be introduced into the CO2 analyzer and the O2 analyzer respectively; An electronic device, in data connection with the CO2 analyzer and the O2 analyzer, and in electrical connection with the air suction fan and the tangential fan.

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