CN116222870A - Dry powder tank car tank body and monitoring system thereof - Google Patents
Dry powder tank car tank body and monitoring system thereof Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65D—CONTAINERS FOR STORAGE OR TRANSPORT OF ARTICLES OR MATERIALS, e.g. BAGS, BARRELS, BOTTLES, BOXES, CANS, CARTONS, CRATES, DRUMS, JARS, TANKS, HOPPERS, FORWARDING CONTAINERS; ACCESSORIES, CLOSURES, OR FITTINGS THEREFOR; PACKAGING ELEMENTS; PACKAGES
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Abstract
The invention relates to the technical field of electronic digital data processing, in particular to a dry powder tank car tank body and a monitoring system thereof, which comprises the following components: segmenting the gas pressure data and the vibration intensity data according to the vibration intensity data, obtaining the abnormality degree of the gas pressure data according to the degree that the gas pressure data exceeds the normal gas pressure, obtaining the deviation degree according to whether the fluctuation condition of the gas pressure data in the segments corresponds to the influence relation of the vibration intensity data, obtaining the corresponding adjustment parameters of each gas pressure data, and performing fitting parameter adjustment when performing least square fitting on each gas pressure data. The fitting curve of the gas pressure data can represent the actual change of the gas pressure in the tank body, reduces the error of the gas pressure change caused by tank body vibration, and simultaneously increases the robustness of curve fitting.
Description
Technical Field
The invention relates to the technical field of electronic digital data processing, in particular to a dry powder tank car tank body and a monitoring system thereof.
Background
After the dry powder tank truck is loaded with the goods, the pressure in the tank body loaded at the rear of the truck is high, when the pressure in the tank body is abnormally high and even exceeds the bearing range of the tank body, the serious risk is brought to the moment, so that the pressure in the tank body needs to be monitored at any time by placing a pressure sensor in the tank body, and whether the pressure in the tank body is normal or not is mastered;
when pressure data in the tank body of the existing tank truck is monitored, the pressure data is subjected to least square curve fitting to obtain the variation trend of the pressure data, and then whether abnormal growth occurs in the tank body is judged. However, the tank truck can generate a bump phenomenon in the running process, so that the pressure data is fluctuated, the trend after fitting is higher, and misjudgment is caused, but the fluctuation is actually normal fluctuation, and therefore the invention optimizes the problems.
Disclosure of Invention
The invention provides a dry powder tank car tank body and a monitoring system thereof, which aim to solve the existing problems.
The invention relates to a dry powder tank car tank body and a monitoring system thereof, which adopts the following technical scheme:
the invention provides a monitoring system of a dry powder tank car body, which comprises the following modules:
and a data acquisition module: acquiring vibration intensity data of the inner part of a tank body of the tank truck and gas pressure data at a plurality of positions;
and a data preprocessing module: smoothing and denoising all the gas pressure data and the vibration intensity data, taking the corresponding moment of a data point with the vibration intensity larger than a preset vibration intensity threshold value as a segmentation point, and respectively marking one section of vibration intensity data and one section of gas pressure data contained by two adjacent segmentation points as a vibration intensity data section and a gas pressure data section;
and a data analysis module: the corresponding gas pressure at the initial time in the gas pressure data is recorded as a pressure reference value, and the pressure abnormality degree is obtained according to the difference between the average value of the gas pressure data at any time and the pressure reference value;
carrying out data decomposition on all the vibration intensity data segments to obtain a plurality of IMF vibration intensity components, and recording the time interval between the maximum value of the vibration intensity component in any IMF vibration intensity component and other vibration intensity components as a time interval; obtaining the actual influence degree according to the fusion result of the vibration intensity component and the time interval;
acquiring a standard deviation of the actual influence degree of the IMF vibration intensity component at any time; acquiring a difference value between the gas pressure data and the minimum gas pressure data, recording the difference value as a change amplitude, counting all the change amplitude values, recording the difference between the gas pressure integral change value and the vibration intensity data as a deviation degree factor, and regulating the standard deviation of the deviation degree factor by using the standard deviation of the actual influence degree to obtain the deviation degree;
and a data fitting and adjusting module: the deviation degree is used for adjusting the abnormal pressure degree to obtain fitting adjustment parameters, the gas pressure data is subjected to curve fitting by using a least square method to obtain fitting data, and the fitting data is adjusted by using the fitting adjustment parameters to obtain adjusted fitting data;
the air pressure early warning module: and realizing air pressure early warning according to the size of the adjusted fitting data.
Further, the pressure abnormality degree is obtained by the following steps:
obtaining the pressure abnormality degree at the t-th moment according to the pressure reference value and the gas pressure data
：
Wherein S represents a pressure reference value,
characterization of the first embodiment
The air pressure sensor is at the first
The gas pressure obtained at the moment, I represents the number of the gas pressure sensors,
a logarithmic function based on a natural constant is represented.
Further, the actual influence degree is obtained by the following steps:
carrying out data decomposition on each vibration intensity data segment of the vibration intensity data by using an EMD modal decomposition algorithm, and marking an IMF (inertial measurement unit) component obtained by decomposition as an IMF vibration intensity component, wherein each IMF vibration intensity component corresponds to a component value of vibration intensity at any time and is marked as a vibration intensity component;
recording the time interval between the maximum value of the vibration intensity component in any one vibration intensity data segment and the vibration intensity component corresponding to other moments in any one IMF vibration intensity component as the time interval;
the corresponding vibration intensity component in the mth IMF vibration intensity component in any vibration intensity data section has actual influence degree on the gas pressure data at the t moment
The method comprises the following steps:
wherein ,
representing the mth IMF vibration intensity component
The magnitude of the vibration intensity component corresponding to the moment,
representing the time interval of the t-th vibration intensity component among the m-th IMF vibration intensity components,
representing a linear normalization function.
Further, the deviation degree is obtained by the following steps:
in any gas pressure data segment, whether the gas pressure data deviate from the degree W of intensity change of vibration intensity data or not:
wherein ,
a standard deviation indicating the actual degree of influence at time t,
indicating the normalized gas pressure overall change value at the t-th time,
the normalized numerical value representing the vibration intensity data at the time t,
representing the average of the absolute values of the differences of all normalized gas pressure overall change values and the vibration intensity data, T representing the number of times contained in the corresponding gas pressure data segment,
representing a linear normalization function.
Further, the method for realizing the air pressure early warning according to the size of the adjusted fitting data specifically comprises the following steps:
and performing curve fitting on the gas pressure data according to the corrected least square method, so as to obtain a fitting curve of the actual gas pressure data, judging whether the pressure in the tank body of the dry powder tank truck is dangerous or not according to the data size in the fitting curve by setting a gas pressure threshold in advance, and performing air pressure early warning when the data in the fitting curve is larger than a preset gas pressure threshold.
The invention provides a dry powder tank truck tank body, which specifically comprises the following devices: the cylinder is used for loading dry powder materials, the feeding port is used for filling the dry powder materials into the cylinder, the discharging port is used for discharging the dry powder materials in the cylinder, the air pressure sensors are uniformly arranged at a plurality of positions in the cylinder and used for acquiring air pressure data at different positions, the vibration sensor is arranged at the bottom of the cylinder and used for acquiring vibration intensity data of the cylinder, and a processor connected with the air pressure sensors and the vibration sensor is used for analyzing the acquired air pressure data and vibration intensity data, wherein the processor comprises any monitoring system.
The technical scheme of the invention has the beneficial effects that: after the acquired vibration signals and pressure data are segmented, the difference between the fluctuation of the pressure data in each segment and the corresponding actual vibration influence is taken as an abnormal degree, the degree of the fluctuation of the pressure data in each segment exceeding a normal value is taken as an abnormal degree, the weight of each data when the least square curve fitting is carried out is obtained, the actual pressure change can be represented by the fitted trend, the trend deviation error caused by tank fluctuation is reduced, and meanwhile, the robustness of the trend fitting is increased.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a block flow diagram of a monitoring system for a dry powder tank truck tank according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of a dry powder tank truck tank body and a monitoring system thereof according to the invention, and the detailed implementation, structure, characteristics and effects thereof are as follows. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a dry powder tank truck tank body and a specific scheme of a monitoring system thereof, which are specifically described below with reference to the accompanying drawings.
Referring to fig. 1, a block flow diagram of a monitoring system for a tank of a dry powder tank truck according to an embodiment of the present invention is shown, where the system includes the following blocks:
and a data acquisition module: acquiring vibration intensity data of the inner part of a tank body of the tank truck and gas pressure data at a plurality of positions;
the method comprises the steps that an air pressure sensor and a vibration sensor are arranged in a tank body of a dry powder tank truck, air pressure monitoring in a local range is carried out through an air pressure sensing module in the air pressure sensor, and meanwhile, the air pressure sensors are arranged at a plurality of positions of the tank body because the monitoring is only in the local range, the air pressure sensors are uniformly arranged in the tank body of the tank truck, so that air pressure data in all ranges in the tank body can be obtained as far as possible, and the air pressure data are recorded;
meanwhile, a vibration sensor is arranged right below the tank body, data of vibration intensity received by the tank body in the whole transportation process are collected, vibration intensity data are obtained, and meanwhile, the data of the air pressure sensor and the data of the vibration sensor are guaranteed to correspond to each other in a time sequence;
in addition, after the installation of the air pressure sensor and the vibration sensor is completed, the corresponding air pressure at the initial moment in the air pressure data is recorded as a pressure reference value S;
when the pressure reference value is the pressure inside the tank body measured by the installed pressure sensor before the tank truck starts, the pressure is equal everywhere, so that the pressure reference value is only one and is irrelevant to the number of the sensors.
To this end, pressure reference value, vibration intensity data, and gas pressure data of a plurality of positions inside the tank are obtained.
And a data preprocessing module: and carrying out data segmentation on the gas pressure data and the vibration intensity data according to the vibration intensity.
Due to environmental reasons, certain noise exists in the gas pressure data and the vibration intensity data, wherein the noise part also affects the subsequent data analysis and the fitting effect, and in the embodiment, through mean value filtering, all the gas pressure data and the vibration intensity data are subjected to smooth denoising, fine fluctuation in the data is removed, and the denoised gas pressure data and vibration intensity data are used as the gas pressure data and the vibration intensity data in subsequent analysis processing.
In addition, in the transportation process of the tank truck loaded with the dry powder cargoes, real-time detection needs to be carried out on the pressure in the tank body, and the pressure data is usually time sequence data which continuously fluctuates up and down, so that least square curve fitting is usually needed to obtain the change trend of the whole pressure data, and further whether the pressure data has abnormal increase or decrease trend change is analyzed. However, in the running process of the vehicle, the vehicle body continuously vibrates in a large time and a small time because of the bumping degree of the road surface, so that abnormal fluctuation occurs corresponding to the pressure in the local range monitored by the air pressure sensor in the tank body, when curve fitting is performed, the fitting result of the whole trend is influenced, and the obtained curve fitted to the air pressure change trend cannot accurately and stably reflect the actual change condition of the pressure in the tank body, so that whether the air pressure is overlarge or not is influenced.
Therefore, in the embodiment, through carrying out data fluctuation analysis on the gas pressure data in the local range acquired by a plurality of positions in the tank body, analyzing fluctuation conditions in the gas pressure data in combination with vibration intensity data, quantifying the normal fluctuation data of the gas pressure caused by tank body vibration, analyzing the quantification result to obtain the adjustment parameters for carrying out curve fitting on the gas pressure data, recording the adjustment parameters as the fitting adjustment parameters, and setting weight values when carrying out least square curve fitting according to the fitting adjustment parameters, so that the fitted gas pressure change curve can represent the actual gas pressure data change trend in the tank body as far as possible, and reduce the influence of the data fluctuation caused by tank body vibration on the overall trend;
when the air pressure in the tank body changes, besides the condition that the pressure is abnormal due to the temperature in the tank body, the dry powder in the tank body vibrates along with the vibration of the tank body, so that the local gas volume changes, the gas pressure changes in a local range, and the estimation of the integral pressure change condition in the tank body is influenced.
Therefore, according to the influence of tank vibration on the pressure inside the tank, in the embodiment, the acquired gas pressure data and vibration intensity data are processed in a segmentation way by taking the moment corresponding to the data point with larger vibration intensity in the vibration intensity data as the segmentation point.
And judging whether the vibration intensity corresponding to the data point at each moment in the vibration intensity data is larger than the preset vibration intensity threshold value from the first moment of the vibration intensity data according to the preset vibration intensity threshold value of the experience, taking the moment corresponding to the data point with the vibration intensity larger than the preset vibration intensity threshold value as a segmentation point to obtain a plurality of segmentation points, and respectively recording one section of vibration intensity data and gas pressure data contained by two adjacent segmentation points as a vibration intensity data section and a gas pressure data section to respectively obtain a plurality of vibration intensity data sections and a gas pressure data section.
When the tank body vibrates, the data on the vibration intensity data are not fluctuated, but after the tank body of the tank truck vibrates, the vibration intensity data still have fluctuation, the fluctuation degree is gradually weakened until the vibration intensity of the tank body is recovered to be normal, and therefore each obtained vibration intensity data segment and each obtained gas pressure data segment reflect the data change condition before the next severe vibration after the tank body vibrates severely.
And a data analysis module: for the gas pressure data acquired by a plurality of positions, certain correlation exists among the gas pressure data, namely when the gas pressure of a certain local position is reduced, the gas volume of the corresponding local position is increased, and as the volume of the tank body is unchanged, the gas volume of the other local position is reduced to a certain extent, namely the gas pressure corresponding to the local position with the reduced gas volume is increased, so that the gas pressure change condition in the whole tank body in the dry powder tank truck can fluctuate within a certain range, and the abnormal pressure degree of the whole tank body at any moment is acquired according to the gas pressure data of the plurality of positions;
in addition, the data points in the acquired gas pressure data are recorded as
Representing the gas pressure acquired by the ith gas pressure sensor at the t moment;
step (1), obtaining the pressure abnormality degree at the t-th moment according to the pressure reference value and the gas pressure data
：
Wherein S represents a pressure reference value,
characterization of the first embodiment
The air pressure sensor is at the first
The gas pressure obtained at the moment, I represents the number of the gas pressure sensors,
a logarithmic function based on a natural constant is represented.
The condition of integral pressure change in the tank body is represented by calculating the absolute value of the difference between the mean value of the gas pressure at the same moment and the pressure reference value, and when the absolute value of the difference is higher, the pressure in the tank body is higher than the reference value at the moment no matter the external influence is caused at the moment, and even if the data fluctuation is caused by the tank body vibration at the moment, the information representing the gas pressure data is still needed in the subsequent curve fitting;
it should be noted that the number of the substrates,
the function is used for reducing the degree of abnormality represented by the smaller difference, the real pressure inside the tank body can not be represented accurately only by the mean value, and normal fluctuation with a certain upper and lower amplitude can exist, so that the influence of smaller fluctuation can be weakened by the function, and the higher the difference is, the higher the increase rate of the degree of abnormality represented by the function is, so that the degree of abnormality in the larger difference is amplified simultaneously.
When the pressure intensity is abnormal
The larger the difference between the gas pressure data and the reference value is, the larger the difference is, so that in the subsequent analysis, even if the pressure data fluctuates due to the tank vibration, the gas pressure data corresponding to the degree of pressure abnormality still needs to be taken into consideration when curve fitting is performed.
And (2) decomposing the vibration intensity data to obtain a plurality of vibration intensity component data, and obtaining the actual influence degree according to the time interval between the vibration intensity component data and the data contained in the vibration intensity component data.
Tank trucks tend to bump continuously in the driving process many times, thus causing continuous vibration, each vibration can be regarded as a new vibration source, and the vibration usually occurs after the initial vibration, and is gradually attenuated instead of directly ending, so each vibration has an overlapping effect on the follow-up, then the corresponding pressure fluctuation at the same moment corresponds to the overlapping effect of a plurality of vibrations, and the degree of deviation is not considered, so if the degree of deviation is not adjusted, the obtained degree of deviation is not accurate enough when the vibration is continuously performed many times.
The intensity of each bump is reflected on the vibration signal as the difference of frequency and amplitude, so that the embodiment utilizes an EMD modal decomposition algorithm to carry out data decomposition on each vibration intensity data segment of the vibration intensity data, a plurality of IMF components and residual values are obtained after each vibration intensity data segment is decomposed, the IMF components obtained through decomposition are recorded as IMF vibration intensity components, and each IMF vibration intensity component corresponds to a component value of vibration intensity at any moment and is recorded as a vibration intensity component; it should be noted that, since no residual value is needed in the following, it is not considered here; wherein each IMF component characterizes the magnitude of the vibration intensity component at the same frequency, and the EMD mode is decomposed into existing known techniques.
In addition, the maximum value of the vibration intensity components in the mth IMF vibration intensity component in any vibration intensity data section is obtained, and the time interval between the vibration intensity components corresponding to the mth moment is recorded as the time interval of the mth vibration intensity component in the mth IMF vibration intensity component
。
The corresponding vibration intensity component in the mth IMF vibration intensity component in any vibration intensity data section has actual influence degree on the gas pressure data at the t moment
The method comprises the following steps:
wherein ,
representing the mth IMF vibration intensity component
The magnitude of the vibration intensity component corresponding to the moment,
representing the time interval of the t-th vibration intensity component among the m-th IMF vibration intensity components,
representing a linear normalization function;
the method for obtaining the actual influence degree by using the linear normalization function
The maximum and minimum values selected for the normalization process are obtained from the segment of vibration intensity data where the t-th vibration intensity component is located.
When the time interval between the maximum value of the vibration intensity component in the mth IMF vibration intensity component and the vibration intensity component corresponding to the t moment is longer, the corresponding actual influence degree corresponding to the vibration intensity component is smaller when the vibration intensity component is subsequently overlapped, and the maximum value in the IMF vibration intensity component is always a vibration source at the frequency, so that the subsequent vibration is regarded as a gradual attenuation value after the vibration of the vibration source by default.
Finally, for all IMF vibration intensity components of any one vibration intensity data segment, obtaining the standard deviation of the actual influence degree at the t-th moment, and recording the standard deviation as
The degree of dispersion of the actual influence degree is reflected when
The larger the corresponding IMF vibration intensity components representing any one of the vibration intensity data segments, the more discrete the actual influence degree, and the larger the numerical difference between the vibration intensity components, the more the corresponding vibration intensity data segments have a certain vibration as a main influence, while the rest of the vibrations have influence, but reflect the situation that the actual influence at the moment is small, and the moment can be approximately regarded as being influenced by only one vibration. The smaller the standard deviation is, the more the corresponding vibration has an average influence degree on the moment.
In this step, the abnormal data existing in the vibration intensity data is considered, that is, in order to avoid mistaking important abnormal data existing in the vibration intensity data as normal data caused by vibration, but it cannot be expressed whether the data at this time is actually caused by the vibration data, so that it is also necessary to judge whether the fluctuation change of the pressure data is caused by the vibration of the tank truck in the period in which the vibration occurs.
When vibration occurs, the pressure inside the tank body becomes unstable, the pressure inside the tank body is similar to the characteristic of continuous movement, but under the condition that the integral pressure inside the tank body is not changed, the value of the local gas pressure data acquired by a certain gas pressure sensor is increased, the corresponding local position is reduced in total quantity, so that based on the characteristic, the local gas pressure can be higher than the original integral gas pressure along with the vibration of the tank body, the integral pressure of the finally monitored vibrated gas pressure data is higher than the normal gas pressure, the value of the increased gas pressure is related to the vibration intensity at the corresponding moment, and therefore, whether the gas pressure data at the corresponding moment of vibration intensity data has the correlation characteristic is needed to be judged.
And (3) obtaining the fluctuation degree according to the actual influence degree, and obtaining the deviation degree of the pressure according to the actual influence degree, the vibration intensity data and the gas pressure data.
Firstly, acquiring the difference value of the data point between the t-th moment in any gas pressure data section and the minimum gas pressure data in the corresponding gas pressure data section in the gas pressure data acquired by each gas pressure sensor, and recording the difference value as the change amplitude of the gas pressure when the t-th moment is affected by vibration
. The accumulated value of the changing amplitude of the gas pressure is obtained from the corresponding gas pressure data obtained by all the gas pressure sensors at the same moment
As an integral gas in the tank bodyThe change of the body pressure is recorded as the integral change value of the gas pressure at the t-th moment in any gas pressure data section
。
In addition, the magnitude of the integral pressure change value at any moment in the corresponding gas pressure data section is obtained through linear normalization, namely the integral pressure change value of the normalized gas pressure
。
Obtaining maximum value and minimum value in each vibration intensity data segment by using linear normalization, normalizing the vibration intensity data in each vibration intensity data segment, and recording the normalization result as
。
Then, a deviation degree W of whether the gas pressure data changes with the intensity of vibration intensity data in any gas pressure data segment is obtained:
wherein ,
a standard deviation indicating the actual degree of influence at time t,
indicating the normalized gas pressure overall change value at the t-th time,
the normalized numerical value representing the vibration intensity data at the time t,
representing the average value of the absolute value of the difference between all normalized gas pressure overall change values and vibration intensity data, T representing the value contained in the corresponding gas pressure data segmentIs used for the number of times of (a),
representing a linear normalization function;
degree of deviation factor
The difference between the integral change value of the gas pressure and the vibration intensity data corresponding to the t moment is reflected, and under normal conditions, the change of the gas pressure is corresponding to the vibration intensity of the corresponding moment, so that when the difference is higher, the influence of the integral change value of the gas pressure and the vibration intensity of the actual tank body is not consistent, and other conditions exist when the gas pressure in the tank body is influenced by the vibration of the tank body;
Therefore, the standard deviation of the corresponding relation between the gas pressure change and the vibration intensity in the gas pressure data segment reflects the discrete degree of the corresponding difference condition of the gas pressure change and the vibration signal intensity in the gas pressure data segment, namely the deviation degree of the vibration condition of the gas pressure data and the tank body, when the numerical value of the characteristic is higher, the change of the gas pressure is not in accordance with the influence of normal tank body vibration, wherein the possibility that other factors possibly exist to cause the internal pressure change is higher, so that the data of the part still has other additional factors in the tank body although the data is fluctuated due to the tank body vibration, and the corresponding information in the trend fitting is also required to be reserved.
And a data fitting and adjusting module: and obtaining adjustment parameters according to the pressure deviation degree and the pressure abnormality degree, and adjusting the fitting process of the least square method by using the adjustment parameters.
According to the degree of pressure abnormality at the t-th time obtained in the step (1) and the step (3)
Degree of deviation in the section of gas pressure data
Obtaining the first gas pressure data section
Fitting adjustment parameters of time gas pressure data
：
Wherein W represents the degree of deviation,
the abnormal degree of the pressure at the t-th moment is represented;
representing a linear normalization function;
wherein, the first
The adjustment parameters obtained from the time data are obtained from the degree to which the pressure exceeds the pressure reference value and the degree to which the fluctuation of the data is correlated with the vibration signal in the segmented data, so that the coefficient is obtained based on the integral characteristic of the data to adjust the specific degree of the data, and the multiplication is usedAnd (5) row combination. Finally, when the value is larger, the more information the corresponding data needs to retain at the moment is needed to be subjected to least square fitting, and when the characteristic value is small, the more trend that the pressure data fluctuation at the moment tends to be influenced by vibration only is the fluctuation under normal conditions, and the smaller the corresponding information the data contributes to when the data trend fitting is carried out subsequently is, namely the lower the degree of influence trend is;
acquiring fitting adjustment parameters of the gas pressure data in all the gas pressure data segments of all the gas pressure data, and recording the fitting adjustment parameters of the gas pressure data acquired by the ith gas pressure sensor at the a-th moment as
；
Adjusting parameters according to fit
The least square method curve is adjusted in the curve fitting process of the gas pressure data:
wherein ,
the fitting data after adjustment at the a-th moment is obtained when fitting the gas pressure data acquired by the i-th gas pressure sensor by using a least square method;
the fitting adjustment parameters at the a-th moment are shown in the gas pressure data acquired by the i-th gas pressure sensor;
representing fitting data obtained at the a-th moment when fitting the gas pressure data acquired by the i-th gas pressure sensor by using a least square method;
the fitting data obtained after the least square method fitting is adjusted according to the adjustment parameter value obtained by each gas pressure data, so that the influence of abnormal data in the gas pressure data on curve fitting is reduced; when the fitted data is more approximate to normal, namely when the gas pressure data fluctuates to normal fluctuation caused by tank vibration, the fitted gas pressure data is smoother at the position of the corresponding fitting curve, so that false early warning caused by gas pressure increase of the internal local position caused by tank vibration is avoided.
The method comprises the steps of carrying out data segmentation on gas pressure data and vibration intensity data according to the size of the vibration intensity data, and then, carrying out adjustment on the association degree of fluctuation of the gas pressure data and the vibration intensity data in each gas pressure data segment and each vibration intensity data segment by combining influence superposition caused by multiple times of vibration, so as to represent whether the fluctuation of the data is caused by vibration in the segment and combining the fluctuation of the data with the degree of each data exceeding normal pressure data, thereby obtaining adjustment parameters of each data in curve fitting;
the air pressure early warning module: and performing curve fitting on the gas pressure data according to the corrected least square method to obtain a change curve of the actual gas pressure data, presetting a gas pressure threshold value to be 0.45MPa according to experience, judging whether the pressure in the tank body of the dry powder tank truck is dangerous according to the data size in the fitted curve, and performing air pressure early warning when the data in the fitted curve is greater than the preset gas pressure threshold value to remind a driver of the tank truck of needing to reduce the load and reduce the temperature, wherein otherwise, the excessive gas pressure can cause explosion or leakage of the dry powder tank truck to cause serious personnel injury and property loss.
The dry powder tank truck tank body specifically comprises the following devices: the cylinder is used for loading dry powder materials, the feeding port is used for filling the dry powder materials into the cylinder, the discharging port is used for discharging the dry powder materials in the cylinder, the air pressure sensors are uniformly arranged at a plurality of positions in the cylinder and used for acquiring air pressure data at different positions, the vibration sensor is arranged at the bottom of the cylinder and used for acquiring vibration intensity data of the cylinder, and a processor connected with the air pressure sensors and the vibration sensor is used for analyzing the acquired air pressure data and vibration intensity data, wherein the processor comprises any monitoring system.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (6)
1. The monitoring system of the dry powder tank truck tank body is characterized by comprising the following modules:
and a data acquisition module: acquiring vibration intensity data of the inner part of a tank body of the tank truck and gas pressure data at a plurality of positions;
and a data preprocessing module: smoothing and denoising all the gas pressure data and the vibration intensity data, taking the corresponding moment of a data point with the vibration intensity larger than a preset vibration intensity threshold value as a segmentation point, and respectively recording a section of vibration intensity data and a section of gas pressure data contained by two adjacent segmentation points as a vibration intensity data section and a gas pressure data section;
and a data analysis module: the corresponding gas pressure at the initial time in the gas pressure data is recorded as a pressure reference value, and the pressure abnormality degree is obtained according to the difference between the average value of the gas pressure data at any time and the pressure reference value;
decomposing all the vibration intensity data segments to obtain a plurality of IMF vibration intensity components, and recording the time interval between the maximum value of the vibration intensity components in the IMF vibration intensity components and other vibration intensity components as the time interval; obtaining the actual influence degree according to the fusion result of the vibration intensity component and the time interval;
acquiring a standard deviation of the actual influence degree of the IMF vibration intensity component at any time; acquiring a difference value between gas pressure data and minimum gas pressure data, marking the difference value as a change amplitude value, counting all change amplitude values, marking the difference between the gas pressure overall change value and vibration intensity data as a deviation degree factor, and regulating the standard deviation of the deviation degree factor by using the standard deviation of the actual influence degree to obtain a deviation degree;
and a data fitting and adjusting module: the deviation degree is used for adjusting the abnormal pressure degree to obtain fitting adjustment parameters, the gas pressure data is subjected to curve fitting by using a least square method to obtain fitting data, and the fitting data is adjusted by using the fitting adjustment parameters to obtain adjusted fitting data;
the air pressure early warning module: and realizing air pressure early warning according to the size of the adjusted fitting data.
2. The monitoring system of a dry powder tank truck according to claim 1, wherein the degree of pressure abnormality is obtained by the following method:
obtaining the pressure abnormality degree at the t-th moment according to the pressure reference value and the gas pressure data
：
Wherein S represents a pressure reference value,
characterization of->
The individual air pressure sensor is at +.>
The gas pressure acquired at the moment, I represents the number of gas pressure sensors, +.>
A logarithmic function based on a natural constant is represented.
3. The monitoring system of a dry powder tank truck according to claim 1, wherein the actual influence degree is obtained by the following method:
carrying out data decomposition on each vibration intensity data segment of the vibration intensity data by using an EMD modal decomposition algorithm, and marking an IMF (inertial measurement unit) component obtained by decomposition as an IMF vibration intensity component, wherein each IMF vibration intensity component corresponds to a component value of vibration intensity at any time and is marked as a vibration intensity component;
recording the time interval between the maximum value of the vibration intensity component in any one vibration intensity data segment and the vibration intensity component corresponding to other moments in any one IMF vibration intensity component as the time interval;
the corresponding vibration intensity component in the mth IMF vibration intensity component in any vibration intensity data section has actual influence degree on the gas pressure data at the t moment
The method comprises the following steps:
wherein ,
represents the (th) in the (m) th IMF vibration intensity component>
The magnitude of the vibration intensity component corresponding to the moment,/-or->
Time interval representing the t-th vibration intensity component of the m-th IMF vibration intensity components,/->
Representing a linear normalization function.
4. The monitoring system of a dry powder tank truck according to claim 1, wherein the deviation is obtained by the following steps:
in any gas pressure data segment, whether the gas pressure data deviate from the degree W of intensity change of vibration intensity data or not:
wherein ,
standard deviation +.>
Indicating the normalized gas pressure overall change value at time t, +.>
Normalized value size of vibration intensity data at time t, < >>
Representing the average of the absolute values of the differences of all normalized gas pressure overall change values and vibration intensity data, T representing the number of moments contained in the corresponding gas pressure data segment, +.>
Representing a linear normalization function.
5. The monitoring system of the dry powder tank truck tank according to claim 1, wherein the air pressure early warning is realized according to the adjusted fitting data, and the method specifically comprises the following steps:
and performing curve fitting on the gas pressure data according to the corrected least square method, so as to obtain a fitting curve of the actual gas pressure data, judging whether the pressure in the tank body of the dry powder tank truck is dangerous or not according to the data size in the fitting curve by setting a gas pressure threshold in advance, and performing air pressure early warning when the data in the fitting curve is larger than a preset gas pressure threshold.
6. The dry powder tank truck tank body is characterized by comprising the following devices in detail: the cylinder is used for loading dry powder materials, the feed inlet is used for filling the dry powder materials into the cylinder, the discharge outlet is used for discharging the dry powder materials in the cylinder, the air pressure sensors are uniformly arranged at a plurality of positions in the cylinder and used for acquiring air pressure data at different positions, the vibration sensor is arranged at the bottom of the cylinder and used for acquiring vibration intensity data of the cylinder, and a processor connected with the air pressure sensors and the vibration sensor is used for analyzing the acquired air pressure data and vibration intensity data, wherein the processor comprises the monitoring system according to any one of claims 1-5.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117870943A (en) * | 2024-01-22 | 2024-04-12 | 中国三峡建工(集团)有限公司 | Multi-sensor-based data optimization acquisition system in grouting process |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19646685A1 (en) * | 1996-11-12 | 1998-05-14 | Heuft Systemtechnik Gmbh | Methods for determining parameters, e.g. B. level, pressure, gas composition in closed containers |
| JP2003055710A (en) * | 2001-08-15 | 2003-02-26 | Kawasaki Steel Corp | Method for detecting abnormal blow of immersed lance |
| JP2003214966A (en) * | 2002-01-21 | 2003-07-30 | Masaki Esashi | Oscillation type pressure sensor |
| JP2013097601A (en) * | 2011-11-01 | 2013-05-20 | Cenergy Co Ltd | Liquefied gas lorry remote monitoring system |
| CN203823434U (en) * | 2014-02-13 | 2014-09-10 | 四川宝力能源装备有限公司 | State monitoring device of LNG (Liquefied Natural Gas) low-temperature storage tank |
| CN205744190U (en) * | 2016-05-23 | 2016-11-30 | 南昌市特永实业有限公司 | A kind of automobile safety canister |
| CN107643100A (en) * | 2016-07-21 | 2018-01-30 | 西安定华电子股份有限公司 | A kind of tank car Integrated Measurement System that can efficiently judge leakage |
| CN207827058U (en) * | 2018-01-16 | 2018-09-07 | 成都建工赛利混凝土有限公司 | The explosion-proof can system of powder material tank |
| CN111071646A (en) * | 2019-12-26 | 2020-04-28 | 李华 | Oil tank truck tank body state monitoring system, method and method based on big data |
| CN211717732U (en) * | 2020-05-15 | 2020-10-20 | 吴浩 | Air pressure detection device for canned transport vehicle for transporting explosive gas |
| CN115326165A (en) * | 2022-10-12 | 2022-11-11 | 山东特联信息科技有限公司 | Tank car remote monitoring system |
| CN218600750U (en) * | 2022-10-19 | 2023-03-10 | 江苏誉立化工装备制造有限公司 | Air pressure detection device for oil tank production and processing |
-
2023
- 2023-05-09 CN CN202310513072.5A patent/CN116222870B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE19646685A1 (en) * | 1996-11-12 | 1998-05-14 | Heuft Systemtechnik Gmbh | Methods for determining parameters, e.g. B. level, pressure, gas composition in closed containers |
| JP2003055710A (en) * | 2001-08-15 | 2003-02-26 | Kawasaki Steel Corp | Method for detecting abnormal blow of immersed lance |
| JP2003214966A (en) * | 2002-01-21 | 2003-07-30 | Masaki Esashi | Oscillation type pressure sensor |
| JP2013097601A (en) * | 2011-11-01 | 2013-05-20 | Cenergy Co Ltd | Liquefied gas lorry remote monitoring system |
| CN203823434U (en) * | 2014-02-13 | 2014-09-10 | 四川宝力能源装备有限公司 | State monitoring device of LNG (Liquefied Natural Gas) low-temperature storage tank |
| CN205744190U (en) * | 2016-05-23 | 2016-11-30 | 南昌市特永实业有限公司 | A kind of automobile safety canister |
| CN107643100A (en) * | 2016-07-21 | 2018-01-30 | 西安定华电子股份有限公司 | A kind of tank car Integrated Measurement System that can efficiently judge leakage |
| CN207827058U (en) * | 2018-01-16 | 2018-09-07 | 成都建工赛利混凝土有限公司 | The explosion-proof can system of powder material tank |
| CN111071646A (en) * | 2019-12-26 | 2020-04-28 | 李华 | Oil tank truck tank body state monitoring system, method and method based on big data |
| CN211717732U (en) * | 2020-05-15 | 2020-10-20 | 吴浩 | Air pressure detection device for canned transport vehicle for transporting explosive gas |
| CN115326165A (en) * | 2022-10-12 | 2022-11-11 | 山东特联信息科技有限公司 | Tank car remote monitoring system |
| CN218600750U (en) * | 2022-10-19 | 2023-03-10 | 江苏誉立化工装备制造有限公司 | Air pressure detection device for oil tank production and processing |
Non-Patent Citations (1)
| Title |
|---|
| 孙丽娜等: "罐式集装箱液体晃动过程数值模拟研究", 振动与冲击, vol. 31, no. 22 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117870943A (en) * | 2024-01-22 | 2024-04-12 | 中国三峡建工(集团)有限公司 | Multi-sensor-based data optimization acquisition system in grouting process |
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