CN110610295A - Universal integrated acquisition system and method for resource environment load data - Google Patents

Universal integrated acquisition system and method for resource environment load data Download PDF

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CN110610295A
CN110610295A CN201910749647.7A CN201910749647A CN110610295A CN 110610295 A CN110610295 A CN 110610295A CN 201910749647 A CN201910749647 A CN 201910749647A CN 110610295 A CN110610295 A CN 110610295A
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王禹林
陈超宇
何彦
叶祖坤
祁宏坚
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Nanjing Yuqiyuan Intelligent Equipment Technology Co Ltd
Chongqing University
Nanjing Tech University
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Abstract

The invention discloses a universal integrated acquisition system and a universal integrated acquisition method for resource environmental load data, wherein the acquisition system comprises a data acquisition module, a data communication module and a data processing module, and is used for realizing integrated acquisition of various data and processing the acquired data by integrating sensors such as dust, noise, power, volatile organic compounds, sulfur dioxide, nitric oxide, carbon monoxide, ozone, an electronic weighing meter and the like; the collecting method comprises the steps of setting gas index concentration sampling points and arranging sensors at points to be measured; determining the index quantity needing to be collected in real time; after the data indexes are stable, data acquisition is carried out; and performing missing value compensation and data abnormal value elimination on the data, and performing weighted calculation on the measured data after the data missing value compensation and the abnormal value elimination. The invention can solve the problems of low acquisition efficiency and inaccurate acquisition result of the related indexes of the existing process workshop.

Description

Universal integrated acquisition system and method for resource environment load data
Technical Field
The invention belongs to the field of workshop process environment monitoring, and particularly relates to a universal integrated acquisition system and method for resource environment load data.
Background
Modern manufacturing industries consume large quantities of materials and energy in the manufacturing process of converting resources into products, and produce large quantities of waste and harmful pollutants, which pose serious hazards to the environment and the health of operators. In the process resource load, the consumption of materials and energy is the main process input. In the process environment load, dust is the most common cause of various occupational diseases, and large-particle dust (PM100) is also easy to generate dust explosion in a production workshop; volatile Organic Compounds (VOCs) are products using organic compounds in production raw materials, and are easy to cause acute poisoning of workers; sulfur dioxide (SO)2) Nitrogen oxides (NOx), carbon monoxide (CO), ozone (O)3) The method is characterized in that the method is a common method for discharging toxic and harmful pollutants in the environment and is also an important occupational health hazard index; high decibel noise also can be detrimental to worker hearing and can affect surrounding residents. However, the detection aiming at the indexes is mainly realized by a single sensor at present, the steps are complicated, and the data samples are few; the detection of the related sensors mainly aims at the atmospheric environment, and the regulations of collection methods such as sampling positions and sampling time and the like when a workshop, particularly a single device, collects are lacked; a general integrated acquisition system and a general integrated acquisition method capable of integrally acquiring environmental load data of various resources in a workshop are lacked.
Chinese patent publication No. CN108351335A discloses an apparatus and method for collecting and recording density of fine particles and/or NOx gas in air, which introduces a vehicle-mounted apparatus and a mobile method for collecting and recording density of fine particles and NOx gas in air, the method mainly includes PM2.5 and NOx as measurement indexes, the detection indexes are few, and the integration level of collecting various sensors is low. Chinese patent publication No. CN105548502A discloses an air quality detector, which is mainly used in the field of environmental monitoring, and is suitable for being arranged everywhere in a city, but is not suitable for detecting in a complex workshop process environment because of insufficient index analysis of a relatively closed workshop environment in an industrial production scene, and cannot acquire data for a single discrete machine tool. Chinese patent publication No. CN 105865993a discloses an air quality detector, which mainly aims at toxic and harmful gases generated by interior decoration, and also cannot acquire data for a single machine tool. Meanwhile, the above patents do not perform data processing on the measured values, and do not propose related acquisition methods such as arrangement of an index acquisition sensor and setting of sampling frequency.
In summary, the current collection devices mainly aim at atmospheric environment and interior decoration, no collection system which can collect pollutants related to a single machine tool in a workshop in an integrated manner and is simple to operate exists, and the regulations on collection methods such as collection positions and sampling time are lacked, so that the green optimization of the manufacturing process and the improvement and development of occupational health of operators in the workshop are seriously hindered.
Disclosure of Invention
The invention aims to provide a universal integrated acquisition system and a universal integrated acquisition method for resource environmental load data, which aim to solve the problems of low acquisition efficiency and inaccurate acquisition result of relevant indexes of the existing process workshop.
The technical solution for realizing the purpose of the invention is as follows:
a resource environment load data general integrated acquisition system comprises a data acquisition module, a communication module and a data processing module;
the data acquisition module comprises a dust sensor, a noise sensor, a power sensor, an electronic weighing meter, an RFID reader-writer, a VOCs sensor and an SO2Sensor with a sensor elementNOx sensor, CO sensor, O3Any one or more of any combination of sensors; the dust sensor is used for collecting the dust content; the noise sensor is used for collecting noise; the power sensor is used for measuring the power of the machine tool in the machining process in real time; the electronic weighing meter is used for weighing the input and output weight of the material; the RFID reader is used for identifying material information; the VOCs sensor and SO2Sensor, NOx sensor, CO sensor, O3The sensors are used for measuring corresponding gas concentrations;
the communication module is used for sending the data acquired by the data acquisition module to the data processing module;
the data processing module comprises a data missing value compensation unit, a data abnormal value removing unit, a data weighting calculation unit and a storage unit; the data missing value compensation unit is used for compensating the missing data of the abnormal acquisition points measured by the gas sensor through a regression interpolation method; the abnormal value eliminating unit is used for eliminating the abnormal value measured by the gas sensor; the data weighting calculation unit is used for carrying out weighting calculation on the measurement data processed by the data missing value compensation unit and the abnormal value elimination unit; and the storage unit is used for carrying out real-time display, curve drawing and data storage on the processed data.
A resource environment load data general integrated acquisition method comprises the following steps:
step 1, setting gas index concentration sampling points, and arranging sensors at points to be measured;
step 2, determining the index quantity needing to be collected in real time;
step 3, data acquisition: after the data indexes are stable, data acquisition is carried out;
and 4, data processing: and performing missing value compensation and data abnormal value elimination on the data, and performing weighted calculation on the measured data after the data missing value compensation and the abnormal value elimination.
Compared with the prior art, the invention has the following remarkable advantages:
(1) the acquisition system can acquire dust, VOCs and SO2、NOx、CO、O3Resource environmental load data in various processing technologies such as power, material information, noise and the like; compared with the method that various independent sensors are used for acquisition respectively, the device is high in portability, the installation and acquisition processes of the sensors are greatly simplified, and the data acquisition efficiency is improved; the integration is strong, the data of all indexes at the same time can be collected, and a plurality of sensors of the same kind are used for collecting data of multiple points; therefore, a proper resource environmental load data acquisition system is provided for the industrial scene to evaluate the process environment influence and acquire relevant data.
(2) The system is provided with a data processing module, and performs missing value compensation, abnormal value elimination and related weighted average calculation processing on related data, so that the acquired data is more complete and accurate, and the distribution condition of the measured value data in different time periods or different areas can be better reflected.
(3) The acquisition method of the acquisition system capable of synchronously and integrally acquiring the environmental load data of various resources sets the acquisition position and the sampling time of an instrument, sets the acquisition points of the gas index concentration aiming at different processing scenes of closed and open machine tools, and provides a data acquisition scheme and a calculation method for the acquisition of equipment-level data of a single machine tool and the whole workshop-level data, improves the quality of the acquired data, and has great advantages in the application of data acquisition of industrial production workshops.
Drawings
Fig. 1 is a schematic structural diagram of a resource environmental load data acquisition system.
Fig. 2 is a schematic view of a main view of an in-box device of the resource environmental load data acquisition system.
Detailed Description
The invention is further described with reference to the following figures and embodiments.
With reference to fig. 1 and fig. 2, the resource environmental load data general integrated acquisition system of the present invention includes a data acquisition module, a communication module, and a data processing module;
the data acquisition module comprises a dust sensor 5, a noise sensor 11 and a power transmitterSensor, electronic weighing meter, RFID reader-writer, VOCs (volatile organic compounds) sensor 3 and SO2Sensor 2, NOx sensor 8, CO sensor 9, O3Any one or more of the sensors 10 in any combination; the dust sensor 5 is used for collecting PM100 dust content; the noise sensor 11 is used for collecting noise; the power sensor is used for measuring the power of the machine tool in the machining process in real time to calculate the energy consumption; the electronic weighing meter is used for weighing input and output weights of materials such as workpieces, cutting fluid and the like; the RFID reader-writer is used for identifying material information such as machine tool model, workpiece material, cutting fluid oil, cutter material, geometric angle and the like; VOCs sensor 3, SO2Sensor 2, NOx sensor 8, CO sensor 9, O3The sensor 10 is used to measure the corresponding gas concentration. Various gas sensors can adopt diffusion type sampling and also can adopt pump suction type sampling; a sensor adopting diffusion type sampling is integrated on a sensor mounting plate 4 in a main control machine box 1 and is contacted with ambient gas for sampling through a through hole on the surface of the machine box; the sensor adopting the pump suction type sampling and the sensors of other indexes are connected with the main controller box 1 through cables.
The communication module is used for sending the data acquired by the data acquisition module to the data processing module; the method comprises the steps of sending data acquired by a data acquisition module to a data processing module in a wired or wireless mode; for example, the wired mode can adopt wired communication modules such as a data acquisition card 6, an RS232 and an RS485 to carry out data communication of the sensor near the main control machine box; the wireless mode comprises wireless communication modules such as WiFi, ZIGBEE, GPRS and the like, and the sensors are arranged at the far end for data communication, so that multipoint data can be monitored simultaneously. This allows for a free arrangement of the sensors in the acquisition module.
The data processing module comprises a data missing value compensation unit, a data abnormal value removing unit, a data weighting calculation unit and a storage unit;
the data missing value compensation unit is used for compensating missing data (missing value) of an abnormal acquisition point measured by the gas sensor through a regression interpolation method, and the specific process is as follows:
taking the lost data of the abnormal acquisition points as dependent variables and other normally measured data as independent variables, establishing a regression model by utilizing the fitting relation between the lost data and the other normally measured data under the normal acquisition condition to predict missing values, and performing missing value interpolation by utilizing a multiple linear regression model:
taking the lost data y of the sensor as a dependent variable, namely a missing value; data x measured normally by n sensors1,x2,...,xnFor the independent variables, i.e. other measured values related to the missing values, a multiple linear regression model was established:
y＝β0+β1x1+β2x2+...+βnxn+ε (1)
wherein, beta0,β1,β2,...,βnIs a coefficient of the relevant parameter; epsilon is a constant, obeys the classical assumptions of zero mean, mutual independence and homovariance obeying normal distribution, etc.;
calculating a parameter beta0,β1,β2,...,βnEstimated value of (a):
the parameter beta can be obtained by using the data normally measured by n sensors in actual measurement and adopting a least square method0,β1,β2,...,βnIs estimated value ofAfter the parameter estimation value is solved, a multiple regression equation can be obtained:
and substituting the value of the independent variable to obtain the missing value.
The abnormal value eliminating unit is used for eliminating the abnormal value measured by the gas sensor, and the specific process is as follows: according to the Lauda criterion (3 sigma), the measured quantity of a single sensor is measured with equal precision, and the data x under the same condition are independently obtained1,x2,...,xnCalculating x1,x2,...,xnIs arithmetic mean ofAnd residual errorAnd calculating the standard deviation sigma according to Bessel formula, if a certain measured value xbResidual error v ofb(1. ltoreq. b. ltoreq. n) satisfying the following formula (3):
then consider xbThe bad values containing the gross error values are eliminated.
After the data are processed by the data missing value compensation unit and the abnormal value elimination unit, the acquired data have no free position and invalid data, and have no overlarge data and overlarge data.
The data which are not influenced by the environment are stored by a data storage unit, such as data measured by a power sensor, an electronic weighing meter and an RFID reader-writer. The data affected by the environment needs to be weighted and calculated by a data weighting and calculating unit.
The data weighting calculation unit is used for carrying out weighting calculation on the measurement data processed by the data missing value compensation unit and the abnormal value elimination unit; the method comprises an area weight calculation unit and a time weight calculation unit:
the time weighting calculation unit is used for selecting at least 3 different time intervals for collecting the collected values of the index concentration of the data gas of the equipment level of a single machine tool according to the morning, noon, afternoon or several typical production working days in the work system of 8h a day, respectively, so as to obtain the highest value of the index data, and calculating to obtain the weighted average concentration values of the time intervals, wherein the specific calculation process is as follows:
C＝(C1T1+C2T2+……+CnTn)/(T1+T2+……+Tn) (4)
in the formula: c is the time-weighted average concentration of harmful substances in the air, mg/m3；
C1、C2、……、CnConcentration of harmful substances in air, mg/m, measured at different time intervals3；
T1、T2、……、TnThe working time of workers under different periods of harmful substance concentration is h.
The area weighting calculation unit is used for dividing the collected value of the whole workshop level data into at least 3 different processing areas according to the cutting processes of turning, milling, grinding and the like or the equipment types of closed type and open type machine tools and the like for collection respectively to obtain the highest value of the index data, and calculating to obtain the weighted average concentration values of the areas, wherein the specific calculation process is as follows:
Cworkshop＝(C1S1+C2S2+……+CnSn)/(S1+S2+……+Sn) (5)
In the formula: cWorkshopThe concentration of the whole harmful substances in the workshop is mg/m3；
C1、C2、……、CnConcentration of harmful substance measured for different representative regions, mg/m3；
S1、S2、……、SnIs the area of the different regions, m2。
The original measurement data is processed by a weighted average processing and calculating method to obtain a characteristic value, so that the distribution condition of the measurement data in different time periods or different areas can be better reflected; and then the storage unit carries out real-time display, curve drawing and data storage on the acquired and processed data.
Based on the acquisition system, the invention also provides an acquisition method capable of synchronously and integrally acquiring the environmental load data of various resources, which comprises the following steps:
step 1, judging the type of a machine tool to be measured, setting gas index concentration sampling points according to different closed and open machine tools and processing scenes, arranging all sensors at the points to be measured, connecting a power supply, connecting a data transmission module with an upper computer, and opening upper computer software. The gas index concentration sampling points are arranged to face the production source of the equipment to be tested, such as the machining position of a cutter. If the tool moving range is small, data of a single acquisition point near the tool is adopted, for example, a closed machine tool sampling point is arranged at a machine tool door, and an open machine tool sampling point is arranged at a machined side of a workpiece; however, if the moving range of the tool is large, such as the gas diffusion caused by the gaps around the closed machine tool or the rotary machining of the tool in a larger plane by the open machine tool, a plurality of same sensors are arranged in the front, back, left, right and other directions of the machine tool for acquisition.
And 2, determining the index quantity needing to be collected in real time, collecting corresponding gas by using dust, VOCs, SO2, NOx, CO and O3 sensors, collecting noise by using a noise sensor, and collecting voltage and current information by using a power sensor. Meanwhile, for other process scene information, the weights of the workpiece, the cutting fluid, the waste water and the solid waste can be weighed by an electronic weighing meter, and the related information of the machine tool, the workpiece, the cutting fluid and the cutter can be acquired by an RFID reader-writer.
Step 3, data acquisition: operating the machine tool to carry out actual machining, and stopping the machine tool equipment which possibly generates interference around the machine tool; in the initial stage of equipment operation, the concentration of the relevant index can be continuously increased along with the processing, but tends to be stable after a period of time, so that the measurement of the effective data of the index is carried out after the machine tool operates for 15-30 min.
Step 4, displaying the acquired data, dust, VOCs and SO through a display screen of the storage unit2、NOX、CO、O3And drawing a data curve by taking time as a horizontal axis and taking an index value as a vertical axis, and after the acquisition is finished, processing and storing the data. And (3) acquiring data of a single machine tool equipment level or data of the whole workshop level according to the needs, repeating the steps 1-4, acquiring for at least 3 times, and averaging by using different weighted calculation units.
The processing process in the method is based on the processing process of the data processing module, and comprises missing value compensation, data abnormal value elimination and data weighting calculation, and the specific content is the same as the processing process of the data processing module, and is not described herein again.
Further, dust, VOCs, SO2、NOX、CO、O3The noise sensor is integrated near the main control box due to the similar collection method and index generation source, and the position of the sampling point is 0.5-1m away from the machining position of the cutter; the power sensor is arranged at the power supply input end of the machine tool motor; the electronic weighing meter has any working position and is connected with the upper computer software through a transmission line. The gas sensors such as dust, VOCs, SO2, NOx, CO, O3 and the like can read once every 1-10s during collection; the sampling frequency of the noise sensor can reach 5-20kHz, and the sampling frequency of the power sensor can reach 25-70 Hz; the data of each time period should be collected for 10-30min, and the collection time selected in the time period should be at least 1h to avoid the interference among the data of different time periods.

Claims (10)

1. A resource environmental load data general integrated acquisition system is characterized by comprising a data acquisition module, a communication module and a data processing module;
the data acquisition module comprises a dust sensor, a noise sensor, a power sensor, an electronic weighing meter, an RFID reader-writer, a VOCs sensor and an SO2Sensor, NOx sensor, CO sensor, O3Any one or more of any combination of sensors; the dust sensor is used for collecting the dust content; the noise sensor is used for collecting noise; the power sensor is used for measuring the power of the machine tool in the machining process in real time; the electronic weighing meter is used for weighing the input and output weight of the material; the RFID reader is used for identifying material information; the VOCs sensor and SO2Sensor, NOx sensor, CO sensor, O3The sensors are used for measuring corresponding gas concentrations;
the communication module is used for sending the data acquired by the data acquisition module to the data processing module;
the data processing module comprises a data missing value compensation unit, a data abnormal value removing unit, a data weighting calculation unit and a storage unit; the data missing value compensation unit is used for compensating the missing data of the abnormal acquisition points measured by the gas sensor through a regression interpolation method; the abnormal value eliminating unit is used for eliminating the abnormal value measured by the gas sensor; the data weighting calculation unit is used for carrying out weighting calculation on the measurement data processed by the data missing value compensation unit and the abnormal value elimination unit; and the storage unit is used for carrying out real-time display, curve drawing and data storage on the processed data.
2. The acquisition system according to claim 1, wherein the data missing value compensation unit specifically operates as follows:
data x normally measured by n sensors by taking lost data y of the sensors as a dependent variable1,x2,...,xnEstablishing a multiple linear regression model for the independent variable:
y＝β0+β1x1+β2x2+...+βnxn+ε (1)
wherein, beta0,β1,β2,...,βnIs a coefficient of the relevant parameter; epsilon is a constant, obeys the classical assumptions of zero mean, mutual independence and homovariance obeying normal distribution, etc.;
calculating a parameter beta0,β1,β2,...,βnEstimated value of (a):
the parameter beta can be obtained by using the data normally measured by n sensors in actual measurement and adopting a least square method0,β1,β2,...,βnIs estimated value ofAfter the parameter estimation value is solved, a multiple regression equation can be obtained:
and substituting the value of the independent variable to obtain the missing value.
3. The acquisition system according to claim 1, wherein the abnormal value eliminating unit specifically works as follows:
according to the Lauda criterion, the measured quantity of a single sensor is measured with equal precision, and the data x under the same condition is independently obtained1,x2,...,xnCalculating x1,x2,...,xnIs arithmetic mean ofAnd residual errorAnd calculating the standard deviation sigma according to Bessel formula, if a certain measured value xbResidual error v ofb(1. ltoreq. b. ltoreq. n) satisfying the following formula:
then consider xbThe bad values containing the gross error values are eliminated.
4. The acquisition system according to claim 1, wherein the data weight calculation unit includes an area weight calculation unit and a time weight calculation unit;
the time weighting calculation unit is used for selecting the highest values obtained in different time periods for the acquired values of the index concentration of the data gas at the equipment level of the single machine tool, and calculating to obtain weighted average concentration values C in the time periods;
C＝(C1T1+C2T2+……+CnTn)/(T1+T2+……+Tn) (4)
wherein C is1、C2、……、CnThe concentration of harmful substances in the air is measured in different time periods; t is1、T2、……、TnThe working time of workers under different periods of harmful substance concentration is shortened;
the area weighting calculation unit is used for selecting the highest values of different processing areas for the acquired values of the whole workshop-level data and calculatingObtaining weighted average concentration values C of the regionsWorkshop；
CWorkshop＝(C1S1+C2S2+……+CnSn)/(S1+S2+……+Sn) (5)
Wherein C is1、C2、……、CnThe concentrations of the harmful substances measured for different representative regions; s1、S2、……、SnAre the areas of the different regions.
5. The acquisition system according to claim 1, wherein the sensor adopting diffusion type sampling is integrated on a sensor mounting plate in the main control case and is in contact with the ambient gas for sampling through a through hole on the surface of the case; the sensor adopting the pump suction type sampling and the sensors of other indexes are connected with the main control machine box through cables.
6. Acquisition method of an acquisition system according to any of claims 1 to 5, characterized in that it comprises the following steps:
step 1, setting gas index concentration sampling points, and arranging sensors at points to be measured;
step 2, determining the index quantity needing to be collected in real time;
step 3, data acquisition: after the data indexes are stable, data acquisition is carried out;
and 4, data processing: and performing missing value compensation and data abnormal value elimination on the data, and performing weighted calculation on the measured data after the data missing value compensation and the abnormal value elimination.
7. The acquisition method according to claim 6, wherein the missing value compensation in step 4 specifically comprises: data x normally measured by n sensors by taking lost data y of the sensors as a dependent variable1,x2,...,xnEstablishing a multiple linear regression model for the independent variable:
y＝β0+β1x1+β2x2+...+βnxn+ε (1)
wherein, beta0,β1,β2,...,βnIs a coefficient of the relevant parameter; epsilon is a constant, obeys the classical assumptions of zero mean, mutual independence and homovariance obeying normal distribution, etc.;
calculating a parameter beta0,β1,β2,...,βnEstimated value of (a):
the parameter beta can be obtained by using the data normally measured by n sensors in actual measurement and adopting a least square method0,β1,β2,...,βnIs estimated value ofAfter the parameter estimation value is solved, a multiple regression equation can be obtained:
and substituting the value of the independent variable to obtain the missing value.
8. The acquisition method according to claim 6, wherein the data outlier rejection in step 4 is specifically: according to the Lauda criterion, the measured quantity of a single sensor is measured with equal precision, and the data x under the same condition is independently obtained1,x2,...,xnCalculating x1,x2,...,xnIs arithmetic mean ofAnd residual errorAnd calculating the standard deviation sigma according to Bessel formula, if a certain measured value xbResidual error v ofb(1. ltoreq. b. ltoreq. n) satisfying the following formula:
then consider xbThe bad values containing the gross error values are eliminated.
9. The acquisition method according to claim 6, wherein the weighted calculation of the data in step 4 comprises area weighted calculation and time weighted calculation:
the time weighted calculation is used for selecting the highest values obtained in different time periods for the acquired values of the data gas index concentration of the equipment level of a single machine tool, and calculating to obtain weighted average concentration values C in the time periods;
C＝(C1T1+C2T2+……+CnTn)/(T1+T2+……+Tn) (4)
wherein C is1、C2、……、CnThe concentration of harmful substances in the air is measured in different time periods; t is1、T2、……、TnThe working time of workers under different periods of harmful substance concentration is shortened;
the area weighting calculation is used for selecting the highest values of different processing areas from the acquired values of the whole workshop-level data and calculating to obtain the weighted average concentration value C of the areasWorkshop；
CWorkshop＝(C1S1+C2S2+……+CnSn)/(S1+S2+……+Sn) (5)
Wherein C is1、C2、……、CnThe concentrations of the harmful substances measured for different representative regions; s1、S2、……、SnAre the areas of the different regions.
10. The acquisition method according to claim 6, wherein sampling points are set according to different types of the machine tool to be detected and different processing scenes before acquisition, the closed machine tool sampling points are arranged at a machine tool door, and the open machine tool sampling points are arranged at a processed side of the workpiece; if open type machine toolWhen the rotary processing of the cutter is carried out in a processing plane, at least 1 sensor is arranged in each of the front, the back, the left and the right directions of the machine tool for acquisition; the measurement of effective data during collection is carried out after the equipment works for 15-30 min; the dust, VOCs and SO2、NOX、CO、O3The position of a sampling point of the noise sensor is 0.5-1m away from the machining position of the cutter; the power sensor is arranged at the power supply input end of the machine tool motor; the gas sensors such as dust, VOCs, SO2, NOx, CO, O3 and the like can read once every 1-10s during collection; the sampling frequency of the noise sensor can reach 5-20kHz, and the sampling frequency of the power sensor can reach 25-70 Hz; the data of each time interval should be collected for 10-30min, and the selected collection time interval should be at least 1 h.
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