EP2860715A1 - Method and assembly for identifying gas concentrations as a warning device in the air - Google Patents

Abstract

The invention relates to a method and an arrangement for identifying gas concentrations in the air, whereby parameters are evaluated by means of data processing using reference and / or classification patterns and, depending on the results of the evaluation, an alarm output and / or visualization takes place as hazard alarms.

Description

The invention relates to a method and an arrangement for identifying gas concentrations as danger detectors in the air, where parameters are evaluated by means of data processing using reference and / or classification patterns and, depending on the results of the evaluation, an alarm output and / or visualization takes place.

From the prior art CO and CO2 detectors for detecting fires are known. Different arrangements and measuring methods are described. However, it does not address the early detection of fires and a very low false alarm rate. This requires both accurate and marketable methods. Such a method will be described here.

A font is known WO 2005/119 618 A2 "Fire alarm algorithm with smoke and gas sensor". In this case, an apparatus and a method are described, which are useful for the detection of fires. There is a comprehensive record of concentrations of carbon monoxide, carbon dioxide and smoke in the environment. In the calculation using a method, the time of the increase rates in each level is documented and a corresponding alarm is triggered when a fault value is detected.

The disadvantage of the existing patent and the commercially available sensors is that they guarantee their accuracy only in a small physical window.

The object of the invention is to find a method and an arrangement for the identification of gas concentrations in the air, wherein a high accuracy with a low cross sensitivity with the aid of extension sensors of certain parameters is achieved and the disadvantage of the prior art by influencing environmental influences, which lead to measured value corruption, is compensated.

The object is achieved in that the patent claim 1 and claim 5 are realized with its subclaims.

Measured value methods for the detection of hazardous and toxic gas concentrations, such as occur in fires, are known. In particular, chemical, semiconductor gas sensors and optical sensors in the range of CO and CO2 are used. However, all these sensors use a measurement time> 2s to achieve the corresponding results.

The new method according to the invention differs in that, in the first method step, measurement times of one second are achieved and at the same time a high recognition reliability and lowest false alarm is produced. Thus, the method allows rapid detection of hazardous gases and smoldering fires.

The method according to the invention is not so much aimed at the general fire detection by means of CO and CO2, but at a highly efficient early detection with a very low false alarm rate. No multi-sensor system is needed, just CO and CO2 sensors. It is believed that the use of CO and CO2 sensors for the detection of general fires is state of the art. The state of the art is also that at high CO and high CO2 concentrations is likely to be a fire, since high natural CO levels do not occur in nature. This evaluation also use many CO detectors, which are already known.

The peculiarity of the method according to the invention is the detection of gas concentrations already in the smoldering fire phase arise and are not detected by previous sensor combinations or too late. For this purpose, accurate measured values must be determined and evaluated. In order to achieve high measuring accuracy, the existing sensor drift is compensated and external environmental influences are eliminated. Furthermore, a very high long-term stability is achieved and the false alarm rate is kept below 0.1%. A reliable fire detection is carried out with the inventive method already from 50 ppm CO concentration, in which there is no health risk.

The inventive method is based on two levels of detection of gas concentrations, in particular of a CO concentration.

In the first stage, the CO or CO2 concentration or temperature is sampled once per second. The attachment of molecules in the CO or CO2 sensor is a dynamic process and requires a chemical equilibrium. The mathematical function for achieving the GG is known. Shortening the measurement, the GG is no longer reached. In the first stage, short measurement times are needed, which are less than one second. It is a slightly worse resolution due to the unfinished equilibrium process accepted. If there is no danger detection in this phase, it will continue to measure in this mode. If a signal is detected, the measuring time is automatically extended, so the resolution significantly improve. These process steps can also be applied to two or more sensors.

This measurement algorithm is extremely energy-efficient, as it is carried out in the charge balance method. Thus, it can also be operated by battery-based systems over a long period of time. If a detection event occurs in the first method step, a second method step is started with the entire electronic evaluation.

In the second process step, both CO and CO 2 concentrations are determined with a longer measurement time. At the same time, all environmental parameters are measured and their influences on the measurement result are corrected in order to increase the measuring accuracy. The data thus corrected are fed to a neural network or other intelligent evaluation method which classifies the fire probability. Thus, no thresholds for the gas concentrations are needed, making the system very stable and reproducible. The evaluation of the measurement results is done via a μController.

Through this structure of the process sections, another sensor can be added without major technical changes, which extends the system by a gas component, such as methane. Thus, the system can also be used as a leak detector for Natural gas can be used. Other sensors or combinations are possible.

A repeated execution shows the individual process steps for the identification of gas concentrations in the air.

In a first method step, the evaluation of the CO and / or CO 2 concentration is carried out in an algorithm with one measurement per second. Here is a very fast detection takes place.

If in this first measuring section a signal recognition of a gas concentration of CO, a second process section is switched on, which is executed in longer measuring sections and in this case evaluates CO, CO2, air pressure, temperature and humidity as measurement results.

In this process step, a correction of the measured values, which are falsified by real environmental conditions, such as, for example, atmospheric pressure fluctuations, takes place.

Another special process step is the correction of the long-term drift of CO and CO2 sensors. Subsequently, a normalization of the sensor data take place. Further supply of the given measurement data to a neural network or other intelligent evaluation units can specify the evaluation of the measurement result.

• kein Brand
• Schwelbrand
• Brand
• CO-Alarm
• kein Brand, CO2, Anzeige Feuchte zu hoch, Lüftung des Raumes.

The following measurement results are conceivable:

• no fire
• smoldering
• fire
• CO alarm
• no fire, CO2, humidity indicator too high, room ventilation.

The complexity of the method results from the many combinations of sensor data.

• dass in einem ersten Verfahrensschritt eine Gaskonzentration über Sensoren oder eine Temperatur in kurzen Messzeiten von einmal pro Sekunde ermittelt wird und bei einer Signalerfassung eines von den Normalbedingungen abweichenden Messwertes ein zweiter Verfahrensschritt mit einer Messzeitverlängerung über einmal pro Sekunde der Messung der Gaskonzentration und einer gleichzeitigen Messung eines Druckes und/oder einer Temperatur und/oder einer Feuchte über gegebene Sensoren ausgeführt wird und in Abhängigkeit der Sensordatenfusion eine Korrektur der Gaskonzentration und eine Normierung erfolgt und nachfolgend ein angelerntes Neuronales Netz mit diesen Daten beaufschlagt wird, um eine Auswertung und Gefahrenbewertung mit einer Alarmausgabe und einer Visualisierung durchzuführen,
• dass im ersten Verfahrensschritt die Gaskonzentration über CO2- und CO-Sensoren ermittelt wird,
• dass im ersten Verfahrensschritt eine Temperatur über einen Temperatursensor ermittelt wird,
• dass im zweiten Verfahrensschritt mit einer Messzeitverlängerung die Messung der Gaskonzentration über einen CO- und/oder CO2-Sensor ausgeführt wird,
• dass durch das Heranziehen der Parameter Temperatur und/oder Druck und/oder Feuchte die Effizienz der Auswertung und Gefahrenbewertung der Gaskonzentration erhöht wird,
• dass durch die Sensordatenfusion des CO-Sensors und des CO2-Sensors über Parametervorgaben eine genaue Darstellung von Gefahren, insbesondere von Bränden, ermittelt wird,
• dass eine Korrektur der vorhandenen Temperatur-, Druck- und Langzeitdrift der Messdaten nach einem definierten Verfahren durchgeführt wird,
• dass eine zweistufige Detektionsanordnung zur extrem schnellen Erkennung von Gefahrensituationen vorhanden ist und in der zweiten Stufe eine genaue, schnelle und komplexe Auswertung erfolgt und eine Energieeinspeisung über ein Netzteil und/oder durch Solarbetrieb und/oder durch Akkubetrieb möglich ist und eine optische Anzeige vorhanden ist,
• dass die Konfiguration der Basisplatine zur Bestückung in Form eines Baukastenprinzips gegeben ist,
• dass die Basisplatine einen Buzzer und einen Datenlogger aufweist,
• dass insbesondere der CO2-Sensor und der CO-Sensor eine hohe Lebensdauer und eine geringe Querempfindlichkeit aufweisen.

A method for the identification of gas concentrations in the air and an arrangement for carrying out the method have been developed as set forth in claim 1 and in claim 5 with the subclaims,

• that in a first method step, a gas concentration is determined by sensors or a temperature in short measurement times of once per second and at a signal detection of deviating from the normal conditions measured value, a second process step with a measurement time extension over once per second of the measurement of gas concentration and a simultaneous measurement of a Pressure and / or a temperature and / or humidity via given sensors is performed and depending on the sensor data fusion, a correction of the gas concentration and a normalization takes place and Subsequently, a trained neural network is supplied with this data in order to carry out an evaluation and risk assessment with an alarm output and a visualization,
• that in the first process step the gas concentration is determined by means of CO2 and CO sensors,
• that in the first method step a temperature is determined via a temperature sensor,
• that in the second method step the measuring of the gas concentration is carried out with a measuring time extension via a CO and / or CO 2 sensor,
• that the use of the parameters temperature and / or pressure and / or humidity increases the efficiency of the evaluation and hazard assessment of the gas concentration,
• that the sensor data fusion of the CO sensor and the CO2 sensor determines an exact representation of hazards, especially of fires, via parameter specifications,
• that a correction of the existing temperature, pressure and long-term drift of the measured data is carried out according to a defined method,
• that a two-stage detection arrangement for extremely fast detection of hazardous situations is present and in the second stage an accurate, fast and complex evaluation takes place and a power supply via a power supply and / or solar operation and / or battery operation is possible and a visual display is present
• that the configuration of the base board for assembly is given in the form of a modular principle,
• that the motherboard has a buzzer and a data logger,
• that in particular the CO2 sensor and the CO sensor have a long service life and a low cross-sensitivity.

The present method and arrangement in the form of a module on a base board for identifying gas concentrations in the air include three sensor components that allow timely detection of a hazardous situation. For example, in almost every fire caused by the combustion process, depending on the oxygen content, CO or CO2. The system is robust and durable. In addition to the two gas detectors, temperature and / or pressure and / or humidity are measured. These parameters serve to drift correction of the CO or CO2 sensor values. In addition, the temperature can also be used in sensor data fusion as a fire detection sensor act. The basic module can also be operated autonomously via modular systems with a power supply or by means of a solar cell. The existing module based on the motherboard can be modular and scalable according to customer requirements.

1. 1. Welche Sensorik
   Hier werden im Modul folgende Möglichkeiten angeboten: CO2 und CO als Primärparameter bzw. Temperatur, Druck als Korrekturparameter und ein abgesetztes Temperatur/Feuchte-Modul zur Erfassung von Raumklimadaten - nicht als alleinige Messgröße - als Sekundärparameter.
2. 2. Art der Stromversorgung
   Es kann aus Netzbetrieb, Batteriebetrieb oder Solarbetrieb ausgewählt werden.
3. 3. Auswahl der Schnittstelle
   Hier stehen USB, 4-20mA, 0-10V, andere Schnittstellen Zusatzmodule, WLAN oder LAN mit verschiedenen Protokollen zur Auswahl. Weitere Schnittstellen sind möglich.
4. 4. Anzeige
   Für die Anzeige werden LED's bzw. Displays benutzt.

The following structures are possible:

1. 1. Which sensors
   Here, the following options are offered in the module: CO2 and CO as primary parameters or temperature, pressure as correction parameter and a remote temperature / humidity module for the acquisition of indoor climate data - not as a single measured variable - as a secondary parameter.
2. 2. Type of power supply
   It can be selected from mains operation, battery operation or solar operation.
3. 3. Selection of the interface
   Here are USB, 4-20mA, 0-10V, other interfaces additional modules, WLAN or LAN with different protocols to choose from. Other interfaces are possible.
4. 4. Display
   For the display LEDs or displays are used.

From the viewpoint of the highest configuration probability, the main components are integrated on a base board, all other functions are quickly and easily configured as plug-in modules in the modular principle according to the customer's request.

• hohe Messgenauigkeit von +- 50 ppm durch Korrektur der Driften,
• Sensordatenfusion, denn mehrere Sensoren erlauben eine qualitativ hohe Sicht der Auswerteeinheit; das Alleinstellungsmerkmal ist, dass man mit 2 Sensoren (CO2 und CO) nahezu jeden Brand bereits in der Entstehung erkennen kann; die Abtastrate beträgt 2s bis 15s und ist damit wesentlich schneller als die meisten Rauchmelder,
• hohe Flexibilität in der Konfiguration durch das verwendete Baukastensystem.

The newly developed base module has significant unique features and advantages over the existing state of the art. These are:

• high measuring accuracy of + - 50 ppm by correction of drifts,
• Sensor data fusion, because several sensors allow a high quality view of the evaluation unit; the unique selling point is that with 2 sensors (CO2 and CO) you can detect almost every fire already in its formation; the sampling rate is 2s to 15s, which is much faster than most smoke detectors,
• high flexibility in the configuration due to the modular system used.

Due to the modular system and the configuration of the sensor electronics on the base board, a customer request can be realized within a short time. The amount of hardware and production is considered low.

On the base board are in particular a CO2 sensor with a long service life and lower Cross-sensitivity, a CO sensor with a long service life and low cross-sensitivity and an expansion sensor for temperature, pressure, humidity, light, etc. available. These sensors are merged into a sensor data fusion and used for evaluation and risk assessment. An alarm output and visualization are carried out via the evaluation and hazard assessment.

Thanks to the combination of CO2 and CO sensors, almost all fire situations can be reproduced except for pure hydrogen fires, where no CO2 or CO is produced. The ratio of the oxygen content is decisive, how large the CO2 and the CO content in the combustion gas are.

The sensor combination according to the invention detects gas concentrations that arise only in fires. The high-precision CO2 sensor can also be used as an indoor air quality sensor to monitor air quality.

In addition to the determined gas concentrations from the CO2 sensor and the CO sensor, the temperature is also monitored and used for the evaluation. Furthermore, it is also possible to use the expansion sensor pressure and humidity for evaluation. The correction elements of the expansion sensor technology significantly increase the accuracy of the sensor. By using low-sensitivity sensors, a low false alarm probability is achieved. The measuring system CO2 calibrates automatically. Basically, it can therefore be stated that the novel module is designed as a modular system with regard to sensors and interfaces.

Reference to an embodiment of the inventive solution is described.

Figur 1

Grundmodule des Baukastensystems

Figur 2

CO2-Modul

Figur 3

netzbetriebene Variante für Tagungs- und Schulungsräume mit Datenübertragung

Figur 4

Gefahrenmelder für allgemeine Anwendungen in Business- und Privaträumen

Showing:

FIG. 1

Basic modules of the modular system

FIG. 2

CO2 module

FIG. 3

Mains operated variant for meeting and training rooms with data transmission

FIG. 4

Hazard detectors for general applications in business and private rooms

• Eine Basisplatine A dient als Mainboard für die gesamte Schaltung. Es wird ein Mikroprozessor mit einer intelligenten Firmware als Herzstück eingesetzt. Der interne Speicher dient sowohl der Firmware als auch als Datenspeicher (Datenlogger). Auf der Basisplatine A können mehrere Sensor-Varianten realisiert werden, einschließlich der Zwischenspeicherung von Messwerten.
• Auf der Basisplatine A ist ein Uhrenchip mit Quarz und integrierter Lithiumzelle mit einer Betriebszeit von 10 Jahren vorhanden.
• Es sind ein CO2-Sensor 1 und ein CO-Sensor 2 angeordnet. Die Schaltung des CO-Sensors ist mit auf der Basisplatine A integriert.
• Ein Temperatursensor 3 ist auf der Basisplatine A implementiert und hat eine Genauigkeit von <+-1K. Dieser dient der Korrektur der Temperaturdrift.
• Ein Sensor für die Messung von Temperatur und Feuchte (Erfassung der Raumklimadaten) ist als absetzbarer Zusatzsensor I2C angegliedert.
• Auf der Basisplatine A befindet sich ein Sensor für Druck 5 mit absoluter Druckangabe.
• Weiterhin ist auf der Basisplatine A ein Sensor für Licht auf mit bis zu 2000lux gegeben. Er dient der Sensorsteuerung bei Solarbetrieb (Energiemanagement).
• Ein WLAN Zusatzmodul 7, ein Netzwerk Zusatzmodul 8 und andere Schnittstellenzusatzmodule sind auf der Basisplatine A über den Connector (Schnittstellenmodul) angeschlossen.
• Des Weiteren ist eine serielle Schnittstelle 0-20mA und 0-10V 10 vorhanden. Diese Einheit dient als Schnittstelle für die Sensordaten. Welche Sensordaten ausgewählt und über die Schnittstelle ausgegeben werden, wird über die Firmware definiert.
• Das Modul Netzbetrieb 12-24V 11 realisiert als abgesetztes Netzteil die Spannungsversorgung von 12-24V auf 5V der Basisplatine A.
• Ein Modul Solarbetrieb 5V 12 ist mit einem Solarpanel 5V >350mA oder mit mehreren Solarelementen und zwei Pufferakkus LiPo oder ähnlich ausgestattet. Es ist ein abgesetztes Zusatzmodul, jedoch nicht auf der Basisplatine A.
• Ein Modul Batteriebetrieb 7,2V 13 ist ein Zusatzmodul und mit auf der Zusatzplatine Solarmodul integriert.
• Eine LED Anzeige 14 zeigt den Betriebszustand der Basisplatine A.
• Ein Display Zusatzmodul 15 zeigt die LED Anzeige für den CO2-Wert bzw. den CO-Wert oder anderen Sensorwerten der Basisplatine A. Außerdem sind eine Schnittstelle für die Displayansteuerung und ein akustisches Ausgabeelement integriert.
• Auf der Basisplatine A befinden sich ein Buzzer 16 und ein Datenlogger 17.

From the FIG. 1 the basic module is visible as a modular system. The basic module consists of the base board A and the following composition.

• A base board A serves as a motherboard for the entire circuit. It is a microprocessor with an intelligent firmware used as the heart. The internal memory serves both the firmware as well as data storage (data logger). Several sensor variants can be realized on the base board A, including the temporary storage of measured values.
• Base plate A has a quartz watch chip and integrated lithium cell with an operating time of 10 years.
• There are a CO2 sensor 1 and a CO sensor 2 are arranged. The circuit of the CO sensor is integrated with the base board A.
• A temperature sensor 3 is implemented on the base board A and has an accuracy of <+ - 1K. This serves to correct the temperature drift.
• A sensor for the measurement of temperature and humidity (detection of indoor climate data) is attached as a settable additional sensor I2C.
• On the base board A is a sensor for pressure 5 with absolute pressure.
• Furthermore, on the base board A, a sensor for light up to 2000lux given. It is used for sensor control during solar operation (energy management).
• A WLAN add-on module 7, a network add-on module 8 and other interface add-on modules are connected to the base board A via the connector (interface module).
• Furthermore there is a serial interface 0-20mA and 0-10V 10 available. This unit serves as an interface for the sensor data. Which sensor data is selected and about the Interface are defined via the firmware.
• The module network operation 12-24V 11 implemented as a remote power supply, the power supply of 12-24V to 5V of the base board A.
• A module solar operation 5V 12 is equipped with a solar panel 5V> 350mA or with several solar panels and two buffer batteries LiPo or similar. It is a remote add-on module, but not on the base board A.
• A module Battery operation 7.2V 13 is an additional module and integrated with the additional board solar module.
• An LED display 14 shows the operating state of the base board A.
• A display additional module 15 shows the LED display for the CO2 value or the CO value or other sensor values of the base board A. In addition, an interface for the display control and an acoustic output element are integrated.
• On the base board A there are a buzzer 16 and a data logger 17.

The following Figures 2 . 3 and 4 show certain applications in the form of modular systems for the assembly of the base board A.

The FIG. 2 illustrates a CO2 module for schools and conference rooms. The light sensor serves to increase the operating time. The base board A is equipped with a CO2 sensor 1, a sensor light 6, a module solar operation 5V 12 and an LED display 14th

• CO2-Sensor 1
• Temperatursensor PT1000 3
• Temperatur / Feuchte xxx 4
• Druck 5
• Licht 6
• Schnittstelle 0-20mA 0-10V 10
• LED Anzeige 14
• Netzbetrieb 12-24V 11.

The FIG. 3 shows a power-driven version for meeting and training rooms with data transmission, high accuracy and recording of indoor climate data, possibly with WLAN and presentation of the results on an iPAD or similar. For this purpose, the base board A is equipped with the following units:

• CO2 sensor 1
• Temperature sensor PT1000 3
• Temperature / humidity xxx 4
• Pressure 5
• Light 6
• Interface 0-20mA 0-10V 10
• LED display 14
• Mains operation 12-24V 11.

• CO2-Sensor 1
• CO-Sensor 2
• Temperatursensor PT1000 3
• Druck 5
• LED Anzeige 14
• Buzzer 16
• Netzbetrieb 12-24V 11.

From the FIG. 4 out is another modular design of the base board A for general applications in business and private rooms given. Temperature / humidity and pressure detection are used to reduce the CO2 measurement error. The base board A is equipped with the help of the modular system as follows:

• CO2 sensor 1
• CO sensor 2
• Temperature sensor PT1000 3
• Pressure 5
• LED display 14
• Buzzer 16
• Mains operation 12-24V 11.

• Zusatzmodul Schnittstelle WLAN - Connector 1
• Zusatzmodul Schnittstelle Netzwerk - Connector 1
• Zusatzmodul andere Schnittstelle - Connector 1
• Zusatzmodul Schnittstelle 4-20mA, 0-10V - Connector 1
• Zusatzmodul Solar-/Batteriebetrieb - Connector 2
• Fremdplatine Display - Connector 4

For example, the following interfaces can be integrated via expansion boards as plug-on modules:

• Additional module interface WLAN - Connector 1
• Additional module Interface Network - Connector 1
• Additional module other interface - Connector 1
• Additional module Interface 4-20mA, 0-10V - Connector 1
• Additional module solar / battery operation - Connector 2
• External PCB Display - Connector 4

The base board A has a dimension of 55 x 70 mm ² .

A general functional description of the method and arrangement for identifying gas concentrations in the air will now be presented. The corresponding sensors record CO2 and CO data. Both gases to be detected are fatal from a certain concentration. In the event of a fire, incomplete combustion gives rise primarily to CO; in the case of complete combustion, primarily CO2. The individual values and the combination of both can be used to derive very good parameters for hazards. The visualization is done like this described by an LED display 14. In addition, a signal output is still acoustically realized when exceeding the CO or CO2 limits.

The inventive method is based on two levels of detection of gas concentrations, in particular of a CO concentration.

In the first stage, the CO or CO2 concentration or temperature is sampled once per second. The attachment of molecules in the CO sensor is a dynamic process and requires a chemical equilibrium. The mathematical function for achieving the GG is known. Shortening the measurement, the GG is no longer reached. In the first stage, short measurement times are needed, which are less than one second. It is a slightly worse resolution due to the unfinished equilibrium process accepted. If there is no danger detection in this phase, it will continue to measure in this mode. When a signal is detected, the measurement time is automatically extended to significantly improve the resolution. These process steps can also be applied to two or more sensors.

This measurement algorithm is extremely energy-efficient, as it is carried out in the charge balance method. Thus, it can also be operated by battery-based systems over a long period of time. If a detection event occurs in the first method step, a second process step is started with the entire electronic evaluation.

In the second process step, both CO and CO 2 concentrations are determined with a longer measurement time. At the same time, all environmental parameters are measured and their influences on the measurement result are corrected in order to increase the measuring accuracy. The data thus corrected are fed to a neural network or other intelligent evaluation method which classifies the fire probability. Thus, no thresholds for the gas concentrations are needed, making the system very stable and reproducible. The evaluation of the measurement results is done via a μcontroller.

Through this structure of the process sections, another sensor can be added without major technical changes, which extends the system by a gas component, such as methane. Thus, the system can also be used as a leak detector for natural gas. Other sensors or combinations are possible.

A repeated execution shows the individual process steps for the identification of gas concentrations in the air.

In a first process step, the evaluation of the CO and / or CO 2 concentration in an algorithm with one measurement per second carried out. Here is a very fast detection takes place.

If in this first measuring section a signal recognition of a gas concentration of CO, a second process section is switched on, which is executed in longer measuring sections and in this case evaluates CO, CO2, air pressure, temperature and humidity as measurement results.

In this process step, a correction of the measured values, which are falsified by real environmental conditions, such as, for example, atmospheric pressure fluctuations, takes place.

Another special process step is the correction of the long-term drift of CO and CO2 sensors. Subsequently, a normalization of the sensor data take place. Further supply of the given measurement data to a neural network or other intelligent evaluation units can specify the evaluation of the measurement result.

• kein Brand
• Schwelbrand
• Brand
• CO-Alarm
• kein Brand, CO2, Anzeige Feuchte zu hoch, Lüftung des Raumes.

The following measurement results are conceivable:

• no fire
• smoldering
• fire
• CO alarm
• no fire, CO2, humidity indicator too high, room ventilation.

This danger detector in the form of the base board A is not a conventional fire detector, but a sensor module to increase safety in homes, schools, workspaces and other essential. In addition to the gas components, the temperature and humidity can be helpful as additional information providers.

In order to guarantee the accuracy of the measured values, a correction of the measured value drift is made by temperature changes, the measured value drift by changes in air pressure and the aging drift of the sensors. For this purpose, special mathematical and statistical methods are used. Each recorded raw data value is corrected before further processing. This method ensures high accuracy over years.

An LED display 14 outputs the values of the CO sensor 2 according to EN 50291. Green appears, for example, up to 30 ppm to a maximum of 120 minutes, blue from 31 to 50 ppm from 60 to 90 minutes, flashing blue from 51 to 100 ppm from 10 to 40 minutes, red from 101 to 300 ppm to 3 minutes and flashing red above of 300 ppm. After exceeding of concentrations or time intervals an acoustic alarm is issued. The concentrations and residence times are adjusted to the legal requirements of the federal states.

A third LED can be used to visualize a specific parameter or to display the Operating state are set. Data is output visually / acoustically and via configured interfaces, which have already been listed on this page.

reference numeral

A

Development board

1

CO2 sensor

2

CO sensor

3

temperature sensor

4

Temperature / humidity

5

print

6

light

11

Mains operation 12-24V

14

LED display

16

buzzer

17

data logger

B

Expansion board (attachable to A)

7

WLAN add-on module

8th

Network add-on module

9

USB interface

10

Interface 0-20mA 0-10V

15

Display add-on module

C

expansion board

12

Solar operation 5V

13

Battery operation 7.2V

Claims (11)

Method for identifying gas concentrations in the air, wherein parameters are evaluated by means of data processing using reference and / or classification patterns and, depending on the results of the evaluation, an alarm output and / or visualization is made, wherein measured values are determined via sensors, characterized that in a first method step, a gas concentration is determined by sensors or a temperature in short measurement times of once per second, and a second method step with a measurement time extension of once every second of the measurement of the gas concentration and a simultaneous measurement of a signal acquisition of a deviating from the normal conditions Pressure and / or a temperature and / or humidity via given sensors is performed and depending on the sensor data fusion, a correction of the gas concentration and a normalization and subsequently a trained neural network is acted upon with this data to an evaluation and hazard assessment with an alarm output and to perform a visualization. A method according to claim 1, characterized in that in the first method step, the gas concentration is determined via CO2 and CO sensors. A method according to claim 1, characterized in that in the first method step, a temperature is determined by a temperature sensor. A method according to claim 1, characterized in that in the second method step with a measuring time extension, the measurement of the gas concentration via a CO and / or CO2 sensor is performed. A method according to claim 1, characterized in that by taking the parameters of temperature and / or pressure and / or humidity, the efficiency of the evaluation and hazard assessment of the gas concentration is increased. A method according to claim 1, characterized in that the sensor data fusion of the CO sensor (2) and the CO2 sensor (1) via parameter specifications an accurate representation of hazards, especially of fires, is determined. Method according to the preceding claims, characterized in that a correction of the existing temperature, pressure and Long-term drift of the measured data is carried out according to a defined procedure. Arrangement for carrying out the method, wherein a two-stage detection arrangement for extremely fast detection of dangerous situations is present and in the second stage an accurate, fast and complex evaluation and an energy supply via a power supply and / or solar operation and / or by battery operation is possible and an optical display is present. Arrangement according to claim 8, characterized in that the configuration of the base board (A) for assembly in the form of a modular principle is given. Arrangement according to claim 8, characterized in that the base board (A) has a buzzer (16) and a data logger (17). Arrangement according to the preceding claims, characterized in that in particular the CO2 sensor (1) and the CO sensor (2) have a long service life and a low cross-sensitivity.

Images