Compound sensor and method for diagnosis of biological process diagnosis and analysis of material characteristic analysis

A composite sensor and biological process technology, applied in the field of biological process diagnosis, can solve problems such as single, signal lag, and inflexible feedback

Active Publication Date: 2013-09-18
CHINA AGRI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the previous monitoring and diagnosis methods were too singl

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  • Compound sensor and method for diagnosis of biological process diagnosis and analysis of material characteristic analysis
  • Compound sensor and method for diagnosis of biological process diagnosis and analysis of material characteristic analysis
  • Compound sensor and method for diagnosis of biological process diagnosis and analysis of material characteristic analysis

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Embodiment 1

[0044] For the structure diagram of the composite sensor, please refer to figure 1 . Firstly, under the baseline condition of organic loading rate of 1g COD / L / d in the packed bed reactor, the signal relationship of the three sensors of MFC, pH meter and gas flow meter was compared online through the signal fluctuation caused by pulse injection. Increase the pulse matrix concentration (mixed concentration 0 ~ 500mgCOD / L), the voltage signal change (ΔU), gas flow rate change (ΔgFR) and gas cumulative volume change (ΔgV) of the MFC increase accordingly, and the pH change (ΔpH) increases accordingly decrease. The relationship between ΔU and substrate concentration can be described by the Monod equation. From the equation, it is known that the biofilm MFC (Biofilm MFC, which has electrochemically active biofilm adsorption from the anode) has a higher saturation value than the control MFC (Control MFC), that is, has a wider Concentration detection space. In order to further compa...

Embodiment 2

[0047] Using the device in Example 1, sodium acetate is used as a pulse matrix to inject samples to investigate the changes of different process variables, mainly including the output voltage, pH, gas flow rate, gas production rate, external circulation liquid SCOD, acetic acid, propionic acid and total of MFC. VFAs. Online data are based on the average of three repeated pulse injections, and offline parameter analysis is also based on the average of three repeated pulse injections. All injection injections are based on 1g COD / L / d OECD continuous operation to provide sufficient buffer capacity and stable microbial metabolic activity for the biogas fermentation system. Figure 4 It is the change of various parameters when injecting sodium acetate with a volume of 1mL and a concentration of 200g / L. MFC produces obvious voltage peaks, which are consistent with gas flow convex peaks and pH concave peaks. In addition, off-line VFAs analysis is especially for acetic acid in the filt...

Embodiment 3

[0049] Sodium acetate and cellulose injection:

[0050] Using the device in Example 1, sodium acetate is used as a pulse matrix to inject samples to investigate the changes of different process variables, mainly including the output voltage, pH, gas flow rate, gas production rate, external circulation liquid SCOD, acetic acid, propionic acid and total of MFC. VFAs. Online data are based on the average of three repeated pulse injections, and offline parameter analysis is also based on the average of three repeated pulse injections. All injection injections are based on 1g COD / L / d OECD continuous operation to provide sufficient buffer capacity and stable microbial metabolic activity for the biogas fermentation system. Image 6 is the change of each parameter when injecting a mixture of sodium acetate and cellulose with a volume of 1mL. The concentrations of sodium acetate and cellulose in the mixture are both 200g / L, which is similar to the case of injecting only sodium acetate...

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Abstract

The invention belongs to the field of biological process diagnosis, and in particular relates to a compound sensor and a method for biological process diagnosis and material characteristic analysis. The invention provides a modular compound sensor for online biological process diagnosis and analysis of characteristic analysis. The sensor mainly consists of a packed bed bio-membrane reactor, a microbial fuel cell (MFC), a gas flowmeter and a pH meter, wherein the packed bed bio-membrane reactor performs a quick biochemical reaction for a liquid phase organic matter in a target biological process, and the working state of the target biological process is diagnosed by means of online-detecting the gas flow, the pH of a fermenting liquid and electric signals of the MFC and comparing the signals among the three. The modular compound sensor is mainly characterized in that various sensors comprehensively diagnose and work stably; the sensor is in modular design and strong in mobility; the sensor can realize online diagnosis of industrial biological processes (such as biogas fermentation and hydrogen fermentation).

Description

technical field [0001] The invention belongs to the field of biological process diagnosis, in particular to a composite sensor and method for biological process diagnosis and material characteristic analysis. Background technique [0002] Anaerobic fermentation is of great significance to generate renewable energy (biogas, hydrogen, ethanol, etc.) while treating waste. However, due to the complexity of the fermentation process, anaerobic fermentation is often referred to as a "black box". Since anaerobic fermentation is essentially a biochemical process catalyzed by microorganisms, the most direct and effective research method is to observe the microbial population itself, which requires the use of molecular biology and morphological research methods, such as FISH, DGGE, etc., but these techniques It is difficult to realize online, and even if it is realized, it loses the significance of monitoring due to the high cost. It is a common method to reflect the fermentation pro...

Claims

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Application Information

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IPC IPC(8): G01N27/27
Inventor 刘志丹李保明刘京张源辉
Owner CHINA AGRI UNIV
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