Output Signal Of Sensor Research Articles

Vibration Monitoring for Position Sensor Fault Diagnosis in Brushless DC Motor Drives

A non-invasive technique for condition monitoring of brushless DC motor drives is proposed in this study for Hall-effect position sensor fault diagnosis. Position sensor faults affect rotor position feedback, resulting in faulty transitions, which in turn cause current fluctuations and mechanical oscillations, derating system performance and threatening life expectancy. The main concept of the proposed technique is to detect the faults using vibration signals, acquired by low-cost piezoelectric sensors. With this aim, the frequency spectrum of the piezoelectric sensor output signal is analyzed both under the healthy and faulty operating conditions to highlight the fault signature. Therefore, the second harmonic component of the vibration signal spectrum is evaluated as a reliable signature for the detection of misalignment faults, while the fourth harmonic component is investigated for the position sensor breakdown fault, considering both single and double sensor faults. As the fault signature is localized at these harmonic components, the Goertzel algorithm is promoted as an efficient tool for the harmonic analysis in a narrow frequency band. Simulation results of the system operation, under healthy and faulty conditions, are presented along with the experimental results, verifying the proposed technique performance in detecting the position sensor faults in a non-invasive manner.

Signal processing method of bubble detection in sodium flow based on inverse Fourier transform to calculate energy ratio

Electromagnetic vortex flowmeter is a new type of instrument for detecting leakage of steam generator, and the signal processing method based on the envelope to calculate energy ratio can effectively detect bubbles in sodium flow. The signal processing method is not affected by changes in the amplitude of the sensor output signal, which is caused by changes in magnetic field strength and other factors. However, the detection sensitivity of the electromagnetic vortex flowmeter is reduced. To this end, a signal processing method based on inverse Fourier transform to calculate energy ratio is proposed. According to the difference between the frequency band of the bubble noise signal and the flow signal, only the amplitude in the frequency band of the flow signal is retained in the frequency domain, and then the flow signal is obtained by the inverse Fourier transform method, thereby calculating the energy ratio. Using this method to process the experimental data, the results show that it can detect 0.1 g/s leak rate of water in the steam generator, and its performance is significantly better than that of the signal processing method based on the envelope to calculate energy ratio.

Self-integrating current sensor for fast pulsed current monitor in transmission line.

The fast linear transformer driver (FLTD) utilizes a water-insulated transmission line as its secondary. To monitor the fast pulsed current and locate the fault, a compact self-integrating current sensor is developed. Print circuit board (PCB) coils and PCB integrating resistors are used to form the current sensor. By soldering a large number of chip resistors, PCB integrating resistors with various resistance and low inductance can be obtained. The current sensor is designed in a coaxial structure to reduce its inductance and size and can be installed on the inner conductor of the FLTD's secondary water-insulated transmission line with a small opening. The principle and matching schemes for the current sensor are theoretically analyzed with the circuit principle. Both simple matching and two-stage division can be used to obtain signals without oscillation. The time constant of the two schemes is the same. However, the sensitivity of the current sensor with two-stage division is lower than that with simple matching. A 100 kV step pulse generator is used as the pulsed high current generator to verify the properties of the current sensor. The designed current sensor could respond to the step current pulse with the rise time of 4ns. The matching scheme is verified to be effective with step response experiments. Finally, the influence of the parameters, which are the coil type, the angle between the PCB coil and the magnetic flux, the resistance of the integrating resistor, and the length of the measuring cable, on the output signal of the current sensor is studied.

Nonlinear vibration of conical shell with a piezoelectric sensor patch and a piezoelectric actuator patch

In this study, nonlinear vibration of a conical shell with a piezoelectric sensor patch and a piezoelectric actuator patch is evaluated. The strain displacement relation is considered to be nonlinear and based on that the equations of motion and piezoelectric sensor output signal are extracted. For the first time, nonlinear electromechanical equations of motion for the conical shell with a piezoelectric sensor layer and a piezoelectric actuator layer are extracted in detail and presented. The producer of extraction of conical shell electromechanical equations of motions is presented for further clarifications. The output signal of the piezoelectric sensor patch considering the nonlinear strain displacement equation of motion is derived. For controlling the vibration actively, a proportional controller is defined by which the applied actuator signal is determined. The nonlinear electromechanical equations of motion are expanded based on conical shell strains. By applying the Galerkin method, the nonlinear time-domain equations are extracted. The complicated attained equations are solved using the harmonic balance method. Conical shell nonlinear frequency response in uncontrolled condition and controlled condition is computed and compared with each other. The frequency response shows that the active vibration control of the conical shell increases the nonlinearity of the system and reduces the vibration amplitude. In addition, free nonlinear vibration of the proposed system is calculated and presented. The results show higher impacts of piezoelectric patches on the conical shell free vibration response and they can reduce the vibration amplitude dramatically.

Enhancement of unsteady frequency responses of electro-thermal resonance MEMS cantilever sensors

Unsteady frequency response of in-plane electro-thermal MEMS-based cantilever sensors can cause up-/down-shifting of the resonance phase, which becomes an inhibitive factor in resonance locking using a phase-locked loop setup. Moreover, the inconsistency of resonance phase during real-time measurement potentially causes inaccuracy in resonant-frequency locking. In this work, reference parameters are differentially subtracted from the sensor output signals to enhance the characteristic of frequency response. As a calculation result, a constant resonance phase can be successfully achieved by adjusting the reference parameters close to the sensor baseline, both in sensor amplitude and phase.

Adaptive Fault-Tolerant Control During the Mode Switching for Electric Vehicle Dual-Mode Coupling Drive System

As a new drive system for electric vehicles, the dual-mode coupling drive system can automatically switch between centralized and distributed drive modes and realize two-speed gear shifting. Because the actuator’s displacement signal affects the mode-switching control, when failure occurs at the angle-displacement sensor, the mode-shifting quality is likely to drop greatly, even possibly leading to shift failure. To address the angle-displacement sensor failure and improve the reliability of the shift control, an adaptive fault-tolerant control method is proposed and verified. First, the effect of the output signal of the angle-displacement sensor in the mode-switching control process is analyzed. Then, an adaptive mode-switching fault-tolerant control method is designed based on the Kalman filter and fuzzy theory. Finally, the feasibility of the control effect is verified through simulations and vehicle experiments. The results indicate that the proposed method can effectively eliminate the signal noise of the angle-displacement sensor and successfully switch the modes when the sensor fails. It provides a reference for ensuring the working quality of similar electric drive systems under sensor failures.

Fault Tolerant and Nano Displacement Drive Control Method of Photoelectric Motor for Battery Electric Vehicle

The low-resolution photoelectric position sensor is used, that is, Hall position sensor replaces the traditional photoelectric encoder and other high-resolution position sensors to monitor the rotor position. However, because the three-phase Hall position sensor can only output six position signals, a hardware circuit design of low-resolution position sensor monitoring rotor position signal is proposed. Meanwhile, nanotechnology has been introduced in the study of micro drive of battery electric vehicle (BEV). BEV driver has some disadvantages such as hysteresis, creep and nonlinearity, which seriously affects its application in nano environment. A nano displacement sensor is designed for the characteristics of BEV driver. The nonlinear problem of micro driver is solved through the closed-loop control of position feedback. In the test, through the verification of rotor position and current waveform, it can be proved that the method based on photoelectric position sensor and rotor position signal monitoring can ensure the low deviation of rotor position calculation and correct output signal of three-phase photoelectric position sensor. The decoupling performance of vector control is verified by 3/2 transformation. In the displacement detection of micro driver, the designed nano displacement sensor has higher resolution and its performance is better than that of the previous three generations of displacement sensors.

Design of ECU (Electronic Control Unit) as Biogas Pressure Control to Micro Genset

Biogas fueled generator has a unique character because the converter kit on the generator has the characteristic of absorbing the biogas supply. Therefore, in this study, biogas is accommodated in a plastic container equipped with a valve that can adjust the amount of biogas supply pressure. Combustion in the Genset combustion chamber will occur if the ratio of air supply and supply of biogas (AFR = Air to Fuel Ratio) meets the stoichiometric number. So a ratio control is needed on air supply and biogas supply, which can follow changes in biogas conditions in plastic bags and generator loads. For this reason, this paper presents an ECU (Electronic Control Unit) that can regulate the ratio of air supply to biogas supply by using a servo motor valve, which is commanded by a control signal from the ECU. The resulting ECU prototype is equipped with a multi-input connector (to receive the signal output of CH 4 methane gas sensor and the biogas supply pressure sensor), multi-output (control signal to the servo motor valve), and multi regulators to adjust the Set Point value for the methane gas content CH4, the value of the set point of the biogas supply pressure and to tune the value of the proportional gain control (KP). The results of the ECU performance test by trial and error by giving a dummy input signal (analogy to the signal output of methane gas sensor and the analog of the pressure sensor output signal in the form of an electric voltage generated from the signal generator) can drive the servo motor, valve air supply, and servo motor, valve supply biogas. Accordance with the gain control input from the regulator.

Three-axis force sensor miniaturized by 3D microstructuring using high-temperature punch creep-forming process

This study developed a small, three-axis force sensor with a 3D microstructure for installation into a robot gripper. The sensor was manufactured by high-temperature punch creep-forming of 5 μm thick single-crystal silicon (Si) cantilevers during an impurity diffusion process for piezoresistors. The punch creep-forming could achieve a large out-of-plane deformation of the Si cantilevers within a small area. The punch creep-forming simulations were conducted for designing the 3D formed force sensor based on the creep constitutive equation for a 5 μm thick Si film at 1050 °C. Consequently, this study succeeded in fabricating a 3D formed force sensor with a 320 μm diameter hemispheric structure by punch creep-forming without breaking the structure. The force sensor was set on a printed circuit board and packaged using urethane resin. The viscoelastic response of the resin-packaged sensor was evaluated by conducting stress-relaxation (SR) tests and dynamic mechanical analysis, and characterized by a five-element generalized Maxwell model (GMM). In the SR tests, the sensor output signal in the vertical direction showed a strong correlation with the displacement applied to the test, whereas that in the lateral direction was closely related to the load acting on the sensor. Numerical analyses based on the GMM could estimate the load and displacement acting on the sensor from its output signal.

A hybrid noise removal algorithm for MEMS sensors

The use of microelectromechanical systems (MEMS) in electronics, automotive, consumer and medical sector is increasing rapidly. It is expected that by 2024 the Global MEMS and sensor market will reach the value of 93 billion dollars. MEMS inertial measurement sensors (accelerometer and gyroscopes) are used in low end consumer electronics such as smartphones to high end products such as drones used in military applications. MEMS IMU (Inertial Measurement Unit) are often deployed in dynamic environment such as in machining process for condition monitoring, vehicles for identifying driving behaviors, wearable technology for fall detection and many others. Consequently, Gaussian noise is always present in the output signal of such sensors. Denoising the output signal is critical for feature extraction and data analysis. Recently hybrid approaches for noise removal have gained much research attention. The aim of this paper is to present a hybrid noise removal algorithm for MEMS IMU sensors. In this technique, the signal to noise ratio has been improved and remove glitches by minimizing the hybrid noise from the original output signal of the MEMS IMU sensor.

Detection and Early Warning of Toxic Gases Based on Semiconductor Wireless Sensors

This paper studies a semiconductor wireless sensor system, which is composed of a semiconductor wireless sensor sampling circuit, gas‐sensitive signal alarm and wireless transmitting circuit, and wireless radio frequency signal receiving circuit. The system is suitable for wireless monitoring of hydrogen fluoride gas in chemical plants. The hydrogen fluoride gas sensor is designed, integrated, and classified according to the polarity and size of the sensor output signal. The signal processing circuit of the sensor output signal is made with an integrated design. This paper developed a simulation experimental system for the wireless monitoring network characteristics of toxic hydrogen fluoride gas and completed the monitoring system’s sensor characteristic calibration and accuracy comparison simulation experiment, the communication distance test experiment of the communication system, and the research experiment on the influence of environmental humidity on the sensor characteristics of the monitoring system. In terms of software, the workflow of network nodes has been optimized. Since the structure of the wireless sensor network is not exactly the same in different application fields, the toxic gas monitoring system based on wireless sensor networks must focus on extending the network’s life cycle. Without affecting the normal operation of the system, distributed compressed sensing can greatly extend the service life of the system. Therefore, this subject combines the compressed sensing technology developed in recent years with the air monitoring system for the processing of transmission data, in order to achieve the purpose of further reducing the energy consumption of the system. The simulation experiment demonstrated that the lmF neural network combined with gas sensor array technology can realize qualitative identification, quantitative analysis of single gas, and quantitative analysis of mixed combustible gas. The research work in this area also provides a new way to further combine the miniature hydrogen fluoride gas sensor unit with sensor technology, integrate the hydrogen fluoride gas sensor unit and the electronic tag, and expand the wireless application of the gas sensor.

Chemical static equipment commonly used sensor fault detection and isolation methods

This paper conducts a study on the faults of common sensors involved in chemical static equipment. Firstly, the types and characteristics of commonly used sensors of chemical static equipment are analyzed, and the characteristics of sensor output signal changes are summarized with the working characteristics of chemical equipment. Then the faults of static equipment sensors are classified and a fault model is established. Through the study of sensor fault detection and isolation methods at home and abroad, the overall scheme of sensor system fault detection and isolation combining single sensor fault detection and isolation method and multi-sensor fault detection and isolation method is proposed. According to the characteristics that chemical processes are generally in a dynamic and stable state and there is a certain correlation between the signals of each detection point in the equipment, a sensor system model is established by using the correlation of multiple sensors on the equipment, and when a sensor in the sensor system fails, the system model changes beyond the threshold value, and a different form of residual generation is used to determine which sensor is faulty and achieve the detection and isolation of faulty sensors. The fault detection method is simulated and studied by using relevant software, combined with a support vector machine and neural network toolbox. The results show that the method proposed in this paper can effectively complete the fault detection and isolation of sensors commonly used in chemical static equipment. The accuracy and reliability of the prediction model are high.

The Effect of Icing on the Output Parameters of the Airflow-Angle Sensor in Case of Failure of the Electric Heating System

At present, with the intensive operation of aircrafts in extremely harsh air conditions, their all-weather use, the work related to improving the flight safety is especially relevant. One of the directions of work in this topic is the study of the types of parametric failures of onboard equipment associated with the influence of the external environment in order to assess their impact on interacting systems and develop recommendations for identifying and countering detected failures. The presented paper considers the results of a full-scale experiment to determine the possibility of operation of the aerodynamic angle sensor in artificially formed icing conditions in case of failure of its electric heating system, as well as a description and results of subsequent modeling of the sensor icing process, and an assessment of its effect on the accuracy characteristics of the sensor output signal. The statement of the research problem is formulated as follows: it is necessary to ensure the testing of the sensor and the subsequent processing of the results obtained in order to form a generalized mathematical model of the sensor icing process, as well as to solve the problem of introducing additional errors into the sensor signals, which makes it possible to study the behavior of air signal systems using vane sensors of aerodynamic angles with artificially introduced failures. A full-scale experiment was carried out in an air-cooling tube on the basis of the enterprise JSC "UKBP". Numerical modeling and determination of correction factors were carried out in the software packages Ansys FENSAP ICE and MathCAD. Analysis of the results achieved in the course of modeling confirmed the convergence of the model obtained with the data of real experiments in an air-cooling tube. The data obtained made it possible to confirm the possibility of detecting distorted values for the angle of attack by the parametric quorum control method.

Design of weak magnetic signal detection system for residual stress detection

The residual stress detection based on eddy current method belongs to weak signal detection. Aiming at the problems of sensor output signal with many channels, large amount of data, wide frequency range and low signal-to-noise ratio, a weak magnetic signal detection system is designed and implemented with Zynq-7020 (ARM+ FPGA) as the development board and peripheral hardware circuit. Among them, FPGA controls the peripheral chip to complete the signal source excitation and 8-channel high-speed data acquisition and preprocessing, and then the data is transmitted to ARM through AXI bus. ARM extracts the signal characteristics through digital orthogonal lock-in amplification technology according to the control parameters provided by the upper computer, and feeds back the results to the upper computer. The test results show that the system has high stability and detection accuracy, and meets the overall requirements of the system.

A METHOD OF REDUCING THE ERROR IN DETERMINING THE ANGULAR DISPLACEMENTS WHEN USING INDUCTIVE SENSORS

Goal. Representation of a special mathematical software for determining the angular displacements of the rotor of the induction angle sensor – resolver (rotating transformer) for applications in which the speed of the sensor's rotor is close to zero. As well as performing its experimental verification. Methodology. The presented method is based on the determination of the phase shift angle of the output signals of the induction sensor, which is determined by comparing the obtained arrangements of signal values with a circular discrete convolution in order to achieve the most precise approximation of the obtained signal values to cosine and sine. The conversion of orthogonal components to an angle is based on the use of a digital phase detector which is use of a software comparator and inverse trigonometric functions. Results. Based on the obtained results of mathematical modeling and experimental research, the characteristic dependencies of the angle of rotation of the rotor of the induction sensor relative to its stator, the nature of which is linear, were obtained. In addition, the estimation of measurement errors of angular displacements is carried out that occur when defining such angles by the method offered. The obtained results of the computer simulation taking into account the high signal noise, as well as the results of experimental investigations, confirm the high precision of this method and the fact that it can be used in systems where high positioning accuracy is required and the speed of the sensor shaft is close to zero. Originality. This article introduces, for the first time, special mathematical software for a new method of determining the angular displacements of the rotor of an induction sensor, which is based on the determination of the orthogonal components of the signal in combination with the use of a circular discrete convolution in the determination of the phase shift angle of the induction sensor signals. Practical meaning. The proposed method does not require the use of demodulators, counters and quadrant tables associated with conventional methods for determining the phase shift of signals. The presented method can be used to measure the full range of 0-2p angular displacements in real time, is simple and can be easily implemented using digital electronic circuitry.

Stable, High‐Efficiency Voltage‐Dependent Color‐Tunable Organic Light‐Emitting Diodes with a Single Tetradentate Platinum(II) Emitter Having Long Operational Lifetime

Voltage-dependent, color-tunable organic light-emitting diodes (OLEDs) are appealing tools that can be used for the visualization of electronic output signal of sensors. Nonetheless, the literature-reported color-tunable OLEDs that have a simple single-cell device structure suffer from relatively low efficiency, pronounced efficiency roll-off, color-aging, and short operation lifetime, all of which limit their practical applications. Here, a novel co-host-in-double-emissive-layer (CHIDEL) device, designed to enhance the performance of color-tunable OLEDs with the use of a single tetradentate Pt[O^ N^ C^ N] emitter, is described. When Pt-X-2 is used as a single emitter in an optimized CHIDEL device, a white OLED with tunable Commission International de I'Eclairage (CIE) coordinates from (0.47, 0.44) at 3V to (0.36, 0.48) at 11V, a high color rendering index of 82, and high external quantum efficiency (EQE) of up to 20.75% can be achieved. By using Pt-X-4 as a single emitter, the voltage-dependent color-tunable CHIDEL device, with CIE coordinates shifted from (0.56, 0.43) at 3V to (0.42, 0.55) at 11V, demonstrates a high luminance of beyond 90 000cd m-2 and a high EQE of 23.23% at a luminance of 1300cd m-2 . A long-lifetime time to 90% of the initial luminance (LT90 ) of almost 20000 h is demonstrated for the color-tunable OLED with Pt-X-4 emitting dopant.

Chemoresistive Nanostructured Sensors for the Analysis of Human Tumor Tissue Exhalations

One of the greatest goals in medicine is early-stage tumor detection. An effective prevention is crucial to allow physicians and surgeons to intervene on tumor affected patients with the available therapies and surgical techniques with a high probability of success. The purpose of this research relies on the identification of cancer presence by detecting the volatile organic biomarkers directly produced by cancer cells. Cancer cells produce different biomarkers with respect to healthy cells, mainly due to the altered metabolism and cellular membrane peroxidation. This difference can be recognized by using an innovative device manufactured in the Sensor Laboratory of the University of Ferrara, hosting a specific sensor array chosen for biological sample investigation. The sensor array is composed by four chemoresistive metal-oxide nanostructured sensors, able to detect gases in low concentration (up to 1 ppm) with excellent stability and repeatability. In this study, a fast-responding, reliable and reproducible sensing device, named SCENT B1[1], showed to be capable of discriminating cancerous cells from healthy ones, proving to be an efficient and low-invasive screening system.The device combines a specific electronic and pneumatic system to a specifically selected sensor array. The sample is inserted inside a sample box through a support composed by Petri dishes, while a stabilized ambient airflow conveys the exhalations to sensors. Sensor responses are then statistically analyzed by principal component analysis (PCA).Measurements have been performed on cancer and healthy tissues, extracted during surgery from human colon and rectum, with the future aim of extending the study to the other tumor types.Sensors chosen are the following: a mixture of tin and titanium oxides with addition of gold (ST25Au), tungsten oxide (W11), a mixture of tin, titanium and niobium oxides (STN) and a solid solution of titanium oxide, tantalum and vanadium (TiTaV). Sensors have been selected after a feasibility study performed on immortalized cells of diverse types, where sensors responses have been correlated with cell type and cell initial plating concentration of the samples; the measures have been performed after 24, 48, 72 hours of incubation.The sensor output signal is a voltage directly proportional to the sensor conductance; it depends on the chemical redox reactions taking place on sensor surface [2,3]. In Figure (a) the response R=ÄG/G for each sensor is reported, where ÄG is the difference between the sensor conductance with and without the metabolites expelled by the cells of a tissue. All four sensors gave larger responses (although with different amplitudes) to the tumor tissue with respect to the healthy one. Smaller and reproducible responses were given by the breeding ground (DMEM) only, confirming that it does not alter the measurement.The results are consistent with the stronger metabolism of tumor cells with respect to the healthy ones, because the former emits larger amounts of volatile biomarkers [4,5]. Other tests proved also that different initial plating concentrations (250k, 500k and 1M) of cell give increasing responses, as shown in Figure (b). From this study what emerges is that the device is capable of distinguishing different cell samples basing on their health status and concentrations. The encouraging results of this study are the basis of a deepen study for the clinical validation of the device as a oncologic screening device.

Twin Marine Hydrokinetic Cross-Flow Turbines in Counter Rotating Configurations: A Laboratory-Scaled Apparatus for Power Measurement

This article proposes an experimental apparatus design to measure the power of a cross-flow marine hydrokinetic turbine system operating in a laboratory water tunnel. Data, from one Hall sensor output signal, was processed to capture the three types of torque exerted on the turbines: mechanical loss, brake, and hydrodynamic torque. The method was then applied to compare the power of a twin turbine system in different counter-rotating configurations. Controlled by a hysteresis brake, the tip-speed-ratio was varied in a constant freestream velocity of 0.316 m/s. While the braking torque was independent of the speed, the mechanical loss was found to depend on the system rotational speed and the amount of mass mounted on the mechanical support. In a counter-rotating configuration, the turbines were synchronized through a pair of spur gears and timing pulleys. Operating at the average chord based Reynolds number of 8000, each turbine had three NACA0012 blades mounted at 15∘ pitch angle. The power coefficient results of 8 turbine configurations showed the tendency of power enhancement of counter-rotating configurations due to blade interaction and increase in blockage ratio. Comparison of the results suggested direct application in a river flow scenario and manipulation of the blade interaction for optimal power production.

Nonlinear Correction of LVDT Sensor Based on ACO-BP Neural Network

In this paper, the output signal of the linear variable differential transformer type displacement sensor (LVDT) is nonlinear, a BP neural network optimized by the ant colony algorithm is designed to fit and correct the nonlinear output of the LVDT. This scheme first uses the ant colony algorithm to search the optimal range of neural network weights and thresholds, and then uses the BP neural network to fit any non-linear function to LVDT nonlinear output fitting and correction, which overcomes the shortcomings of BP neural network easily falling into local minimum and slow convergence. Through MATLAB simulation experiments, it is concluded that the convergence speed, average error and average error percentage of the ACO-BP neural network are better than the BP neural network. This solution has certain feasibility for solving the LVDT nonlinear problem, and provides a new solution for the sensor nonlinear correction.

Selective detection of complex gas mixtures using point contacts: concept, method and tools.

Of all modern nanosensors using the principle of measuring variations in electric conductance, point-contact sensors stand out in having a number of original sensor properties not manifested by their analogues. The nontrivial nature of point-contact sensors is based on the unique properties of Yanson point contacts used as the sensing elements. The quantum properties of Yanson point contacts enable the solution of some of the problems that could not be solved using conventional sensors measuring conductance. In the present paper, we demonstrate this by showing the potential of quantum point-contact sensors to selectively detect components of a gas mixture in real time. To demonstrate the high efficiency of the proposed approach, we analyze the human breath, which is the most complex of the currently known natural gas mixtures with extremely low concentrations of its components. Point-contact sensors allow us to obtain a spectroscopic profile of the mixture. This profile contains information about the complete set of energy interactions occurring in the point contact/breath system when the breath constituents adsorb to and desorb from the surface of the point-contact conduction channel. With this information we can unambiguously characterize the analyzed system, since knowing the energy parameters is key to successfully identifying and modeling the physicochemical properties of various quantum objects. Using the point-contact spectroscopic profile of a complex gas mixture it is possible to get a functional dependence of the concentration of particular breath components on the amplitude of the sensor output signal. To demonstrate the feasibility of the proposed approach, we analyze the point-contact profiles from the breath of several patients and compare them with the concentrations of serotonin and cortisol in the body of each patient. The obtained results demonstrate that the proposed methodology allows one to get an effective calibration function for a non-invasive analysis of the level of serotonin and cortisol in the human body using the point-contact breath test. The present study indicates some necessary prerequisites for the design of fast detection methods using differential sensor analysis in real time, which can be implemented in various areas of science and technology, among which medicine is one of the most important.